OCPA Bionic Autonomous Learning System and Its Application to Robot Poster Balance Control
CAI Jian-Xian1,2, RUAN Xiao-Gang1
1.College of Electronic Information and Control Engineering, Beijing University of Technology, Beijing 100124 2.Institute of Disaster Prevention, Sanhe 065201
Abstract An operant conditioning probabilistic automation (OCPA) bionic autonomous learning system is constructed according to nonlinear, strong-coupling and complex two-wheeled self-balancing robot dynamic system. The OCPA bionic autonomous learning system is a probabilistic automaton based on Skinner operant conditioning whose main character lies in simulating the operant conditioning mechanism of biology. And it has bionic self-organization function which contains the self-learning and adaptive functions, and thus the OCPA automaton can be used to describe, simulate and design various self-organization systems. The convergence of operant conditioning learning algorithm of OCPA learning system is proved theoretically. The results of both simulation and experiment applied to two-wheeled robot poster balance control indicate that the OCPA learning system does not require the robot model, and the motion balanced skills of robot are formed, developed and perfected gradually by simulating the operant conditioning mechanism of biology.
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2011, Vol. 24 
