Optimal Sampling and Regulation of Uncertain Interconnected Linear Continuous Time Systems
This paper presents a co-design approach for optimizing both the sampling period and the control policy of uncertain isolated and interconnected linear continuous time systems. The simultaneous optimization of event-based aperiodic sampling instants and control policy is formulated as a min-max problem and a saddle point solution is generated. An adaptive solution to the min-max control problem is obtained using a two player zero-sum game based Q-leaning approach. Novel update laws, both for flow period and jump instants, for updating the Q-function parameters are proposed in an impulsive system framework. Asymptotic regulation of the system states and Q-function parameters are guaranteed for both the isolated and interconnected systems, under the assumption of persistence of excitation (PE) condition. It is demonstrated that the resulting sampled data implementation of the controllers for both the isolated and interconnected systems do not exhibit Zeno behavior. Numerical results are included to substantiate the claims.
A. Sahoo et al., "Optimal Sampling and Regulation of Uncertain Interconnected Linear Continuous Time Systems," Proceedings of the 2017 IEEE Symposium Series on Computational Intelligence (2017, Honolulu, HI), Institute of Electrical and Electronics Engineers (IEEE), Nov 2017.
The definitive version is available at https://doi.org/10.1109/SSCI.2017.8285233
2017 IEEE Symposium Series on Computational Intelligence, SSCI (2017: Nov. 27-Dec. 1, Honolulu, HI)
Electrical and Computer Engineering
Keywords and Phrases
Artificial intelligence; Impulse response; Lyapunov methods; Adaptive solution; Asymptotic regulation; Co-design approach; Impulsive systems; Linear continuous-time system; Numerical results; Persistence of excitation; Simultaneous optimization; Continuous time systems
International Standard Book Number (ISBN)
Article - Conference proceedings
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