Self-triggered optimal fault-tolerant control for saturated-inputs zero-sum game nonlinear systems via particle swarm optimization-based reinforcement learning

•In this paper, PSOA is used for the first time to solve the optimal ZSG control problem for nonlinear systems. The algorithm can compensate for faults negative effects while minimizing the cost function.•Different from previous works on ETC, the design of the STC strategy avoids continuous monitori...

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Published in:Communications in nonlinear science & numerical simulation Vol. 153; p. 109512
Main Authors: Zhao, Junzheng, Niu, Ben, Xu, Ning, Zong, Guangdeng, Zhang, Liang
Format: Journal Article
Language:English
Published: Elsevier B.V 01.02.2026
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ISSN:1007-5704
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Abstract •In this paper, PSOA is used for the first time to solve the optimal ZSG control problem for nonlinear systems. The algorithm can compensate for faults negative effects while minimizing the cost function.•Different from previous works on ETC, the design of the STC strategy avoids continuous monitoring for trigger errors in this study. Moreover, a better compromise between system performance and communication load can be achieved.•The design of the STC is suitable for nonlinear systems with saturated-inputs, which not only adjusts trigger moments in real time to reduce computational burden, but also ensures that the system maintains stable operation and avoids over-excitation. This paper proposes a self-triggered fault-tolerant optimal control scheme for zero-sum game nonlinear systems with saturated-inputs by using particle swarm optimization-based adaptive dynamic programming. First, a new self-triggered control strategy is proposed to equivalently convert a fault-optimal control problem into finding an optimal zero-sum game control scheme. Then, a saturated-inputs problem is solved by constructing a novel value function. In addition, a self-triggered condition is designed to reduce the communication bandwidth and energy consumption. And, the particle swarm optimization algorithm is used instead of gradient descent to find the optimal neural network weights. Finally, the effectiveness of the developed control scheme is demonstrated via simulation results.
AbstractList •In this paper, PSOA is used for the first time to solve the optimal ZSG control problem for nonlinear systems. The algorithm can compensate for faults negative effects while minimizing the cost function.•Different from previous works on ETC, the design of the STC strategy avoids continuous monitoring for trigger errors in this study. Moreover, a better compromise between system performance and communication load can be achieved.•The design of the STC is suitable for nonlinear systems with saturated-inputs, which not only adjusts trigger moments in real time to reduce computational burden, but also ensures that the system maintains stable operation and avoids over-excitation. This paper proposes a self-triggered fault-tolerant optimal control scheme for zero-sum game nonlinear systems with saturated-inputs by using particle swarm optimization-based adaptive dynamic programming. First, a new self-triggered control strategy is proposed to equivalently convert a fault-optimal control problem into finding an optimal zero-sum game control scheme. Then, a saturated-inputs problem is solved by constructing a novel value function. In addition, a self-triggered condition is designed to reduce the communication bandwidth and energy consumption. And, the particle swarm optimization algorithm is used instead of gradient descent to find the optimal neural network weights. Finally, the effectiveness of the developed control scheme is demonstrated via simulation results.
ArticleNumber 109512
Author Xu, Ning
Niu, Ben
Zhao, Junzheng
Zhang, Liang
Zong, Guangdeng
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  organization: College of Control Science and Engineering, Bohai University, Jinzhou Liaoning, 121013, China
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  surname: Niu
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  organization: Faculty of Electronic Information and Electrical Engineering, Dalian University of Technology, Dalian Liaoning, 116024, China
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  givenname: Ning
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  email: hpxuning@163.com
  organization: College of Information Science and Technology, Bohai University, Jinzhou, Liaoning 121013, China
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  givenname: Guangdeng
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  surname: Zong
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  givenname: Liang
  orcidid: 0000-0002-1907-016X
  surname: Zhang
  fullname: Zhang, Liang
  email: md18638@126.com
  organization: College of Control Science and Engineering, Bohai University, Jinzhou Liaoning, 121013, China
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Keywords Self-triggered control
Zero-sum games
Saturated-inputs
Optimal control
Particle swarm optimization algorithm
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Snippet •In this paper, PSOA is used for the first time to solve the optimal ZSG control problem for nonlinear systems. The algorithm can compensate for faults...
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SubjectTerms Optimal control
Particle swarm optimization algorithm
Saturated-inputs
Self-triggered control
Zero-sum games
Title Self-triggered optimal fault-tolerant control for saturated-inputs zero-sum game nonlinear systems via particle swarm optimization-based reinforcement learning
URI https://dx.doi.org/10.1016/j.cnsns.2025.109512
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