Approximate Output Regulation of Discrete-Time Stochastic Multiagent Systems Subject to Heterogeneous and Unknown Dynamics

• Published in: IEEE transactions on systems, man, and cybernetics. Systems Vol. 52; no. 10; pp. 6373 - 6382
• Main Authors: Li, Shaobao, Wang, Feng, Er, Meng Joo, Yang, Zhenyu
• Format: Journal Article
• Language: English
• Published: New York IEEE 01.10.2022; The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
• Subjects: Adaptive control; Biological neural networks; Compensation; Control theory; Cooperative control; Decentralized control; Discrete time systems; Dynamical systems; Feedback control; Feedforward control; Mathematical analysis; Mathematical models; Multiagent system (MAS); Multiagent systems; neural network; Neural networks; Nonlinear dynamical systems; Nonlinear dynamics; Nonlinearity; Observers; output regulation; Regulation; Stability analysis; State estimation; State observers; stochastic system; Vehicle dynamics
• ISSN: 2168-2216; 2168-2232
• DOI: 10.1109/TSMC.2022.3145354

The output regulation approach has been extensively applied for the cooperative control of heterogeneous multiagent systems (MASs) with known dynamics, but rarely for MASs subject to stochastic and unknown dynamics. One challenging problem is that it is still unclear how to construct the regulator equations of stochastic MASs with unknown dynamics for dynamic exosystem compensation. Toward this end, this article develops a novel distributed control scheme for the approximate output regulation of discrete-time stochastic MASs subject to heterogeneous and unknown nonlinear dynamics. A distributed observer is designed for the exosystem-state estimation of agents, based upon which nonlinear regulator equations are constructed for the feedforward control design, thereby achieving distributed exosystem compensation. A high-order neural network is deployed to approximately solve the nonlinear regulator equations with unknown nonlinearity, and an adaptive control law is developed for the approximate output regulation of discrete-time stochastic MASs. Stability analysis shows that the closed-loop system is semiglobally uniformly ultimately bounded. Simulation results demonstrate the effectiveness and efficiency of the proposed control law.