Modeling and Control of a Spherical Rolling Robot Using Model Reference Adaptive Control

摘要

Generally the conventional controller not well tuned. Due to the abstraction of the real system ,unmodeled dynamics, parameter variations and disturbance results in poor performance. In our paper which presents the control of a spherical rolling robot based on fuzzy control and a adaptive control theory based on learning algorithm.This proposed control schemes assure asymptotic stability of the system in a closed space based on a neuro fuzzy control and a conventional controller. The derived parameter updating rules of the neuro-fuzzy system using MRAS theory can be proved by its lyapunov function. Simulation results of this proposed scheme shows that without knowing dynamic equations we can eliminate the steady state error and we can enhance the transient response of the spherical rolling robot. One of the reference paper describes about a prototype and analytical studies of the spherical rolling robot by using a new design of the nonholonomic robot constraints. The mathematical model of the spherical rolling robots motion was developed by using the nonholonomic constraints. It has shown experimentally that the model subjected areas well with the results of the system. So many methods were developed for planning feasible, minimum time and minimum energy trajectories for the robot.