Title :
Solving the nonlinear dynamic control problems by GA with structurizing the search space
Author :
Kawaji, S. ; Ogasawara, Kenichi
Author_Institution :
Dept. of Electr. Eng. & Comput. Sci., Kumamoto Univ., Japan
Abstract :
We propose a new search method of genetic algorithm (GA), which reduces the difficulties of the design of the fitness function. In the method, the control objective is divided into some intermediate control objectives according to the control strategy. The search process progresses with the fitness function corresponding to the intermediate control objective, and the process is controlled by switching the fitness function based on the average fitness value of the current candidate solutions so that the optimum solution with desired quality may be found. Thus, the search space is structured repeatedly during the search process by switching the fitness function based on the quality of the current candidate solutions. In order to confirm the availability of the proposed method, the swing-up control of the cart-pendulum system is used as an example, and some simulation results are given
Keywords :
genetic algorithms; nonlinear dynamical systems; optimal control; pendulums; search problems; cart-pendulum system; fitness function; genetic algorithm; nonlinear dynamic control; search space; swing-up control; Algorithm design and analysis; Control systems; Genetic algorithms; Genetic engineering; Motion control; Nonlinear control systems; Nonlinear dynamical systems; Power engineering and energy; Process control; Search methods;
Conference_Titel :
Intelligent Control, 1995., Proceedings of the 1995 IEEE International Symposium on
Conference_Location :
Monterey, CA
Print_ISBN :
0-7803-2722-5
DOI :
10.1109/ISIC.1995.525052