Speed Proportional Integrative Derivative Controller: Optimization Functions in Metaheuristic Algorithms

Recent advancements in computer science include some optimization models that have been developed and used real applications. Some metaheuristic search/optimization algorithms tested to obtain optimal solutions speed controller applications self-driving cars. are based on social behaviour, resulting several search models, functions, parameters, thus algorithm-specific strengths weaknesses. The present paper proposes a fitness function the basis of mathematical description proportional integrative derivate controllers showing mean square error is not always best measure when looking for solution problem. this contains features equations from background derivative calculate performance system. Such results applied quantitatively evaluate twenty-one algorithms. Furthermore, improved versions considered, order investigate which aspects enhanced by applying Results show right key point get good performance, regardless chosen algorithm. aim novel objective carry out optimizations gains PID controller, using computational intelligence techniques perform optimizations. result these will demonstrate efficiency selected control schema.