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Active Optimal Fault-Tolerant Control Method for Multi-fault Concurrent Modular Manipulator Based on Adaptive Dynamic Programming

机译:基于自适应动态规划的多故障并发模块化机械臂主动最优容错控制方法

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In this paper, a novel active optimal fault-tolerant control (FTC) scheme is designed based on adaptive dynamic programming (ADP) for modular manipulator when sensor and actuator faults are concurrency. Firstly, the sensor fault is transformed into the pseudo-actuator fault by constructing a nonlinear transformation with diffeomorphism theory. Secondly, the faults estimated by the adaptive fault observer are applied to establish an improved performance index function. Next, the online policy iteration (PI) algorithm is used to solve the Hamilton-Jacobi-Bellman (HJB) equation via establishing a critic neural network. The optimal fault-tolerant controller is proved to be uniformly ultimately bounded (UUB) based on Lyapunov stable theory. Finally, the effectiveness of the proposed multi-fault-tolerant control algorithm is verified by simulation results.
机译:本文针对传感器和执行器故障并发的情况,设计了一种基于自适应动态规划(ADP)的模块化机械手主动最优容错控制方案。首先,利用微分同构理论构造非线性变换,将传感器故障转化为伪致动器故障。其次,将自适应故障观测器估计的故障应用于建立改进的性能指标函数。接下来,使用在线策略迭代(PI)算法通过建立评论者神经网络来求解Hamilton-Jacobi-Bellman(HJB)方程。基于李雅普诺夫稳定理论,证明最优的容错控制器是一致的最终有界(UUB)。最后,仿真结果验证了所提出的多容错控制算法的有效性。

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