https://www.cds.caltech.edu/~murray/wiki/api.php?action=feedcontributions&user=Yilinmo&feedformat=atomMurrayWiki - User contributions [en]2020-10-29T00:41:11ZUser contributionsMediaWiki 1.23.12https://www.cds.caltech.edu/~murray/wiki/index.php?title=Sergio_Pequito,_31_03_2015Sergio Pequito, 31 03 20152015-03-31T20:51:24Z<p>Yilinmo: </p>
<hr />
<div>Sérgio Pequito, a Postdoctoral Researcher at Upenn working with Prof. George J. Pappas, will visit Caltech on 31 March 2015 and give a group seminar.<br />
<br />
=== Schedule ===<br />
<br />
Tuesday<br />
* 9:30a : Meeting with Richard, 109 Steele<br />
* 10:00a: Open<br />
* 10:45a: Open<br />
* 11:30a: Set up for seminar and grab lunch<br />
* 12:00p: Lunchtime seminar, 213 ANB<br />
* 1:15p: Open<br />
* 2:00p: Changhong Zhao, 232 ANB<br />
* 2:45p: Yorie Nakahira, 239 ANB<br />
* 3:30p: Enrique Mallada, 338 ANB<br />
* 4:15p: Open<br />
* 5:00p: Open<br />
* 5:45p: Done for the Day<br />
<br />
=== Seminar info ===<br />
<br />
Speaker: Sérgio Pequito<br><br />
Date & Time: Tuesday, March 31st (12pm)<br><br />
Location: 213 Annenberg<br><br />
Affiliation: University of Pennsylvania<br><br />
<br />
'''A Framework for Structural Input/Output and Control Configuration Selection of Large - Scale Systems'''<br />
<br />
The structure control system design consists mainly of two steps: input/output (I/O) selection and control configuration (CC) selection. The first one is devoted to the problem of computing how many actuators/sensors are needed and where should be placed in the plant to obtain some desired property. Control configuration is related to the decentralized control problem and is dedicated to the task of selecting which outputs (sensors) should be available for feedback and to which inputs (actuators) in order to achieve a predefined goal. The choice of inputs and outputs affects the performance, complexity and costs of the control system. Due to the combinatorial nature of the selection problem, an efficient and systematic method is required to complement the designer intuition, experience and physical insight.<br />
<br />
Motivated by the above, this presentation addresses the structure control system design taking explicitly into consideration the possible application to large - scale systems. We provide an efficient framework to solve the following major minimization problems: i) selection of the minimum number of manipulated/measured variables to achieve structural controllability/observability of the system, and ii) selection of the minimum number of measured and manipulated variables, and feedback interconnections between them such that the system has no structural fixed modes. Contrary to what would be expected, we showed that it is possible to obtain the global solution of the aforementioned minimization problems in polynomial complexity in the number of the state variables of the system. To this effect, we propose a methodology that is efficient (polynomial complexity) and unified in the sense that it solves simultaneously the I/O and the CC selection problems. This is done by exploiting the implications of the I/O selection in the solution to the CC problem.<br />
<br />
'''Bio'''<br />
<br />
Sérgio Pequito is a postdoctoral researcher at University of Pennsylvania. He obtained his PhD in Electrical and Computer Engineering from Carnegie Mellon University and Instituto Superior Técnico, through the CMU-Portugal program. Furthermore, he received his BSc and MSc in Applied Mathematics from the Instituto Superior Técnico. Pequito's research consists in understanding the global qualitative behavior of large scale systems from their structural or parametric descriptions and provide a rigorous framework for the design, analysis, optimization and control of large scale (real-world) systems. Pequito was awarded with the best student paper finalist in the Conference on Decision and Control 2009, the ECE Outstanding Teaching Assistant Award at Carnegie Mellon University, and the Carnegie Mellon Graduate Teaching Award (university-wide) honorable mention, both in 2012.</div>Yilinmohttps://www.cds.caltech.edu/~murray/wiki/index.php?title=Sergio_Pequito,_31_03_2015Sergio Pequito, 31 03 20152015-03-31T17:09:13Z<p>Yilinmo: </p>
<hr />
<div>Sérgio Pequito, a Postdoctoral Researcher at Upenn working with Prof. George J. Pappas, will visit Caltech on 31 March 2015 and give a group seminar.<br />
<br />
=== Schedule ===<br />
<br />
Tuesday<br />
* 9:30a : Meeting with Richard, 109 Steele<br />
* 10:00a: Open<br />
* 10:45a: Enrique Mallada, 338 ANB<br />
* 11:30a: Set up for seminar and grab lunch<br />
* 12:00p: Lunchtime seminar, 213 ANB<br />
* 1:15p: Open<br />
* 2:00p: Changhong Zhao, 232 ANB<br />
* 2:45p: Yorie Nakahira, 239 ANB<br />
* 3:30p: Open<br />
* 4:15p: Open<br />
* 5:00p: Open<br />
* 5:45p: Done for the Day<br />
<br />
=== Seminar info ===<br />
<br />
Speaker: Sérgio Pequito<br><br />
Date & Time: Tuesday, March 31st (12pm)<br><br />
Location: 213 Annenberg<br><br />
Affiliation: University of Pennsylvania<br><br />
<br />
'''A Framework for Structural Input/Output and Control Configuration Selection of Large - Scale Systems'''<br />
<br />
The structure control system design consists mainly of two steps: input/output (I/O) selection and control configuration (CC) selection. The first one is devoted to the problem of computing how many actuators/sensors are needed and where should be placed in the plant to obtain some desired property. Control configuration is related to the decentralized control problem and is dedicated to the task of selecting which outputs (sensors) should be available for feedback and to which inputs (actuators) in order to achieve a predefined goal. The choice of inputs and outputs affects the performance, complexity and costs of the control system. Due to the combinatorial nature of the selection problem, an efficient and systematic method is required to complement the designer intuition, experience and physical insight.<br />
<br />
Motivated by the above, this presentation addresses the structure control system design taking explicitly into consideration the possible application to large - scale systems. We provide an efficient framework to solve the following major minimization problems: i) selection of the minimum number of manipulated/measured variables to achieve structural controllability/observability of the system, and ii) selection of the minimum number of measured and manipulated variables, and feedback interconnections between them such that the system has no structural fixed modes. Contrary to what would be expected, we showed that it is possible to obtain the global solution of the aforementioned minimization problems in polynomial complexity in the number of the state variables of the system. To this effect, we propose a methodology that is efficient (polynomial complexity) and unified in the sense that it solves simultaneously the I/O and the CC selection problems. This is done by exploiting the implications of the I/O selection in the solution to the CC problem.<br />
