Fuzzy-Model-Based Robust Fault Estimation Observer Design for Nonlinear Discrete-Time Systems Using Dissipativity Theory
针对一类受有界扰动、传感器和执行器/过程故障影响的离散时间非线性系统，提出一种基于T-S模糊方法的耗散性故障估计观测器，实现故障重构，并通过仿真验证了有效性。
This article investigates the robust fault estimation (FE) scheme for a class of discrete-time nonlinear dynamics subject to simultaneous bounded disturbances, sensor and actuator/process faults through the T–S fuzzy method. By constructing an augmented system that contains sensor faults as part of its state, a dissipativity-based FE observer is proposed to achieve sensor and actuator/process faults reconstruction. Combine with the fuzzy Lyapunov function method and dissipativity theory, some brand-new conditions with slack scalars and matrices are attained to ensure that observation error systems are strictly <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$(\mathcal {R},\mathcal {W},\mathcal {S}) -\delta -$ </tex-math></inline-formula>dissipative. Besides, to improve the transient FE performance, regional pole placement problem is also considered in FE observer design. It is worth mentioning that different from some existing results which assume that actuator faults occur in a constant form, the method given in this article is suitable for more types of faults such as time-varying ones. By two simulation experiments, the validity and practicability of the proposed FE observer are fully illustrated.