Parallelized Algorithm for Persistent Feasibility in Linear Systems with Multiple, External Switching Signals

Ensuring feasibility in externally switched systems usually requires identifying time-varying, control invariant (CI) sets that ensure state and input constraints can be respected under any possible switching signal. As with traditional, time-invariant CI sets, these time-varying constraints can be...

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Bibliographic Details
Published in2022 IEEE 61st Conference on Decision and Control (CDC) pp. 485 - 690
Main Authors Hall, Richard A, Bridgeman, Leila
Format Conference Proceeding
LanguageEnglish
Published IEEE 06.12.2022
Subjects
Control systems
Costs
Directed graphs
Linear systems
Scalability
Switched systems
Switches
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Summary:Ensuring feasibility in externally switched systems usually requires identifying time-varying, control invariant (CI) sets that ensure state and input constraints can be respected under any possible switching signal. As with traditional, time-invariant CI sets, these time-varying constraints can be very difficult to compute for higher dimensional systems. Furthermore, if multiple switching signals are present, the number of switching sequences that must be considered grows exponentially. Previous works would struggle to account for this growth. Inspired by distributed systems, this work examines a class of high dimensional systems with multiple switching signals. The switching signals are constrained using directed graphs that are significantly more flexible than dwell time based methods. An iterative algorithm is developed that computes the time-varying CI sets for this class of systems. Critically, this algorithm is parallelized over the number of agents, preventing the exponential growth in computation time as agents are added to the system. The scalability of the results is demonstrated on a randomized numerical example.
ISSN:2576-2370
DOI:10.1109/CDC51059.2022.9992861