<br />
'''Bio'''<br />
<br />
Sérgio Pequito is a postdoctoral researcher at University of Pennsylvania. He obtained his PhD in Electrical and Computer Engineering from Carnegie Mellon University and Instituto Superior Técnico, through the CMU-Portugal program. Furthermore, he received his BSc and MSc in Applied Mathematics from the Instituto Superior Técnico. Pequito's research consists in understanding the global qualitative behavior of large scale systems from their structural or parametric descriptions and provide a rigorous framework for the design, analysis, optimization and control of large scale (real-world) systems. Pequito was awarded with the best student paper finalist in the Conference on Decision and Control 2009, the ECE Outstanding Teaching Assistant Award at Carnegie Mellon University, and the Carnegie Mellon Graduate Teaching Award (university-wide) honorable mention, both in 2012.</div>Yilinmohttps://www.cds.caltech.edu/~murray/wiki/index.php?title=Sergio_Pequito,_31_03_2015Sergio Pequito, 31 03 20152015-03-30T22:40:05Z<p>Yilinmo: /* Schedule */</p>
<hr />
<div>Sérgio Pequito, a Postdoctoral Researcher at Upenn working with Prof. George J. Pappas, will visit Caltech on 31 March 2015 and give a group seminar.<br />
<br />
=== Schedule ===<br />
<br />
Tuesday<br />
* 9:30a : Meeting with Richard, 109 Steele<br />
* 10:00a: Open<br />
* 10:45a: Enrique Mallada, 338 ANB<br />
* 11:30a: Set up for seminar and grab lunch<br />
* 12:00p: Lunchtime seminar, 213 ANB<br />
* 1:15p: Open<br />
* 2:00p: Changhong Zhao, 232 ANB<br />
* 2:45p: Yorie Nakahira, <br />
* 3:30p: Open<br />
* 4:15p: Open<br />
* 5:00p: Open<br />
* 5:45p: Done for the Day<br />
<br />
=== Seminar info ===<br />
<br />
Speaker: Sérgio Pequito<br><br />
Date & Time: Tuesday, March 31st (12pm)<br><br />
Location: 213 Annenberg<br><br />
Affiliation: University of Pennsylvania<br><br />
<br />
'''A Framework for Structural Input/Output and Control Configuration Selection of Large - Scale Systems'''<br />
<br />
The structure control system design consists mainly of two steps: input/output (I/O) selection and control configuration (CC) selection. The first one is devoted to the problem of computing how many actuators/sensors are needed and where should be placed in the plant to obtain some desired property. Control configuration is related to the decentralized control problem and is dedicated to the task of selecting which outputs (sensors) should be available for feedback and to which inputs (actuators) in order to achieve a predefined goal. The choice of inputs and outputs affects the performance, complexity and costs of the control system. Due to the combinatorial nature of the selection problem, an efficient and systematic method is required to complement the designer intuition, experience and physical insight.<br />
<br />
Motivated by the above, this presentation addresses the structure control system design taking explicitly into consideration the possible application to large - scale systems. We provide an efficient framework to solve the following major minimization problems: i) selection of the minimum number of manipulated/measured variables to achieve structural controllability/observability of the system, and ii) selection of the minimum number of measured and manipulated variables, and feedback interconnections between them such that the system has no structural fixed modes. Contrary to what would be expected, we showed that it is possible to obtain the global solution of the aforementioned minimization problems in polynomial complexity in the number of the state variables of the system. To this effect, we propose a methodology that is efficient (polynomial complexity) and unified in the sense that it solves simultaneously the I/O and the CC selection problems. This is done by exploiting the implications of the I/O selection in the solution to the CC problem.<br />
<br />
'''Bio'''<br />
<br />
Sérgio Pequito is a postdoctoral researcher at University of Pennsylvania. He obtained his PhD in Electrical and Computer Engineering from Carnegie Mellon University and Instituto Superior Técnico, through the CMU-Portugal program. Furthermore, he received his BSc and MSc in Applied Mathematics from the Instituto Superior Técnico. Pequito's research consists in understanding the global qualitative behavior of large scale systems from their structural or parametric descriptions and provide a rigorous framework for the design, analysis, optimization and control of large scale (real-world) systems. Pequito was awarded with the best student paper finalist in the Conference on Decision and Control 2009, the ECE Outstanding Teaching Assistant Award at Carnegie Mellon University, and the Carnegie Mellon Graduate Teaching Award (university-wide) honorable mention, both in 2012.</div>Yilinmohttps://www.cds.caltech.edu/~murray/wiki/index.php?title=Sergio_Pequito,_31_03_2015Sergio Pequito, 31 03 20152015-03-29T23:38:03Z<p>Yilinmo: </p>
<hr />
<div>Sérgio Pequito, a Postdoctoral Researcher at Upenn working with Prof. George J. Pappas, will visit Caltech on 31 March 2015 and give a group seminar.<br />
<br />
=== Schedule ===<br />
<br />
Tuesday<br />
* 9:30a : Meeting with Richard, 109 Steele<br />
* 10:00a: Open<br />
* 10:45a: Enrique Mallada, 338 ANB<br />
* 11:30a: Set up for seminar and grab lunch<br />
* 12:00p: Lunchtime seminar, 213 ANB<br />
* 1:15p: Open<br />
* 2:00p: Changhong Zhao, 232 ANB<br />
* 2:45p: Open<br />
* 3:30p: Open<br />
* 4:15p: Open<br />
* 5:00p: Open<br />
* 5:45p: Done for the Day<br />
<br />
=== Seminar info ===<br />
<br />
Speaker: Sérgio Pequito<br><br />
Date & Time: Tuesday, March 31st (12pm)<br><br />
Location: 213 Annenberg<br><br />
Affiliation: University of Pennsylvania<br><br />
<br />
'''A Framework for Structural Input/Output and Control Configuration Selection of Large - Scale Systems'''<br />
<br />
The structure control system design consists mainly of two steps: input/output (I/O) selection and control configuration (CC) selection. The first one is devoted to the problem of computing how many actuators/sensors are needed and where should be placed in the plant to obtain some desired property. Control configuration is related to the decentralized control problem and is dedicated to the task of selecting which outputs (sensors) should be available for feedback and to which inputs (actuators) in order to achieve a predefined goal. The choice of inputs and outputs affects the performance, complexity and costs of the control system. Due to the combinatorial nature of the selection problem, an efficient and systematic method is required to complement the designer intuition, experience and physical insight.<br />
<br />
