期刊
INFORMATION SCIENCES
卷 605, 期 -, 页码 119-135出版社
ELSEVIER SCIENCE INC
DOI: 10.1016/j.ins.2022.05.021
关键词
Adaptive consensus; Inverse optimal control; Actuator and sensor faults; Multiagent systems
资金
- National Natural Science Foundation of China [U1911401, 61703112, 61973087]
- State Key Laboratory of Synthetical Automation for Process Industries, China [2020-KF-21-02]
- National Key Research and Development Program of China [2020AAA0108303]
This paper addresses a neuroadaptive inverse optimal consensus problem for uncertain nonlinear multiagent systems subject to actuator and sensor faults. The proposed control mechanism minimizes a loss function without solving the Hamilton-Jacobi-Bellman equation, simplifying the computational workload. Additionally, a compensation strategy for actuator and sensor faults is considered, and a novel fault-tolerant adaptive inverse optimal protocol incorporating the Lyapunov design is constructed. The effectiveness of the control design is demonstrated through a simulation example.
This paper addresses a neuroadaptive inverse optimal consensus problem of uncertain nonlinear multiagent systems (MASs) subject to actuator and sensor faults simultaneously. Unlike traditional adaptive dynamic programming methods, the proposed control mechanism minimizes a loss function without solving the Hamilton-Jacobi-Bellman equation, which simplifies the computational workload. In addition, a compensation strategy for actuator and sensor faults is considered and a novel fault-tolerant adaptive inverse optimal protocol incorporating the Lyapunov design is constructed. It is demonstrated that the system is input-to-state stabilizable (ISS) under the designed inverse optimal controller and the tracking errors of the MASs can converge to a predefined range. A simulation example is presented to illustrate the effectiveness of the control design. (C) 2022 Elsevier Inc. All rights reserved.
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