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Author:

Cai, Jianxian (Cai, Jianxian.) | Ruan, Xiaogang (Ruan, Xiaogang.)

Indexed by:

CPCI-S EI Scopus

Abstract:

This paper constructs a stochastic fuzzy controller to realize self-balancing control of two-wheeled robot. The rule of fuzzy controller is stochastic, which is automatically generated by an OCPFA learning system and optimized online. The OCPFA learning system is in fact a Probabilistic Finite Automata (PFA) which based on Skinner Operant Conditioning (Skinner OC), and it is composed by a bionic reorientation mechanism and an OC learning mechanism. The reorientation mechanism take for orientation function of robot posture balance as the goal-orientation, and response to the output control variable of fuzzy stochastic controller; Learning mechanism updated probability contribution of output control variable by using the response information form the environment and then choose the optimal control variable according to the new probability contribution. The OCPFA learning system gradually adapts to the environment changes by interacting with the dynamic environment based on which the learning system realize the self-organization of stochastic fuzzy control rules and show character of autonomous learning. In the same time the theoretical prove that the process of autonomous learning is convergent in sense of probability. The simulation indicate the stochastic fuzzy controller can successfully applied in two-wheeled robot self-balancing without requiring the model of the robot and the robot can show control behavior of autonomous learning which similar to animal's OC learning behavior.

Keyword:

OCPFA learning system self-balancing control autonomous learning stochastic fuzzy controller

Author Community:

  • [ 1 ] [Cai, Jianxian]Beijing Univ Technol, Dept Pattern Recognit & Artificial Intelligence, Beijing, Peoples R China
  • [ 2 ] [Ruan, Xiaogang]Beijing Univ Technol, Dept Pattern Recognit & Artificial Intelligence, Beijing, Peoples R China

Reprint Author's Address:

  • [Cai, Jianxian]Beijing Univ Technol, Dept Pattern Recognit & Artificial Intelligence, Beijing, Peoples R China

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Source :

2010 8TH WORLD CONGRESS ON INTELLIGENT CONTROL AND AUTOMATION (WCICA)

Year: 2010

Page: 4775-4780

Language: English

Cited Count:

WoS CC Cited Count: 3

SCOPUS Cited Count: 3

ESI Highly Cited Papers on the List: 0 Unfold All

WanFang Cited Count:

Chinese Cited Count:

30 Days PV: 5

Online/Total:1027/10809913
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