Intelligent PID controller design with adaptive criterion adjustment via least squares support vector machine

PID controllers have been widely used in many industries. They can provide robust and reliable performance for most systems. However, it is very important to tune the PID parameters properly. There is a large variety of methods for tuning the PID parameters. But none of them can cope with the wide system uncertainties. The main motivation in this paper is to present a design scheme of controllers using the LS-SVM which achieve to self-tune the parameter. This method used LS-SVM to identify the predictive model of the system off-line, then linearized the model in local on-line for reducing computation, and combined the general minimum variance to self-tune the PID parameters. The controller has a better effect than the conventional PID controller. Simulation study shows the effectiveness and good performance.