Title :
Hierarchical systems control using threshold fuzzy systems
Author :
Overholt, James L. ; Cheok, K.C.
Abstract :
This paper describes a behavior-based method of controlling an autonomous skid-steer robot operating in an unknown environment. We introduce a new modular, neural-fuzzy system called a threshold fuzzy system (TFS). Supervised training, using error backpropagation, is used to find optimal parameters of the TFS. In this paper, a TFS controller is developed for a skid-steer autonomous vehicle system (AVS). Several hundred simulations are conducted and results for the AVS are compared (favorably) with a traditional neural network approach
Keywords :
backpropagation; digital simulation; electric vehicles; fuzzy control; fuzzy systems; hierarchical systems; intelligent control; mobile robots; neural nets; autonomous skid-steer robot; behavior-based method controlling; error backpropagation; hierarchical systems control; modular neural-fuzzy system; optimal parameters; simulations; skid-steer autonomous vehicle system; supervised training; threshold fuzzy systems; unknown environment; Computer errors; Computer science; Control systems; Engines; Fuzzy neural networks; Fuzzy systems; Hierarchical systems; Mobile robots; Neural networks; Systems engineering and theory;
Conference_Titel :
Systems, Man, and Cybernetics, 2001 IEEE International Conference on
Conference_Location :
Tucson, AZ
Print_ISBN :
0-7803-7087-2
DOI :
10.1109/ICSMC.2001.972892
