Dual-variables decoupling control system based on artificial neural network

Because there is a couple between the heating layer and the cooling one of the boiler in a PCT-II process control system, tuning the PID parameters is quite difficult and takes a long time to control the temperatures of the boiler besides some steady-state error. In this paper a decoupling control method based on the neural network is presented. The algorithm adopts tandem structure with the PID controller and an artificial neural network. And some appropriate compensation is used to eliminate the influence among the control variables, which can control the temperature effectively in the system. The experiment shows that the decoupling controller could almost eliminate the coupling between the variables and the steady-state output error, and achieve a better decoupling control by using the artificial neural networks to adapt to the nonlinear, time-varying characteristics.