Design of a Fuzzy Logic Sliding mode Model Following Controller for a Brushless DC Servomotor Drivers

Amir Amir

doi:10.3844/erjsp.2011.22.28

Abstract

Problem statement: A brushless DC servomotor position control system using a fuzzy logic sliding mode model following controller or FLSMFC is presented. Approach: The FLSMFC structure consists of an integrator and variable structure system. Results: The integrator ensures the elimination of steady state error due to step and ramp command inputs, while the fuzzy control would maintain the insensitivity to parameter variation and disturbances. The FLSMFC strategy is implemented and applied to a position control of a brushless DC servomotor. Conclusion/Recommendations: Experimental results indicated that FLSMFC system performance with respect to the sensitivity to parameter variations is greatly reduced. Also, its can achieve a rather accurate servo tracking and avoids the chattering phenomenon.

Highlights

This study presents the design and implementation of brushless DC servomotor position control systems using the Fuzzy Logic Sliding mode Model Following Controller or FLSMFC approach
The robustness of the proposed FLSMFC approach (b) against large variations of plant parameters and external load disturbances has been implemented for demonstration
The results are compared with obtained from the IVSMFC and MIVSC approaches, respectively

Summary

INTRODUCTION

Advancements in magnetic materials, semiconductor power devices and control theory have made the permanent magnet motor servo drive play an important role in motion control applications (Krause et al, 2002). This study presents the design and implementation of brushless DC servomotor position control systems using the Fuzzy Logic Sliding mode Model Following Controller or FLSMFC approach. This approach, which input, e.g., a ramp input. The transfer function when the system is on the sliding surface can be shown as Eq 6: Fig. 1: The structure of FLSMFC system It can achieve a rather accurate servo tracking and is fairly robust to plant parameter variations and external load disturbances. According to the above form, use the fuzzy calculation method introduced in (Klir and Youn, 1995) and gravity method to turn fuzzy output into precise control quantity Eq 14: Fig. 4: The subordinate function of ∆ki.

MATERIALS AND METHODS

AND DISCUSSION

CONCLUSION