A fuzzy proportional-derivative controller for engineering optimization problems using an optimality criteria approach

This paper proposes a fuzzy proportional-derivative (PD) controller optimization engine for engineering optimization problems using an optimality criteria approach. Traditional numerical optimization algorithms treat optimization problems as pure mathematical problems. Engineering knowledge about the problem is not utilized in the optimization process. The idea of using the fuzzy PD controller in engineering optimization is that, instead of using purely numerical information to obtain the new design point in the next iteration, engineering knowledge and human supervision process can be modeled in the optimization algorithm using fuzzy rules. The fuzzy PD controller optimization engine developed in this work appears to have stable performance in both structural optimization and blow molding parameter optimization examples.