Difference between revisions of "CDS270(Fall2014)"
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Revision as of 18:35, 30 September 2014
Networked Control Systems
Tu/Th 1:00-2:25 pm, 243 ANB
Instructor: Yilin Mo (yilinmo@caltech.edu)
Pre-requisites
Undergraduate linear algebra, probability and signal processing, understanding of modern (state space) control theory
Course Schedule
| Week | Date | Topic | Reading |
| 1 | |||
| 30 Sept (Tu) | Course Overview | Control in an Information Rich World | |
| 2 Oct (Th) | State Estimation, Kalman Filtering | Kalman Filtering | |
| 2 | 7 Oct (Tu) | Discrete-time Algebraic Riccati Equations | |
| 9 Oct (Th) | Estimation over Lossy Networks | ||
| 3 | 14 Oct (Tu) | Off-line Sensor Scheduling | |
| 16 Oct (Th) | Event-based Estimation and Control | ||
| 4 | 21 Oct (Tu) | Control Over Lossy Networks, Witsenhausen's counterexample | |
| 23 Oct (Th) | Average Consensus | ||
| 5 | 28 Oct (Tu) | Non-Negative Matrices | |
| 30 Oct (Th) | Gossip Algorithm | ||
| 6 | 4 Nov (Tu) | Variants of Average Consensus | |
| 6 Nov (Th) | Large Deviation | ||
| 7 | 11 Nov (Tu) | Distributed Hypothesis Testing | |
| 13 Nov (Th) | Distributed Kalman Filtering | ||
| 8 | 18 Nov (Tu) | Fault Detection and Identification | |
| 20 Nov (Th) | Generic Properties of Linear Structural Systems | ||
| 9 | 25 Nov (Tu) | Secure Consensus Algorithm | |
| 27 Nov (Th) | Thanksgiving, No class | ||
| 10 | 2 Dec (Tu) | Research Presentation | |
| 4 Dec (Th) | Research Presentation |
Course Description
Networked control systems are spatially distributed systems for which the communication between sensors, actuators and controllers is supported by communication networks. Recent advances in sensing, communication technologies and computer architecture have led to the rapid growth of cost effective and low power devices, which dramatically increases the adaptability, efficiency and functionality of the control systems. However, networked control systems also introduce new challenges, as the information becomes local to each node and the information sharing between nodes may subject to network effects such as packet drop or delay.
In this course, we will review several recent advancements in networked control theory. We first consider a centralized control scheme, where the communication between the sensor, the controller and the actuator is unreliable. We then move to distributed control schemes and analyze the consensus algorithm, as it is key for many distributed control applications. Next, we study the performance of a consensus-based distributed inference algorithm. Finally, we discuss the consensus algorithm in adversarial environment.
Course Administration
There is no required homework and no midterm or final exam. Course grades will be based on a research presentation on last week.