Motivated by the above, this presentation addresses the structure control system design taking explicitly into consideration the possible application to large - scale systems. We provide an efficient framework to solve the following major minimization problems: i) selection of the minimum number of manipulated/measured variables to achieve structural controllability/observability of the system, and ii) selection of the minimum number of measured and manipulated variables, and feedback interconnections between them such that the system has no structural fixed modes. Contrary to what would be expected, we showed that it is possible to obtain the global solution of the aforementioned minimization problems in polynomial complexity in the number of the state variables of the system. To this effect, we propose a methodology that is efficient (polynomial complexity) and unified in the sense that it solves simultaneously the I/O and the CC selection problems. This is done by exploiting the implications of the I/O selection in the solution to the CC problem.<br />
<br />
'''Bio'''<br />
<br />
Sérgio Pequito is a postdoctoral researcher at University of Pennsylvania. He obtained his PhD in Electrical and Computer Engineering from Carnegie Mellon University and Instituto Superior Técnico, through the CMU-Portugal program. Furthermore, he received his BSc and MSc in Applied Mathematics from the Instituto Superior Técnico. Pequito's research consists in understanding the global qualitative behavior of large scale systems from their structural or parametric descriptions and provide a rigorous framework for the design, analysis, optimization and control of large scale (real-world) systems. Pequito was awarded with the best student paper finalist in the Conference on Decision and Control 2009, the ECE Outstanding Teaching Assistant Award at Carnegie Mellon University, and the Carnegie Mellon Graduate Teaching Award (university-wide) honorable mention, both in 2012.</div>Yilinmohttps://www.cds.caltech.edu/~murray/wiki/index.php?title=Sergio_Pequito,_31_03_2015Sergio Pequito, 31 03 20152015-03-27T17:29:35Z<p>Yilinmo: </p>
<hr />
<div>Sérgio Pequito, a Postdoctoral Researcher at Upenn working with Prof. George J. Pappas, will visit Caltech on 31 March 2015 and give a group seminar.<br />
<br />
=== Schedule ===<br />
<br />
Tuesday<br />
* 9:30a : Meeting with Richard, 109 Steele<br />
* 10:00a: Open<br />
* 10:45a: Enrique Mallada, 338 ANB<br />
* 11:30a: Set up for seminar and grab lunch<br />
* 12:00p: Lunchtime seminar, 213 ANB<br />
* 1:15p: Open<br />
* 2:00p: Open<br />
* 2:45p: Open<br />
* 3:30p: Open<br />
* 4:15p: Open<br />
* 5:00p: Open<br />
* 5:45p: Done for the Day<br />
<br />
=== Seminar info ===<br />
<br />
Speaker: Sérgio Pequito<br><br />
Date & Time: Tuesday, March 31st (12pm)<br><br />
Location: 213 Annenberg<br><br />
Affiliation: University of Pennsylvania<br><br />
<br />
'''A Framework for Structural Input/Output and Control Configuration Selection of Large - Scale Systems'''<br />
<br />
The structure control system design consists mainly of two steps: input/output (I/O) selection and control configuration (CC) selection. The first one is devoted to the problem of computing how many actuators/sensors are needed and where should be placed in the plant to obtain some desired property. Control configuration is related to the decentralized control problem and is dedicated to the task of selecting which outputs (sensors) should be available for feedback and to which inputs (actuators) in order to achieve a predefined goal. The choice of inputs and outputs affects the performance, complexity and costs of the control system. Due to the combinatorial nature of the selection problem, an efficient and systematic method is required to complement the designer intuition, experience and physical insight.<br />
<br />
Motivated by the above, this presentation addresses the structure control system design taking explicitly into consideration the possible application to large - scale systems. We provide an efficient framework to solve the following major minimization problems: i) selection of the minimum number of manipulated/measured variables to achieve structural controllability/observability of the system, and ii) selection of the minimum number of measured and manipulated variables, and feedback interconnections between them such that the system has no structural fixed modes. Contrary to what would be expected, we showed that it is possible to obtain the global solution of the aforementioned minimization problems in polynomial complexity in the number of the state variables of the system. To this effect, we propose a methodology that is efficient (polynomial complexity) and unified in the sense that it solves simultaneously the I/O and the CC selection problems. This is done by exploiting the implications of the I/O selection in the solution to the CC problem.<br />
<br />
'''Bio'''<br />
<br />
Sérgio Pequito is a postdoctoral researcher at University of Pennsylvania. He obtained his PhD in Electrical and Computer Engineering from Carnegie Mellon University and Instituto Superior Técnico, through the CMU-Portugal program. Furthermore, he received his BSc and MSc in Applied Mathematics from the Instituto Superior Técnico. Pequito's research consists in understanding the global qualitative behavior of large scale systems from their structural or parametric descriptions and provide a rigorous framework for the design, analysis, optimization and control of large scale (real-world) systems. Pequito was awarded with the best student paper finalist in the Conference on Decision and Control 2009, the ECE Outstanding Teaching Assistant Award at Carnegie Mellon University, and the Carnegie Mellon Graduate Teaching Award (university-wide) honorable mention, both in 2012.</div>Yilinmohttps://www.cds.caltech.edu/~murray/wiki/index.php?title=Sergio_Pequito,_31_03_2015Sergio Pequito, 31 03 20152015-03-26T21:09:29Z<p>Yilinmo: </p>
<hr />
<div>Sérgio Pequito, a Postdoctoral Researcher at Upenn working with Prof. George J. Pappas, will visit Caltech on 31 March 2015 and give a group seminar.<br />
<br />
=== Schedule ===<br />
<br />
Tuesday<br />
* 9:30a : Meeting with Richard, 109 Steele<br />
* 10:00a: Open<br />
* 10:45a: Open<br />
* 11:30a: Set up for seminar and grab lunch<br />
* 12:00p: Lunchtime seminar, 213 ANB<br />
* 1:15p: Open<br />
* 2:00p: Open<br />
* 2:45p: Open<br />
* 3:30p: Open<br />
* 4:15p: Open<br />
* 5:00p: Open<br />
* 5:45p: Done for the Day<br />
<br />
=== Seminar info ===<br />
<br />
Speaker: Sérgio Pequito<br><br />
Date & Time: Tuesday, March 31st (12pm)<br><br />
Location: 213 Annenberg<br><br />
Affiliation: University of Pennsylvania<br><br />
<br />
'''A Framework for Structural Input/Output and Control Configuration Selection of Large - Scale Systems'''<br />
<br />
The structure control system design consists mainly of two steps: input/output (I/O) selection and control configuration (CC) selection. The first one is devoted to the problem of computing how many actuators/sensors are needed and where should be placed in the plant to obtain some desired property. Control configuration is related to the decentralized control problem and is dedicated to the task of selecting which outputs (sensors) should be available for feedback and to which inputs (actuators) in order to achieve a predefined goal. The choice of inputs and outputs affects the performance, complexity and costs of the control system. Due to the combinatorial nature of the selection problem, an efficient and systematic method is required to complement the designer intuition, experience and physical insight.<br />
