Autonomous Cascade Structure Feedback Controller Design With Genetic Algorithm-based Structure Optimization

Abstract

Designing a precise feedback (FB) controller that realizes the required properties such as a wide bandwidth and robust stability/sensitivity for resonant modes is a key design issue in achieving the fast and precise positioning performance of galvano scanners used in laser drilling. The aim of this study is to develop an efficient controller structure optimization method in an autonomous cascade structure FB controller design. The genetic algorithm efficiently searches the optimal structure for a target plant with high-order resonant modes in a short time according to the fitness of the controller parameter optimization problem. The effectiveness of the proposed method is demonstrated through a comparison with the conventional full search-based structure optimization method using a laboratory galvano scanner.