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.
Study and application of a constrained multi-objective optimization algorithm
1999-01-01
236380 byte
Conference paper
Electronic Resource
English
Study and Application of a Constrained Multi-object Optimization Algorithm
British Library Conference Proceedings | 1999
|Duct Shape Optimization Using Multi-Objective and Geometrically Constrained Adjoint Solver
SAE Technical Papers | 2019
|