Title :
Genetically designing neuro-controllers for a dynamic system
Author :
Dasgupta, Dipankar ; McGregor, Douglas R.
Author_Institution :
Dept. of Comput. Sci., Strathclyde Univ., Glasgow, UK
Abstract :
In this paper, me describes the application of a structured genetic algorithm for integrating the process of design and training neural networks for a specific task. The important feature of this genetic approach is that it can determine the network structures and their weights solely by an evolutionary process. The paper presents some experimental results in the automatic design of neural network based controllers for balancing a typical dynamic (pole-cart) system using this genetic approach.
Keywords :
control system synthesis; genetic algorithms; intelligent control; learning (artificial intelligence); neural nets; neurocontrollers; dynamic system control; evolutionary process; network structures; network weights; neural network learning; neurocontrollers; pole-cart system; structured genetic algorithm; Acceleration; Algorithm design and analysis; Automatic control; Biological cells; Control systems; Design optimization; Force control; Genetic algorithms; Network topology; Neural networks;
Conference_Titel :
Neural Networks, 1993. IJCNN '93-Nagoya. Proceedings of 1993 International Joint Conference on
Print_ISBN :
0-7803-1421-2
DOI :
10.1109/IJCNN.1993.714341
