Evolutionary Tuning Method for PID Controller Parameters of a Cruise Control System Using Metamodeling

Abstract EN

For long time the optimization of controller parameters uses the well-known classical method such as the Ziegler-Nichols and the Cohen-Coon tuning techniques.

Despite its effectiveness, these off-line tuning techniques can be time consuming especially for a case of complex nonlinear system.

This paper attempts to show a great deal on how Metamodeling techniques can be utilized to tune the PID controller parameters quickly.

Note that the plant use in this study is the cruise control system with 2 different models, which are the linear model and the nonlinear model.

The difference between both models is that the disturbances were taken into consideration for the nonlinear model, but in the linear model the disturbances were assumed as zero.

The Radial Basis Function Neural Network Metamodel is able to prove that it can minimize the time in tuning process as it is able to give a good approximation to the optimum controller parameters in both models of this system.