A cascade active disturbance rejection control based on SPSA-memory optimization for SCR denitration process

Abstract

The selective catalytic reduction (SCR) denitration process is characterized by high inertia, significant time delay, and strong nonlinearity, which poses a significant challenge for the control problem. In this paper, an internal model control (IMC)-based active disturbance rejection control (ADRC) strategy with delay compensation is proposed. By decomposing the plant dynamics into a nominal model and an uncertain part, IMC and extended state observer (ESO) in ADRC are used to handle these two parts, respectively. Then a modified simultaneous perturbation stochastic approximation (MSPSA) algorithm is employed to perform online parameters optimization, including the parameter in the IMC filter and two bandwidth parameters in the ADRC. The proposed algorithm incorporates a memory function that recalls historical data, enabling real-time updates of optimal parameters as operating conditions change. Simulation results demonstrate that the proposed scheme outperforms traditional proportional-integral-derivative (PID) control and linear ADRC, showcasing superior control effectiveness.