Study and application of a constrained multi-objective optimization algorithm

It is well known that the PID regulator has been very successful and widely accepted for controlling systems where one objective function is the performance criterion. When the objective functions are more than one, to select the parameters of the controller is very difficult. Especially for modern nonlinear robust controllers, it is almost impossible to tune these parameters. This paper introduces the multiobjective fuzzy genetic optimization algorithm, which provides an effective, efficient and intuitive framework for selecting these parameters. This can be used to design complex controllers in developing the diesel engine.