Sensor and actuator fault-tolerant control based on fuzzy unknown input observer: A polynomial fuzzy approach

This paper studies sensor and actuator Fault-Tolerant Control (FTC) of nonlinear systems. The fault tolerance is necessary to have desired performance and prevent the system from instability. A Polynomial Fuzzy Unknown Input Observer (PFUIO) with immeasurable premise variable is proposed to estimate the states of the system, and sensor and actuator faults; and to use them in the controller to compensate the faults. The essence of the sensor fault necessitates considering the third class of Polynomial Fuzzy Model (PFM) with immeasurable premise variables. This makes the design procedure more complicated. Application of PFM reduces the conservatism and increases modeling accuracy. Moreover, the disturbance and model uncertainties are considered to realize more practical conditions. The polynomiality leads to Sum Of Squares (SOS), which can be solved using existing software. The proposed approach is evaluated by applying it to the inverted pendulum system. Simulating results show better performance of the proposed method as compared with the Linear Matrix Inequality (LMI) approach (C) 2021 Elsevier B.V. All rights reserved.

Automated summary

This paper studies sensor and actuator Fault-Tolerant Control (FTC) of nonlinear systems, proposing a Polynomial Fuzzy Unknown Input Observer (PFUIO) for estimating system states and faults. The proposed approach shows better performance compared with the Linear Matrix Inequality (LMI) approach.