Adaptive Fault-Tolerant Control for Nonlinear Uncertain Electromechanical Systems with Full-State Time-Varying Constraints

大鹏 李
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Abstract

This paper proposes an adaptive fault-tolerant control method for nonlinear electromechanical system with full-state time varying constraints. In order to ensure the control performance of the system, a fault tolerant compensation controller is constructed to eliminate the influence of the actuator loss of effectiveness and bias fault. The time-varying barrier Lyapunov functions are introduced to ensure that all the system state does not exceed the specified time-varying constraint range; especially in the case of actuator failure, the full-state constraints are not violated. Neural network as the approximator is employed to approximate unknown function in the processing system. Based on the Lyapunov analysis, it is proved that all the signals in the closed-loop system are bounded and the good tracking performance of the system is achieved. The simulation results further illustrate the effectiveness of the proposed control strategy.
具有全状态时变约束的非线性不确定机电系统自适应容错控制
针对具有全状态时变约束的非线性机电系统,提出了一种自适应容错控制方法。为了保证系统的控制性能,构建了容错补偿控制器,消除了执行器失效和偏置故障的影响。引入时变势垒Lyapunov函数,保证系统所有状态不超过规定的时变约束范围;特别是在执行器失效的情况下,不违反全状态约束。采用神经网络作为逼近器对加工系统中的未知函数进行逼近。基于李雅普诺夫分析,证明了闭环系统中所有信号都是有界的,系统具有良好的跟踪性能。仿真结果进一步验证了所提控制策略的有效性。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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