Sensor and Actuator Fault Estimations and Self-Healing Control of Discrete-Time T-S Fuzzy Model With Double Observers and Its Application to Wastewater Treatment Process

Abstract

In real-world industrial control systems, the extended usage of diverse equipment and instruments over extended periods increases the likelihood of malfunctions in any process unit. Such malfunctions can significantly impact the entire system, leading to substantial economic losses. To address these challenges, this article proposes an actuator-sensor fault estimation and self-healing control scheme aimed at ensuring the stable and efficient operation of a discrete Takagi-Sugeno (T-S) fuzzy system. First, a dual observer fault estimation method is introduced to overcome the limitations of highly conservative stability conditions and limited applicability encountered when estimating actuator and sensor faults with a single observer. Second, self-healing controllers based on integral sliding mode and state feedback are individually designed. Lastly, leveraging the T-S fuzzy model of the wastewater treatment plant, simulation experiments are conducted to validate the efficacy of the proposed methods. Comparative analysis of simulation results reveals that the dual observer fault estimation methods exhibit faster response speed for both faults estimation. Furthermore, in comparison to other self-healing controllers, the fuzzy-weighted self-healing controller exhibits superior overall performance.