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Online fault compensation control based on policy iteration algorithm for a class of affine non-linear systems with actuator failures

机译:基于策略迭代算法的一类带有执行器故障的仿射非线性系统在线故障补偿控制

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摘要

In this study, a novel online fault compensation control scheme based on policy iteration (PI) algorithm is developed for a class of affine non-linear systems with actuator failures. The control scheme consists of a PI algorithm and a fault compensator. For fault-free dynamic models, the PI algorithm is developed to solve the Hamilton-Jacobi-Bellman equation by constructing a critic neural network, and then the approximate optimal control policy can be derived directly. Alternatively, the actuator failure is reconstructed adaptively to achieve online fault compensation without the fault detection and isolation mechanism. The closed-loop system is proved to be asymptotically stable via Lyapunov's direct method. Two numerical simulation examples are given to demonstrate the effectiveness of the proposed fault compensation control scheme.
机译:在这项研究中,针对一类带有执行器故障的仿射非线性系统,开发了一种基于策略迭代(PI)算法的新型在线故障补偿控制方案。控制方案由PI算法和故障补偿器组成。对于无故障动态模型,通过构造评论器神经网络,开发了PI算法来求解Hamilton-Jacobi-Bellman方程,然后可以直接推导近似的最优控制策略。可替代地,执行器故障被自适应地重构以实现在线故障补偿,而无需故障检测和隔离机制。通过李雅普诺夫的直接方法证明了闭环系统是渐近稳定的。给出了两个数值仿真例子,以证明所提出的故障补偿控制方案的有效性。

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