Adaptive Fuzzy Cerebellar Model Articulation Controller for Two-Wheeled Robot
Jen-Yang Chen, Kuei-Chih Lin, Pu-Sheng Tsai, Chuan-Hsi Liu, and Jing-Ming Ouyang
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In this paper, an adaptive Fuzzy Cerebellar Model Articulation Controller (FCMAC) is proposed to control two-wheeled robot at upright position. The dynamical model of the robot,LEGO Mindstorms NXT, is derived from Lagrange of kinetic and potential energies. Based on the developed model, an adaptive FCMAC is then designed. Adaptation laws are derived from the Lyapunov stability analysis. According to the stability analysis, the developed FCMAC guarantees that the system tracking performance and the error convergence can be assured in the closed-loop system. Finally, to compare the system performances we apply the proposed FCMAC and the PID(Proportional Integral Derivative) controller to balance the two-wheeled robot.