Nonlinear Predictive Control Based on ELM Neural Network and Dung Beetle Optimization Algorithm

PH neutralization process is a very typical nonlinear system in the complex industrial field, which has the characteristics of time-varying, strong interference, large delay and so on. When the working condition changes, the predictive control effect of linear control system will become very poor. To solve this problem, a nonlinear predictive control method combining neural network and intelligent optimization algorithm is proposed. Firstly, the predictive model is established by the optimized neural network and combined with MPC, and then the objective function of the rolling optimization link is solved by the intelligent optimization algorithm. The simulation results verify that the proposed control method has better control effect.