Title :
Design for intelligent motion controller of unmanned vehicle
Author :
Jiuhong, Ruan ; Rui, Song ; Yibin, Li
Author_Institution :
Shandong Jiaotong Univ., Jinan, China
Abstract :
As the unmanned vehicle is a complicated system, its controller can be regarded as the selection of the controller structure space and the process of seeking proper parameters. It´s generally solved by optimal algorithm. This paper details a method in which the T-S fuzzy-neural networks is used as the control strategy and GA as the learning algorithm. This controller would not get trapped into the complicated rules of fuzzy logic controller, nor the intricate analyse in neural networks. This method can be applied in designing of a controller with monitor learning function under actual datum. Additionally, the universality of it caused this method can also be used for designing some other intelligent controllers.
Keywords :
control system synthesis; fuzzy control; fuzzy neural nets; genetic algorithms; intelligent control; learning (artificial intelligence); mobile robots; neurocontrollers; optimal control; vehicles; GA; T-S fuzzy-neural networks; Takagi-Sugeno fuzzy-neural networks; controller structure space selection; genetic algorithm; intelligent motion controller design; intricate analysis; learning algorithm; monitor learning function; neural networks; optimal algorithm; unmanned vehicle; Automatic control; Control systems; Fuzzy logic; Intelligent control; Intelligent vehicles; Monitoring; Motion control; Motion planning; Neural networks; Space vehicles;
Conference_Titel :
Intelligent Control and Automation, 2002. Proceedings of the 4th World Congress on
Print_ISBN :
0-7803-7268-9
DOI :
10.1109/WCICA.2002.1020867