Fuzzy integral fault-tolerant control of an activated sludge process

Abstract

This paper presents a fuzzy integral fault-tolerant controller (FIFTC) for robust regulation of substrate and dissolved oxygen in activated sludge processes (ASP). The nonlinear dynamics of the process are represented using an augmented Takagi–Sugeno (TS) fuzzy model, which includes an additional vector representing the integral state to improve tracking accuracy. A fuzzy proportional-integral (PI) observer is employed to estimate states and detect actuator faults, particularly in the aeration system. Controller and observer gains are computed by solving linear matrix inequalities (LMIs), while an H∞ performance criterion, defined by the parameter, ensures effective disturbance attenuation and bounds the error energy. In the simulation, we considered actuator faults of the loss of effectiveness (LOE) type. Simulation results demonstrate that FIFTC significantly outperforms classical linear quadratic regulator (LQR) in terms of tracking accuracy, robustness, and fault tolerance, even under partial actuator failures and external disturbances. The proposed FIFTC control strategy, which leverages fuzzy modeling, robust observers, and LMI-based optimization, provides significant benefits, primarily by improving efficiency, reducing energy consumption, and enhancing robustness.