<br />
Motivated by the above, this presentation addresses the structure control system design taking explicitly into consideration the possible application to large - scale systems. We provide an efficient framework to solve the following major minimization problems: i) selection of the minimum number of manipulated/measured variables to achieve structural controllability/observability of the system, and ii) selection of the minimum number of measured and manipulated variables, and feedback interconnections between them such that the system has no structural fixed modes. Contrary to what would be expected, we showed that it is possible to obtain the global solution of the aforementioned minimization problems in polynomial complexity in the number of the state variables of the system. To this effect, we propose a methodology that is efficient (polynomial complexity) and unified in the sense that it solves simultaneously the I/O and the CC selection problems. This is done by exploiting the implications of the I/O selection in the solution to the CC problem.<br />
<br />
'''Bio'''<br />
<br />
Sérgio Pequito is a postdoctoral researcher at University of Pennsylvania. He obtained his PhD in Electrical and Computer Engineering from Carnegie Mellon University and Instituto Superior Técnico, through the CMU-Portugal program. Furthermore, he received his BSc and MSc in Applied Mathematics from the Instituto Superior Técnico. Pequito's research consists in understanding the global qualitative behavior of large scale systems from their structural or parametric descriptions and provide a rigorous framework for the design, analysis, optimization and control of large scale (real-world) systems. Pequito was awarded with the best student paper finalist in the Conference on Decision and Control 2009, the ECE Outstanding Teaching Assistant Award at Carnegie Mellon University, and the Carnegie Mellon Graduate Teaching Award (university-wide) honorable mention, both in 2012.</div>Yilinmohttps://www.cds.caltech.edu/~murray/wiki/index.php?title=Sergio_Pequito,_31_03_2015Sergio Pequito, 31 03 20152015-03-26T20:56:48Z<p>Yilinmo: /* Schedule */</p>
<hr />
<div>Sérgio Pequito, a Postdoctoral Researcher at Upenn working with Prof. George J. Pappas, will visit Caltech on 31 March 2015 and give a group seminar.<br />
<br />
=== Schedule ===<br />
<br />
Tuesday<br />
* 10:00a: Open<br />
* 10:45a: Open<br />
* 11:30a: Set up for seminar and grab lunch<br />
* 12:00p: Lunchtime seminar, 213 ANB<br />
* 1:15p: Open<br />
* 2:00p: Open<br />
* 2:45p: Open<br />
* 3:30p: Open<br />
* 4:15p: Open<br />
* 5:00p: Done for the day<br />
<br />
=== Seminar info ===<br />
<br />
Speaker: Sérgio Pequito<br><br />
Date & Time: Tuesday, March 31st (12pm)<br><br />
Location: 213 Annenberg<br><br />
Affiliation: University of Pennsylvania<br><br />
<br />
'''A Framework for Structural Input/Output and Control Configuration Selection of Large - Scale Systems'''<br />
<br />
The structure control system design consists mainly of two steps: input/output (I/O) selection and control configuration (CC) selection. The first one is devoted to the problem of computing how many actuators/sensors are needed and where should be placed in the plant to obtain some desired property. Control configuration is related to the decentralized control problem and is dedicated to the task of selecting which outputs (sensors) should be available for feedback and to which inputs (actuators) in order to achieve a predefined goal. The choice of inputs and outputs affects the performance, complexity and costs of the control system. Due to the combinatorial nature of the selection problem, an efficient and systematic method is required to complement the designer intuition, experience and physical insight.<br />
<br />
Motivated by the above, this presentation addresses the structure control system design taking explicitly into consideration the possible application to large - scale systems. We provide an efficient framework to solve the following major minimization problems: i) selection of the minimum number of manipulated/measured variables to achieve structural controllability/observability of the system, and ii) selection of the minimum number of measured and manipulated variables, and feedback interconnections between them such that the system has no structural fixed modes. Contrary to what would be expected, we showed that it is possible to obtain the global solution of the aforementioned minimization problems in polynomial complexity in the number of the state variables of the system. To this effect, we propose a methodology that is efficient (polynomial complexity) and unified in the sense that it solves simultaneously the I/O and the CC selection problems. This is done by exploiting the implications of the I/O selection in the solution to the CC problem.<br />
<br />
'''Bio'''<br />
<br />
Sérgio Pequito is a postdoctoral researcher at University of Pennsylvania. He obtained his PhD in Electrical and Computer Engineering from Carnegie Mellon University and Instituto Superior Técnico, through the CMU-Portugal program. Furthermore, he received his BSc and MSc in Applied Mathematics from the Instituto Superior Técnico. Pequito's research consists in understanding the global qualitative behavior of large scale systems from their structural or parametric descriptions and provide a rigorous framework for the design, analysis, optimization and control of large scale (real-world) systems. Pequito was awarded with the best student paper finalist in the Conference on Decision and Control 2009, the ECE Outstanding Teaching Assistant Award at Carnegie Mellon University, and the Carnegie Mellon Graduate Teaching Award (university-wide) honorable mention, both in 2012.</div>Yilinmohttps://www.cds.caltech.edu/~murray/wiki/index.php?title=Sergio_Pequito,_31_03_2015Sergio Pequito, 31 03 20152015-03-26T20:56:35Z<p>Yilinmo: /* Seminar info */</p>
<hr />
<div>Sérgio Pequito, a Postdoctoral Researcher at Upenn working with Prof. George J. Pappas, will visit Caltech on 31 March 2015 and give a group seminar.<br />
<br />
=== Schedule ===<br />
<br />
Tuesday<br />
* 10:00a: Open<br />
* 10:45a: Open<br />
* 11:30a: Set up for seminar and grab lunch<br />
* 12:00p: Lunchtime seminar, 107 ANB<br />
* 1:15p: Open<br />
* 2:00p: Open<br />
* 2:45p: Open<br />
* 3:30p: Open<br />
* 4:15p: Open<br />
* 5:00p: Done for the day<br />
<br />
=== Seminar info ===<br />
<br />
Speaker: Sérgio Pequito<br><br />
Date & Time: Tuesday, March 31st (12pm)<br><br />
Location: 213 Annenberg<br><br />
Affiliation: University of Pennsylvania<br><br />
<br />
'''A Framework for Structural Input/Output and Control Configuration Selection of Large - Scale Systems'''<br />
