Rational entropy‐based fuzzy fault tolerant control for descriptor stochastic distribution networked control systems with packet dropout

Abstract

The fault tolerant control (FTC) problem based on rational entropy performance criteria is researched for fuzzy descriptor stochastic distribution networked control (SDNC) systems with packet dropout. The independent Bernoulli distribution is employed to describe the packet dropout in the feedback channel. The static model and the dynamic model of descriptor SDNC systems are built up by the rational square‐root fuzzy logic model (FLM) and the T‐S fuzzy model, respectively. When the given output probability density function (PDF) is not known, the minimization of output randomness becomes an important control target. First, the unknown fault is estimated by developing the fuzzy fault estimation observer. Then, the fault tolerant controller with the fault compensation is designed so that the output of the descriptor SDNC system remains with the minimum uncertainty after the fault occurs. A simulation example is supplied to prove the proposed scheme.

Fuzzy observer design for sampled nonlinear systems with measurement uncertainty

“…In [35], a linear extended state observer and a double‐loop single‐dimensional fuzzy sliding mode control were proposed and applied to intelligent control design of spiral trajectory tracking for an underactuated four‐rotor aircraft. The fault‐tolerant control problem based on rational entropy performance criteria was researched for fuzzy descriptor stochastic distribution networked control systems with packet dropout [36]. Based on the above analysis, limited research has been conducted on high‐gain observers with sampled output and measurement noise, which is also the motivation for this study.…”