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Robust Model Predictive Control for Signal Temporal Logic Synthesis
Abstract Most automated systems operate in uncertai …
Most automated systems operate in uncertain or adversarial conditions, and have to be capable of reliably reacting to changes in the environment. The focus of this paper is on automatically synthesizing reactive controllers for cyber-physical systems subject to signal temporal logic (STL) specifications. We build on recent work that encodes STL specifications as mixed integer linear constraints on the variables of a discrete-time model of the system and environment dynamics. To obtain a reactive controller, we present solutions to the worst-case model predictive control (MPC) problem using a suite of mixed integer linear programming techniques. We demonstrate the comparative effectiveness of several existing worst-case MPC techniques, when applied to the problem of control subject to temporal logic specifications; our empirical results emphasize the need to develop specialized solutions for this domain.
lop specialized solutions for this domain.  +
Authors Samira S. Farahani, Vasumathi Raman, and Richard M. Murray  +
Funding The TerraSwarm Research Center +
ID 2014n  +
Source 2015 IFAC Conference on Analysis and Design of Hybrid Systems (ADHS)  +
Tag frm15-adhs  +
Title Robust Model Predictive Control for Signal Temporal Logic Synthesis +
Type Conference paper  +
Categories Papers
Modification date
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28 May 2016 22:12:07  +
URL
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http://www.cds.caltech.edu/~murray/preprints/frm15-adhs.pdf  +
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Robust Model Predictive Control for Signal Temporal Logic Synthesis + Title
 

 

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