A Novel Dual‐Chamber Microbial Fuel Cell Model and Its Fixed‐Time Sliding Mode Controller

ABSTRACT Microbial fuel cells (MFCs) have received extensive attention in recent years as a new source of wastewater treatment. This paper aims to address the limitations of slow convergence rates and excessive overshoot in existing controllers by introducing a novel control strategy to attain rapid and stable convergence performances. Firstly, a control‐oriented parameterized model for a dual‐chamber system is established to address the limitations of low electricity generation and slow convergence of system state variables in single‐chamber models. Then, a sliding mode controller with a novel reaching law is designed, and its fixed‐time stability is proven by using Lyapunov stability theory. A principal advantage of this methodology resides in its convergence rate being unaffected by initialization states. Finally, an improved chaos game optimization algorithm is introduced to tune the controller parameters, ensuring acquisition of optimum parameter combinations within designated boundaries. Numerical simulations validate the model's reliability and the fixed‐time sliding mode control scheme exhibits superior performance compared with the alternative algorithms concerning convergence rapidity, overshoot suppression, and steady‐state precision. The dual‐chamber model and fixed‐time sliding mode controller provide technical support for further applications of MFCs in wastewater treatment.