Control system design based on distributed probabilistic model-building genetic algorithm

This paper presents an approach for solving non-convex control problems that arise in many practical control system designs. Distributed Probabilistic Model-Building Genetic Algorithm (DPMBGA), which is recently developed and is known as one of efficient meta-heuristics, is utilized for solving the problems. Conducting numerical experiments, we show the control system design method using DPMBGA generally achieves better performance compared to Particle Swarm Optimization (PSO) algorithm which is also known as one of efficient heuristic optimization algorithms.