Two-Level Local Observer-Based Decentralized Optimal Fault Tolerant Tracking Control for Unknown Nonlinear Interconnected Systems
针对执行器部分失效的未知非线性互联系统，提出一种基于两级局部神经网络观测器的分散式最优容错跟踪控制方法，通过估计故障因子和优化局部代价函数实现轨迹跟踪与系统稳定性。
In this article, a decentralized optimal fault tolerant tracking control (DOFTTC) approach is proposed for unknown nonlinear interconnected systems (NISs) with partial loss of actuator effectiveness (PLOAE) through a two-level local observer structure. To begin with, the upper boundedness assumption of the interconnected term in traditional decentralized control methods is relaxed by replacing the actual states of the coupled subsystems with their desired ones. At the first level, a local neural network observer (LNNO) is established for the fault-free subsystem to get the local control coefficient matrix. At the second level, another LNNO is designed based on the LNNO developed at the first level to estimate the effectiveness factor (EF) for the faulty subsystem with PLOAE fault, thereby the safety and reliability of the subsystem are ensured. To achieve the trajectory tracking control, an augmented system is established by combining the tracking error dynamics and reference trajectory dynamics. To obtain the decentralized optimal tracking control (DOTC), an improved local cost function is designed for each subsystem, and then, a local adaptive critic mechanism with cooperative adaptive tuning laws is constructed to solve the local Hamilton–Jacobi–Bellman equation. Hereafter, the DOFTTC can be derived with the assistance of DOTC and the EF estimation. Besides, the closed-loop NIS with asymptotic stability is analyzed via the Lyapunov stability theorem. Simulation results further demonstrate the effectiveness and reliability of the developed DOFTTC approach.