Multi-objective Pole Placement with Evolutionary Algorithms

Multi-Objective Evolutionary Algorithms (MOEA) have been succesfully applied to solve control problems. However, many improvements are still to be accomplished. In this paper a new approach is proposed: the Multi-Objective Pole Placement with Evolutionary Algorithms (MOPPEA). The design method is based upon using complexvalued chromosomes that contain information about closed-loop poles, which are then placed through an output feedback controller. Specific cross-over and mutation operators were implemented in simple but efficient ways. The performance is tested on a mixed multi-objective H2/H control problem. Key words: Multi-objective control; Pole placement; Evolutionary Algorithms.

• Type: Conference
• Year: 2006
• Where: EMO
• Authors: Gustavo Sánchez, Minaya Villasana, Miguel Strefezza
• Keywords: Control Problem, EMO 2006, Evolutionary Algorithms, Optimization, Pole Placement