Improved Coupled Tank Liquid Levels System Based on Swarm Adaptive Tuning of Hybrid Proportional-Integral Neural Network Controller

Abstract

Problem statement: Accuracy and stability of many systems in chemical and process industries which has Two-Input Two-Output (TITO) is one of the key factors of process which have cross coupling between process input and output. Approach: Unlike traditional neural network weight adaptation using gradient descent method, Particles Swarm Optimization (PSO) technique was utilized for adaptive tuning of neural network weights adjustment and fine tuning the controller’s parameters. Design approach for controlling liquid levels of Coupled Tank TITO system by using hybrid PI-Neural Network (hybrid PI-NN) controllers. Results: Tuning method for parameters of improved hybrid PI-NN controller was also discussed. Conclusion: Performances of proposed method also compared with PID-NN controllers, it was shown that hybrid PI-NN controller exhibited better performance in terms of transient response analysis.