RBF Neural Network of Sliding Mode Control for Time-Varying 2-DOF Parallel Manipulator System

Haizhong Chen,Songlin Wo

doi:10.1155/2013/201712

Abstract

This paper presents a radial basis function (RBF) neural network control scheme for manipulators with actuator nonlinearities. The control scheme consists of a time-varying sliding mode control (TVSMC) and an RBF neural network compensator. Since the actuator nonlinearities are usually included in the manipulator driving motor, a compensator using RBF network is proposed to estimate the actuator nonlinearities and their upper boundaries. Subsequently, an RBF neural network controller that requires neither the evaluation of off-line dynamical model nor the time-consuming training process is given. In addition, Barbalat Lemma is introduced to help prove the stability of the closed control system. Considering the SMC controller and the RBF network compensator as the whole control scheme, the closed-loop system is proved to be uniformly ultimately bounded. The whole scheme provides a general procedure to control the manipulators with actuator nonlinearities. Simulation results verify the effectiveness of the designed scheme and the theoretical discussion.

Highlights

The past several decades have seen a rapid increase in parallel manipulators connected to the control system
When the system reaches the sliding mode, the system with variable structure control is insensitive to the external disturbances and the variations of the plant parameters, and it has been widely applied to the manipulator system due to its operation characteristics for the sake of fastness, robustness, and stability in large load variations
According to angle displacement error responses of joint A1 in Figures 11 and 12, we can see that the angle error of joint stable at origin is within 40 s based on time-varying sliding mode control (TVSMC) algorithm, but based on radial basis function (RBF) TVSMC algorithm it is not later than 3 s

Summary

Introduction

The past several decades have seen a rapid increase in parallel manipulators connected to the control system. When the system reaches the sliding mode, the system with variable structure control is insensitive to the external disturbances and the variations of the plant parameters, and it has been widely applied to the manipulator system due to its operation characteristics for the sake of fastness, robustness, and stability in large load variations. All those merits are gotten at the cost of the chattering. The RBF TVSMC algorithm and the TVSMC algorithm are compared after being tested

System Model

TVSMC Design and Parameter Setting

RBF SMC Algorithm Design

Simulation Tests

Conclusions