Decentralized Event-Triggered Asymmetric Constrained Control Through Adaptive Critic Designs for Nonlinear Interconnected Systems
In this article, a decentralized event-triggered control mechanism is established to solve the interconnected issue of continuous-time nonlinear systems with asymmetric input constraints and matched interconnections based on the adaptive critic technology. First, by inserting the discount factor, a...
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Veröffentlicht in: | IEEE transactions on systems, man, and cybernetics. Systems man, and cybernetics. Systems, 2024-01, Vol.54 (1), p.391-402 |
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Sprache: | eng |
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Zusammenfassung: | In this article, a decentralized event-triggered control mechanism is established to solve the interconnected issue of continuous-time nonlinear systems with asymmetric input constraints and matched interconnections based on the adaptive critic technology. First, by inserting the discount factor, a novel nonquadratic cost function is constructed for the constrained subsystem with nonzero equilibrium point. Meanwhile, the decentralized event-triggered control issue is transformed into a set of optimal control issues. Then, the execution of nominal subsystem is based on the event-triggered mechanism (ETM) with an event-triggering condition which increases the algorithm efficiency. Moreover, we derive the associated event-triggered Hamilton-Jacobi-Bellman (HJB) equation which arising in the discounted-cost optimal event-triggered control issues of nominal subsystems. In the implementation, an adaptive critic framework is employed to approximate the optimal cost function. Later, the experience replay (ER) approach is introduced into a novel weight tuning mechanism, which converts the traditional persistence of excitation (PE) condition into an easy-checked rank condition. Theoretically, the stability of the system and the exclusion of Zeno behavior are demonstrated. Finally, one representative example is simulated to validate the efficacy of the constructed framework. |
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ISSN: | 2168-2216 2168-2232 |
DOI: | 10.1109/TSMC.2023.3308918 |