Design of Multiobjective Predictive Controller Based on Genetic Algorithm

In this paper, a strategy for automatic tuning of predictive controller synthesis parameters based on multi-objective optimization is proposed. This strategy integrates the genetic algorithm to generate the synthesis parameters (the prediction horizon, the control horizon and the cost weighting factor) making a compromise between closed loop performances (the overshoot, the variance of the control and the settling time). An example of simulation is presented to illustrate the performance of this strategy in the on-line adjustment of the parameters of generalized predictive control.