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Adaptive NN Fixed-Time Fault-Tolerant Control for Uncertain Stochastic System With Deferred Output Constraint via Self-Triggered Mechanism
IEEE Transactions on Cybernetics ( IF 11.8 ) Pub Date : 2022-09-28 , DOI: 10.1109/tcyb.2022.3205765 Jian Wu 1 , Furong He 1 , Hao Shen 2 , Shihong Ding 3 , Zheng-Guang Wu 4
IEEE Transactions on Cybernetics ( IF 11.8 ) Pub Date : 2022-09-28 , DOI: 10.1109/tcyb.2022.3205765 Jian Wu 1 , Furong He 1 , Hao Shen 2 , Shihong Ding 3 , Zheng-Guang Wu 4
Affiliation
For a class of nonstrict-feedback stochastic nonlinear systems with the injection and deception attacks, this article explores the problem of adaptive neural network (NN) fixed-time control ground on the self-triggered mechanism in a pioneering way. After developing the self-triggered mechanism and the delay-error-dependence function, a neural adaptive delay-constrained fault-tolerant controller is proposed by employing the backstepping technique. The self-triggered mechanism does not require an additional observer to determine the time of the data transmission, which reduces the consumption of the system resources more efficiently. In addition, the whole Lyapunov function with the delay-error-dependence term is developed to solve the deferred output constraint problem. Under the proposed controller, it can be proven that all the signals within the closed-loop system are semiglobally uniformly bounded in probability, while the convergence time is independent of the initial state and the deferred output constraint control performance is achieved. The feasibility and the superiority of the proposed control strategy are shown by some simulations.
中文翻译:
通过自触发机制实现延迟输出约束的不确定随机系统的自适应神经网络定时容错控制
针对一类具有注入和欺骗攻击的非严格反馈随机非线性系统,本文开创性地探讨了基于自触发机制的自适应神经网络(NN)定时控制问题。在开发了自触发机制和延迟误差相关函数后,采用反步技术提出了神经自适应延迟约束容错控制器。自触发机制不需要额外的观察者来确定数据传输的时间,更有效地减少了系统资源的消耗。此外,还开发了带有延迟误差相关项的整个Lyapunov函数来解决延迟输出约束问题。在所提出的控制器下,可以证明闭环系统内的所有信号在概率上都是半全局一致有界的,而收敛时间与初始状态无关,并且实现了延迟输出约束控制性能。仿真结果表明了该控制策略的可行性和优越性。
更新日期:2022-09-28
中文翻译:
通过自触发机制实现延迟输出约束的不确定随机系统的自适应神经网络定时容错控制
针对一类具有注入和欺骗攻击的非严格反馈随机非线性系统,本文开创性地探讨了基于自触发机制的自适应神经网络(NN)定时控制问题。在开发了自触发机制和延迟误差相关函数后,采用反步技术提出了神经自适应延迟约束容错控制器。自触发机制不需要额外的观察者来确定数据传输的时间,更有效地减少了系统资源的消耗。此外,还开发了带有延迟误差相关项的整个Lyapunov函数来解决延迟输出约束问题。在所提出的控制器下,可以证明闭环系统内的所有信号在概率上都是半全局一致有界的,而收敛时间与初始状态无关,并且实现了延迟输出约束控制性能。仿真结果表明了该控制策略的可行性和优越性。