<br />
The structure control system design consists mainly of two steps: input/output (I/O) selection and control configuration (CC) selection. The first one is devoted to the problem of computing how many actuators/sensors are needed and where should be placed in the plant to obtain some desired property. Control configuration is related to the decentralized control problem and is dedicated to the task of selecting which outputs (sensors) should be available for feedback and to which inputs (actuators) in order to achieve a predefined goal. The choice of inputs and outputs affects the performance, complexity and costs of the control system. Due to the combinatorial nature of the selection problem, an efficient and systematic method is required to complement the designer intuition, experience and physical insight.<br />
<br />
Motivated by the above, this presentation addresses the structure control system design taking explicitly into consideration the possible application to large - scale systems. We provide an efficient framework to solve the following major minimization problems: i) selection of the minimum number of manipulated/measured variables to achieve structural controllability/observability of the system, and ii) selection of the minimum number of measured and manipulated variables, and feedback interconnections between them such that the system has no structural fixed modes. Contrary to what would be expected, we showed that it is possible to obtain the global solution of the aforementioned minimization problems in polynomial complexity in the number of the state variables of the system. To this effect, we propose a methodology that is efficient (polynomial complexity) and unified in the sense that it solves simultaneously the I/O and the CC selection problems. This is done by exploiting the implications of the I/O selection in the solution to the CC problem.<br />
<br />
'''Bio'''<br />
<br />
Sérgio Pequito is a postdoctoral researcher at University of Pennsylvania. He obtained his PhD in Electrical and Computer Engineering from Carnegie Mellon University and Instituto Superior Técnico, through the CMU-Portugal program. Furthermore, he received his BSc and MSc in Applied Mathematics from the Instituto Superior Técnico. Pequito's research consists in understanding the global qualitative behavior of large scale systems from their structural or parametric descriptions and provide a rigorous framework for the design, analysis, optimization and control of large scale (real-world) systems. Pequito was awarded with the best student paper finalist in the Conference on Decision and Control 2009, the ECE Outstanding Teaching Assistant Award at Carnegie Mellon University, and the Carnegie Mellon Graduate Teaching Award (university-wide) honorable mention, both in 2012.</div>Yilinmohttps://www.cds.caltech.edu/~murray/wiki/index.php?title=Sergio_Pequito,_31_03_2015Sergio Pequito, 31 03 20152015-03-26T19:38:58Z<p>Yilinmo: Created page with "Sérgio Pequito, a Postdoctoral Researcher at Upenn working with Prof. George J. Pappas, will visit Caltech on 31 March 2015 and give a group seminar. === Schedule === Tuesd..."</p>
<hr />
<div>Sérgio Pequito, a Postdoctoral Researcher at Upenn working with Prof. George J. Pappas, will visit Caltech on 31 March 2015 and give a group seminar.<br />
<br />
=== Schedule ===<br />
<br />
Tuesday<br />
* 10:00a: Open<br />
* 10:45a: Open<br />
* 11:30a: Set up for seminar and grab lunch<br />
* 12:00p: Lunchtime seminar, 107 ANB<br />
* 1:15p: Open<br />
* 2:00p: Open<br />
* 2:45p: Open<br />
* 3:30p: Open<br />
* 4:15p: Open<br />
* 5:00p: Done for the day<br />
<br />
=== Seminar info ===<br />
<br />
Speaker: Sérgio Pequito<br><br />
Date & Time: Tuesday, March 31st (??)<br><br />
Location: <br><br />
Affiliation: University of Pennsylvania<br><br />
<br />
'''A Framework for Structural Input/Output and Control Configuration Selection of Large - Scale Systems'''<br />
<br />
The structure control system design consists mainly of two steps: input/output (I/O) selection and control configuration (CC) selection. The first one is devoted to the problem of computing how many actuators/sensors are needed and where should be placed in the plant to obtain some desired property. Control configuration is related to the decentralized control problem and is dedicated to the task of selecting which outputs (sensors) should be available for feedback and to which inputs (actuators) in order to achieve a predefined goal. The choice of inputs and outputs affects the performance, complexity and costs of the control system. Due to the combinatorial nature of the selection problem, an efficient and systematic method is required to complement the designer intuition, experience and physical insight.<br />
<br />
Motivated by the above, this presentation addresses the structure control system design taking explicitly into consideration the possible application to large - scale systems. We provide an efficient framework to solve the following major minimization problems: i) selection of the minimum number of manipulated/measured variables to achieve structural controllability/observability of the system, and ii) selection of the minimum number of measured and manipulated variables, and feedback interconnections between them such that the system has no structural fixed modes. Contrary to what would be expected, we showed that it is possible to obtain the global solution of the aforementioned minimization problems in polynomial complexity in the number of the state variables of the system. To this effect, we propose a methodology that is efficient (polynomial complexity) and unified in the sense that it solves simultaneously the I/O and the CC selection problems. This is done by exploiting the implications of the I/O selection in the solution to the CC problem.<br />
<br />
'''Bio'''<br />
<br />
Sérgio Pequito is a postdoctoral researcher at University of Pennsylvania. He obtained his PhD in Electrical and Computer Engineering from Carnegie Mellon University and Instituto Superior Técnico, through the CMU-Portugal program. Furthermore, he received his BSc and MSc in Applied Mathematics from the Instituto Superior Técnico. Pequito's research consists in understanding the global qualitative behavior of large scale systems from their structural or parametric descriptions and provide a rigorous framework for the design, analysis, optimization and control of large scale (real-world) systems. Pequito was awarded with the best student paper finalist in the Conference on Decision and Control 2009, the ECE Outstanding Teaching Assistant Award at Carnegie Mellon University, and the Carnegie Mellon Graduate Teaching Award (university-wide) honorable mention, both in 2012.</div>Yilinmohttps://www.cds.caltech.edu/~murray/wiki/index.php?title=Jin_Ge,_Dec_2014Jin Ge, Dec 20142014-12-09T06:13:35Z<p>Yilinmo: /* Schedule */</p>
<hr />
<div>Jin Ge is a graduate student working with Gabor Orosz who will be visiting on 11 Dec (Thu). <br />
