دانلود رایگان مقاله کنترل مد لغزش فازی سازنده آنلاین برای موتور کویل صدا

Abstract

In this paper, a voice coil motor (VCM) featuring fast dynamic performance and high position repeatability is developed. To achieve robust VCM control performance under different operating conditions, an on-line constructive fuzzy sliding-mode control (OCFSC) system, which comprises of a main controller and an exponential compensator, is proposed. In the main controller, a fuzzy observer is used to on-line approximate the unknown nonlinear term in the system dynamics with on-line structure learning and parameter learning using a gradient descent algorithm. According to the structure learning mechanism, the fuzzy observer can either increase or decrease the number of fuzzy rules based on tracking performance. The exponential compensator is applied to ensure the system stability with a nonlinear exponential reaching law. Thus, the chattering signal can be alleviated and the convergence of tracking error can be speed up. Finally, the experimental results show that not only the OCFSC system can achieve good position tracking accuracy but also the structure learning ability enables the fuzzy observer to evolve its structure on-line.

5. Conclusions

The purpose of this paper is to develop an OCFSC system to possess high-accuracy position tracking performance for a VCM. A fuzzy observer uses TSK-type fuzzy rules, which is constructed by simultaneous structure and parameter learning, to on-line approximate the unknown nonlinear term of system dynamics. After structure learning, parameters are tuned using the gradient descent algorithm and an exponential compensator is applied to ensure the system stability based on a Lyapunov function. On the basis of the structure and parameter learning, the experimental results are provided to verify the validity of the proposed OCFSC scheme in real-time VCM control applications. Further, a comparison of control characteristics among the PD control, the FSMC system, the AWFC system and the OCFSC system is summarized in Table 1. It shows that the OCFSC system is more suitable to control the VCM since the on-line structure learning and parameter learning are applied. Further works on the OCFSC system include: (1) consider autotuning of the learning rates in the parameter learning law to increase the convergence of the closed-loop system; (2) consider a method such as singular value decomposition [38] to reduce a fuzzy rules after structure and parameter learning.