Comparison of Various PID Control Algorithms on Coupled-Tank Liquid Level Control System

Abstract

On account of the unsatisfactory control effects of traditional PID control theory on dealing with complicated or nonlinear control system, the paper focused on multiple intelligent control theories, including fuzzy self-adaptation modulation PID control, BP neural network modulation PID control and RBF neural network modulation PID control. By setting double-Tank model as an example, and adopting MATLAB software programming, the research is aimed to realize tank level control via four PID control algorithms. By comparing the simulation curves of the four control algorithms, the superiority of the REF neural network in arbitrarily accurate approximating any continuous function is proved.