<br />
=== Schedule ===<br />
* 9:45 am - meet Richard in 109 Steele Lab<br />
* 10 - 12 pm - Networked Control Systems group meeting<br />
* 12-1:30 - group meeting (seminar)<br />
* 1:30 - 2:15: Yilin Mo (Ann 310)<br />
* 2:15 - 3:00: Open<br />
* 3:00 - 3:45: Open<br />
* 3:45 - 4:30: Open<br />
<br />
=== Talk info ===<br />
Title: Linear Quadratic Regulation (LQR) for Time-Varying Systems with Delay<br><br />
Thu, 12 pm -- 213 Annenberg<br />
<br />
In this talk, linear quadratic regulation (LQR) for time-varying systems with delay is used to optimize the control gains for connected cruise control (CCC). We assume that the CCC vehicle receives kinematic information through wireless vehicle-to-vehicle (V2V) communication from several vehicles ahead. An optimized feedback law is obtained by minimizing a cost function defined by distance and velocity errors and the acceleration of the CCC vehicle on an infinite horizon. Communication delays, driver reaction times, and heterogeneity among vehicles are taken into account. We show that the feedback gains can be obtained recursively as signals from vehicles farther ahead become available, and that the optimal gains decay with the number of cars between the source of the signal and the CCC vehicle. To ensure smooth traffic flow the head-to-tail string stability is investigated and the robustness against connectivity loss and delay variations is tested. The analytical results are verified by numerical simulations of connected vehicle systems</div>Yilinmohttps://www.cds.caltech.edu/~murray/wiki/index.php?title=File:Handout.pdfFile:Handout.pdf2014-11-20T19:44:54Z<p>Yilinmo: handout on intrusion detection for control systems for CDS 270 lecture 16</p>
<hr />
<div>handout on intrusion detection for control systems for CDS 270 lecture 16</div>Yilinmohttps://www.cds.caltech.edu/~murray/wiki/index.php?title=File:Cds27015.pdfFile:Cds27015.pdf2014-11-18T19:49:19Z<p>Yilinmo: handout for linear structured system of lecture 15 of cds 270</p>
<hr />
<div>handout for linear structured system of lecture 15 of cds 270</div>Yilinmohttps://www.cds.caltech.edu/~murray/wiki/index.php?title=File:Cds27014.pdfFile:Cds27014.pdf2014-11-13T20:00:29Z<p>Yilinmo: Yilinmo uploaded a new version of &quot;File:Cds27014.pdf&quot;</p>
<hr />
<div>handout on non-negative matrices and Perron Frobenius Theorem for CDS 270 Lecture 14.</div>Yilinmohttps://www.cds.caltech.edu/~murray/wiki/index.php?title=File:Cds27014.pdfFile:Cds27014.pdf2014-11-13T18:37:59Z<p>Yilinmo: handout on non-negative matrices and Perron Frobenius Theorem for CDS 270 Lecture 14.</p>
<hr />
<div>handout on non-negative matrices and Perron Frobenius Theorem for CDS 270 Lecture 14.</div>Yilinmohttps://www.cds.caltech.edu/~murray/wiki/index.php?title=File:Cds27013.pdfFile:Cds27013.pdf2014-11-11T19:25:42Z<p>Yilinmo: handout on distributed estimation for cds 270 lecture 13</p>
<hr />
<div>handout on distributed estimation for cds 270 lecture 13</div>Yilinmohttps://www.cds.caltech.edu/~murray/wiki/index.php?title=File:Cds27012.pdfFile:Cds27012.pdf2014-11-06T09:08:52Z<p>Yilinmo: handout on distributed hypothesis testing via running consensus</p>
<hr />
<div>handout on distributed hypothesis testing via running consensus</div>Yilinmohttps://www.cds.caltech.edu/~murray/wiki/index.php?title=File:Cds27010.pdfFile:Cds27010.pdf2014-10-30T05:38:08Z<p>Yilinmo: handout on gossip algorithm for cds270 lecture 10</p>
<hr />
<div>handout on gossip algorithm for cds270 lecture 10</div>Yilinmohttps://www.cds.caltech.edu/~murray/wiki/index.php?title=File:Cds2709.pdfFile:Cds2709.pdf2014-10-27T16:02:13Z<p>Yilinmo: handouts on finite time consensus and consensus with channel noise for lecture 9 of cds 270</p>
<hr />
<div>handouts on finite time consensus and consensus with channel noise for lecture 9 of cds 270</div>Yilinmohttps://www.cds.caltech.edu/~murray/wiki/index.php?title=File:Cds2708.pdfFile:Cds2708.pdf2014-10-23T19:16:19Z<p>Yilinmo: </p>
<hr />
<div></div>Yilinmohttps://www.cds.caltech.edu/~murray/wiki/index.php?title=File:Cds2707.pdfFile:Cds2707.pdf2014-10-21T07:43:32Z<p>Yilinmo: handout on event based estimation for cds 270, lecture 7</p>
<hr />
<div>handout on event based estimation for cds 270, lecture 7</div>Yilinmohttps://www.cds.caltech.edu/~murray/wiki/index.php?title=File:Cds2706.pdfFile:Cds2706.pdf2014-10-16T08:07:08Z<p>Yilinmo: handout on sensor selection for lecture 6, cds270</p>
<hr />
<div>handout on sensor selection for lecture 6, cds270</div>Yilinmohttps://www.cds.caltech.edu/~murray/wiki/index.php?title=File:Cds2705.pdfFile:Cds2705.pdf2014-10-14T21:48:21Z<p>Yilinmo: Yilinmo uploaded a new version of &quot;File:Cds2705.pdf&quot;</p>
<hr />
<div>handout on control over lossy network for cds270</div>Yilinmohttps://www.cds.caltech.edu/~murray/wiki/index.php?title=File:Cds2705.pdfFile:Cds2705.pdf2014-10-14T21:46:51Z<p>Yilinmo: Yilinmo uploaded a new version of &quot;File:Cds2705.pdf&quot;: correct several typos</p>
<hr />
<div>handout on control over lossy network for cds270</div>Yilinmohttps://www.cds.caltech.edu/~murray/wiki/index.php?title=File:Cds2705.pdfFile:Cds2705.pdf2014-10-14T09:48:59Z<p>Yilinmo: handout on control over lossy network for cds270</p>
<hr />
<div>handout on control over lossy network for cds270</div>Yilinmohttps://www.cds.caltech.edu/~murray/wiki/index.php?title=File:Cds2703.pdfFile:Cds2703.pdf2014-10-13T21:57:02Z<p>Yilinmo: handout for properties of Riccati and Lyapunov functions for cds270</p>
<hr />
<div>handout for properties of Riccati and Lyapunov functions for cds270</div>Yilinmohttps://www.cds.caltech.edu/~murray/wiki/index.php?title=File:Cds270lecture4.pdfFile:Cds270lecture4.pdf2014-10-13T21:55:11Z<p>Yilinmo: handout on critical value of KF with intermittent observations for cds270</p>
<hr />
<div>handout on critical value of KF with intermittent observations for cds270</div>Yilinmohttps://www.cds.caltech.edu/~murray/wiki/index.php?title=File:Cds270lecture2.pdfFile:Cds270lecture2.pdf2014-10-03T23:48:24Z<p>Yilinmo: handout on Kalman filter for the lecture 2 of CDS 270</p>
<hr />
<div>handout on Kalman filter for the lecture 2 of CDS 270</div>Yilinmohttps://www.cds.caltech.edu/~murray/wiki/index.php?title=File:Cds270lecture1.pdfFile:Cds270lecture1.pdf2014-10-02T00:42:33Z<p>Yilinmo: the slides for the first lecture of cds 270: networked control systems in fall 2014.</p>
<hr />
<div>the slides for the first lecture of cds 270: networked control systems in fall 2014.</div>Yilinmohttps://www.cds.caltech.edu/~murray/wiki/index.php?title=Roy_Fox,_Oct_2014Roy Fox, Oct 20142014-09-29T16:42:41Z<p>Yilinmo: /* Schedule */</p>
<hr />
<div>Roy Fox is a 4th year PhD student in the Computer Science working with Prof. Naftali Tishby on Information Theoretic methods for Reinforcement Learning. He will be visiting Caltech on 2 Oct (Thu). If you would like to meet with him, please sign up for a slot below (use your IMSS credentials to log in).<br />
<br />
=== Schedule ===<br />
<br />
* 11:30 am - Richard Murray<br />
* 12:00 pm - Group meeting talk, 106 ANB<br />
