Improved Interval Type-II Fuzzy Broad MPC Method for Furnace Temperature of Municipal Solid Waste Incineration Process

Furnace temperature (FT) is a critical controlled variable for ensuring the stable operation and compliance with pollution emission standards in the municipal solid waste incineration process. Due to the inherent uncertainty and nonlinearity, effectively controlling the FT is challenging. In this article, we propose an improved interval type-2 fuzzy broad model predictive control (I2T2FB-MPC) approach for FT regulation. First, we design an MPC control strategy that incorporates an interval type-2 fuzzy broad learning system (IT2FBLS) prediction model and an online optimal control (OPC) algorithm. To prevent redundant parameter updates and the overgrowth of the IT2FBLS model’s structure, we introduce triggered parameter update and adaptive structure optimization strategies. Next, we employ the gradient descent method to implement the OPC algorithm and derive the optimal control law within a finite-time horizon. Finally, we prove the convergence of the I2T2FBLS and the stability of the I2T2FB-MPC. The feasibility and performance of the proposed method are experimentally validated using numerical simulation data and actual industrial data.