* 1:30 pm - Open<br />
* 2:15 pm - Open<br />
* 3:00 pm - Yilin Mo<br />
* 3:45 pm - Open<br />
* 4:30 pm - Depart<br />
<br />
=== Abstract ===<br />
<br />
Optimal Selective Attention and Action in Reactive Agents <br><br />
Roy Fox, Hebrew University<br />
<br />
2 Oct (Thu), 12 pm <br><br />
106 Annenberg<br />
<br />
Intelligent agents, interacting with their environment, operate under constraints on what they can observe and how they can act. Unbounded agents can use standard Reinforcement Learning to optimize their inference and control under purely external constraints. Bounded agents, on the other hand, are subject to internal constraints as well. This only allows them to partially notice their observations, and to partially intend their actions, requiring rational selection of attention and action.<br />
<br />
In this talk we will see how to find the optimal information-constrained policy in reactive (memoryless) agents. We will discuss a number of reasons why internal constraints are often best modeled as bounds on information-theoretic quantities, and why we can focus on reactive agents with hardly any loss of generality. We will link the solution of the constrained problem to that of soft clustering, and present some of its nice properties, such as principled dimensionality reduction.</div>Yilinmohttps://www.cds.caltech.edu/~murray/wiki/index.php?title=Tomoaki_Hashimoto,_Aug_2014Tomoaki Hashimoto, Aug 20142014-07-24T22:07:48Z<p>Yilinmo: </p>
<hr />
<div>* Visitor: Prof. Tomoaki Hashimoto (Osaka University, Assistant Professor)<br />
* Date: August 1st (Fri)<br />
=== Schedule ===<br />
* 9 am - Yutaka (218 ANB; ex 3552)<br />
* 10 am - <br />
* 11 am -<br />
* 11:50 am - seminar set up<br />
* 12-1:15 pm - seminar (213 ANB)<br />
* 1:15 pm - Richard (until 2 pm)<br />
* 2 pm - <br />
* 3 pm - Yilin Mo (310 ANN; ex 3503)<br />
* 4 pm -<br />
* 5 pm - Done<br />
<br />
=== Seminar ===<br />
Abstract: Model predictive control (MPC), also known as receding horizon control, is a type of optimal feedback control where control performance<br />
over a finite future is optimized with a performance index that has a moving initial time and a terminal time. This talk provides two topics about MPC. <br />
One is a design method of MPC for thermal fluid systems governed by nonlinear partial differential equations [1]. The other one is probabilistic constrained<br />
MPC for linear discrete-time stochastic systems. Both topics are related to the recent development of MPC. In particular, we would like to review the<br />
background and key idea of these studies [1, 2] rather than the technical details.<br />
<br />
References: <br />
<br />
[1] Tomoaki HASHIMOTO, Yusuke YOSHIOKA and Toshiyuki OHTSUKA: Receding Horizon Control with Numerical Solution for Nonlinear <br />
Parabolic Partial Differential Equations, IEEE Transactions on Automatic Control, Vol. 58, pp.725-730, 2013.<br />
<br />
[2] Tomoaki HASHIMOTO: Probabilistic Constrained Model Predictive Control for Linear Discrete-time Systems with Additive Stochastic Disturbances,<br />
Proceedings of the 52nd IEEE Conference on Decision and Control, pp.6434-6439, 2013. <br />
<br />
=== Bio ===<br />
Dr. Hashimoto received the B.Eng., M.Eng., and D.Eng. degrees from the Tokyo Metropolitan Institute of Technology, Hino, Japan, in 2003, 2004, and 2007, respectively, all in aerospace engineering. He was a Research Assistant at the RIKEN Brain Science Institute, Wako, Japan, from 2007 to 2008, and an Assistant Professor at the Shinshu University, Nagano, Japan, from 2008 to 2009. Since 2009, he has been an Assistant Professor at Osaka University, Toyonaka, Japan. His recent research interests are in the area of model predictive control and its application.</div>Yilinmohttps://www.cds.caltech.edu/~murray/wiki/index.php?title=Art_Krener,_Mar_2014Art Krener, Mar 20142014-02-26T17:25:45Z<p>Yilinmo: </p>
<hr />
<div>Art Krener will be visiting Caltech on 3 Mar 2014 (Mon). IF you would like to meet with him, sign up below.<br />
<br />
=== Schedule ===<br />
* 10:30 - Richard Murray, 109 Steele Lab<br />
* 11:00 - Seminar, 121 Annenberg<br />
* 12:00 - Lunch with Richard, John?, Doug?<br />
* 1:30 - Matanya Horowitz, 335 Annenberg<br />
* 2:15 - Eric Wolff, 331 Annenberg<br />
* 3:00 - Yilin Mo, 310 Annenberg<br />
* 3:45 - Open<br />
* 4:30 - Done for the day<br />
<br />
=== Abstract ===<br />
<br />
Computational Issues in Nonlinear Control<br />
<br />
Arthur J. Krener, Naval Postgraduate School<br><br />
3 March 2014 - 11:00am PST, 121 Annenberg<br />
<br />
Over the past several decades there has been tremendous progress in the development of nonlinear systems theory but implementation of these ideas have lagged behind because of the lack of effective computational tools. Frequently the nonlinear theory requires the solution of partial differential equations in continuous time and functional equations in discrete time. Algorithms for these have been developed but further work is needed to make them broadly and easily accessible. We believe that computational nonlinear control is in a similar stage of development that computational linear control was in around early 1980s. Then there was a well developed theory of linear control but computational tools lagged behind. Soon after comprehensive tools such as MATLAB and Matrix X were developed and put to great use in implementing the linear theory. Advancements in numerical methods together with the exponential increase in computational power has made it possible to solve complex nonlinear problems, many of which are closely related to control systems applications. Developing computational algorithms and software tools for such control systems are not only promising, but also necessary.<br />
<br />
The three topics that we will focus on are the following.<br />
# Numerical solution of Hamillton-Jacobi-Bellman and Dynamic Programming equations<br />
# Numerical calculation of optimal trajectories<br />
# Numerical calculation of invariant manifolds</div>Yilinmohttps://www.cds.caltech.edu/~murray/wiki/index.php?title=Dennis_Bernstein,_Jan_2014Dennis Bernstein, Jan 20142014-01-29T23:49:33Z<p>Yilinmo: /* Schedule */</p>
<hr />
<div>Dennis Berstein and James Forbes from U. Michigan will be visiting Caltech on 29 January 2014. If you would like to meet with Dennis and Jim during their visit, please sign up below.<br />
<br />
=== Schedule ===<br />
* 12:30 - Lunch and meeting with Richard<br />
* 2:00 - Seminar, 121 Annenberg<br />
* 3:00 - CDS tea<br />
* 3:30 - Doug MacMartin <br />
* 4:00 - Yilin Mo, 310 Annenberg<br />
* 4:30 - Matanya Horowitz, 335 Annenberg<br />
* 5:00 - Eric Wolff, 331 Annenberg<br />
* 5:30 - Done for the day<br />
<br />
=== Abstract ===<br />
<center><br />
How Much Modeling Information Is Really Needed for Feedback Control?<br />
<br />
Dennis Bernstein<br><br />
University of Michigan<br />
</center><br />
<br />
Modeling for control is often expensive and time-consuming—not to mention futile, especially when a plant changes unpredictably. Our research is therefore aimed at the following fundamental question: What is the minimal modeling information (order, parameters, nonlinearities, noise spectra, etc.) that must be known—and how *well* must it be known—so that a controller can reliably meet performance specifications? <br />
The approach we are developing is based on retrospective cost adaptive control (RCAC), which uses retrospective optimization for online learning. RCAC is easy to implement, and requires extremely limited modeling information. In this talk I will explain the rationale for RCAC, its applicability to various types of plants (stable/unstable, minimum-phase/NMP, SISO/MIMO, linear/nonlinear), the modeling information it can operate with and (especially) without, and the status of its theoretical foundation.<br />
For flight control, we will apply RCAC to the extreme case of totally unknown control-surface faults, such as a stuck rudder or severe rate saturation. Additional examples are taken from missile control, noise and vibration control, and spacecraft attitude control with nonlinear actuation such as CMGs.</div>Yilinmohttps://www.cds.caltech.edu/~murray/wiki/index.php?title=Dennis_Bernstein,_Jan_2014Dennis Bernstein, Jan 20142014-01-28T00:09:11Z<p>Yilinmo: </p>
<hr />
<div>Dennis Berstein and James Forbes from U. Michigan will be visiting Caltech on 29 January 2014. If you would like to meet with Dennis and Jim during their visit, please sign up below.<br />
<br />
=== Schedule ===<br />
* 12:30 - Lunch and meeting with Richard<br />
* 2:00 - Seminar, 121 Annenberg<br />
* 3:00 - CDS tea<br />
* 3:30 - Doug MacMartin <br />
* 4:00 - Yilin Mo<br />
* 4:30 - Matanya Horowitz<br />
* 5:00 - Open<br />
* 5:30 - Done for the day<br />
<br />
=== Abstract ===<br />
<center><br />
How Much Modeling Information Is Really Needed for Feedback Control?<br />
<br />
Dennis Bernstein<br><br />
University of Michigan<br />
</center><br />
<br />
Modeling for control is often expensive and time-consuming—not to mention futile, especially when a plant changes unpredictably. Our research is therefore aimed at the following fundamental question: What is the minimal modeling information (order, parameters, nonlinearities, noise spectra, etc.) that must be known—and how *well* must it be known—so that a controller can reliably meet performance specifications? <br />
The approach we are developing is based on retrospective cost adaptive control (RCAC), which uses retrospective optimization for online learning. RCAC is easy to implement, and requires extremely limited modeling information. In this talk I will explain the rationale for RCAC, its applicability to various types of plants (stable/unstable, minimum-phase/NMP, SISO/MIMO, linear/nonlinear), the modeling information it can operate with and (especially) without, and the status of its theoretical foundation.<br />
For flight control, we will apply RCAC to the extreme case of totally unknown control-surface faults, such as a stuck rudder or severe rate saturation. Additional examples are taken from missile control, noise and vibration control, and spacecraft attitude control with nonlinear actuation such as CMGs.</div>Yilinmohttps://www.cds.caltech.edu/~murray/wiki/index.php?title=SURF_discussions,_Jan_2014SURF discussions, Jan 20142014-01-24T00:19:00Z<p>Yilinmo: /* 28 Jan (Tue) */</p>
<hr />
<div>Slots for talking with applicants and co-mentors about SURF projects. Please sign up for one of the slots below. All times are PST.<br />
<br />
{| width=100% border=1<br />
|- valign=top<br />
|<br />
==== 27 Jan (Mon) ====<br />
* 9:00: Open<br />
<br />
* 11:00: Open<br />
* 11:30: Juan and Ioannis<br />
|<br />
<br />
==== 28 Jan (Tue) ====<br />
* 13:00: Robert and Yilin<br />
* 13:30: Open<br />
* 14:00: Open<br />
|<br />
<br />
==== 29 Jan (Wed) ====<br />
* 9:30: Open<br />
<br />
* 12:00: Linnea Persson and Scott Livingston<br />
<br />
* 17:30: Open<br />
|}<br />
<br />
The agenda for the phone call is (roughly):<br />
<br />
# Student: Description of the basic idea behind the project (based on students's understanding)<br />
# All: Discussion about approaches, things to read, variations to consider, etc<br />
# Mentor/co-mentor: Discussion of the format of the proposal<br />
# Student: Questions and discussion about the process</div>Yilinmohttps://www.cds.caltech.edu/~murray/wiki/index.php?title=September_2013_MeetingsSeptember 2013 Meetings2013-08-27T18:33:45Z<p>Yilinmo: /* Thu, 5 Sep */</p>
<hr />
<div>The list below has times that I am available to meet between 3 and 13 September. Please pick a time that works and fill in your name. If none of the times work, send me e-mail (or find someone else who has a slot that does work and figure out how much of a bribe is required to get them to switch). __NOTOC__<br />
<br />
{| border=1 width=100%<br />
|- valign=top<br />
| width=20% |<br />
2 Sep - Labor Day<br />
| width=20% |<br />
==== Tue, 3 Sep ====<br />
{{agenda begin}}<br />
{{agenda item|2:00p|Emzo}}<br />
{{agenda item|3:00p|Joe Levine}}<br />
{{agenda item|&nbsp;|&nbsp;}}<br />
{{agenda item|4:30|Enoch}}<br />
{{agenda item|5:30|Zach}}<br />
{{agenda end}}<br />
| width=20% |<br />
<br />
==== Wed, 4 Sep ====<br />
{{agenda begin}}<br />
{{agenda item|&nbsp;|&nbsp;}}<br />
{{agenda item|&nbsp;|&nbsp;}}<br />
{{agenda item|&nbsp;|&nbsp;}}<br />
{{agenda item|4:30|Joe}}<br />
{{agenda item|5:30|Jongmin}}<br />
{{agenda end}}<br />
| width=20% |<br />
<br />
==== Thu, 5 Sep ====<br />
{{agenda begin}}<br />
{{agenda item|2:00p|Yilin}}<br />
{{agenda item|3:00p|Open}}<br />
{{agenda item|&nbsp;|&nbsp;}}<br />
{{agenda item|4:30|Open}}<br />
{{agenda item|5:30|Ioannis}}<br />
{{agenda end}}<br />
| width=20% |<br />
6 Sep - Richard out of town<br />
|- valign=top<br />
| colspan=2 width=40% |<br />
<br />
==== Mon, 9 Sep / Tue, 10 Sep ====<br />
{| cellspacing=0 cellpadding=0<br />
|- valign=top<br />
| width=50% |<br />
{{agenda begin}}<br />
{{agenda item|2:00p|dsg}}<br />
{{agenda item|3:00p|Scott Livingston}}<br />
{{agenda item|&nbsp;|&nbsp;}}<br />
{{agenda item|4:30|Ivan Papusha}}<br />
{{agenda item|5:30|Zoltan}}<br />
{{agenda end}}<br />
| width=50% |<br />
Note: I may need to travel on either Mon or Tue {{implies}} please only sign up for a slot if you can make that time on both days.<br />
|}<br />
| width=20% |<br />
<br />
==== Wed, 11 Sep ====<br />
{{agenda begin}}<br />
{{agenda item|1:00p|Clare}}<br />
{{agenda item|2:00p|Yong}}<br />
{{agenda item|&nbsp;|&nbsp;}}<br />
{{agenda item|4:00|Anandh}}<br />
{{agenda item|5:00|Anu}}<br />
{{agenda end}}<br />
| width=20% |<br />
<br />
==== Thu, 12 Sep ====<br />
{{agenda begin}}<br />
{{agenda item|2:00p|Stephanie}}<br />
{{agenda item|3:00p|Victoria}}<br />
{{agenda item|&nbsp;|&nbsp;}}<br />
{{agenda item|4:30|Shaobin}}<br />
{{agenda item|5:30|Enoch}}<br />
{{agenda end}}<br />
| width=20% |<br />
<br />
==== Fri, 13 Sep ====<br />
{{agenda begin}}<br />
{{agenda item|1:00p|Vanessa}}<br />
{{agenda item|2:00p|Vasu}}<br />
{{agenda end}}<br />
|}</div>Yilinmo