Sliding-Mode Controlled Induction Motor Servo Drive via Genetic Algorithm

• Main Authors: Wen-Der Chou, 周旻德
• Other Authors: Faa-Jeng Lin
• Format: Others
• Language: zh-TW
• Published: 2003
• Online Access: http://ndltd.ncl.edu.tw/handle/67200140149048945012

博士 === 中原大學 === 電機工程研究所 === 91 === The purpose of this dissertation is to develop sliding-mode controllers (SMCs) based on real-time genetic algorithm (GA) for a field-oriented induction motor (IM) servo drive system to achieve robust control performance. The digital controlled IM servo drive system consists of PC, servo control card, digital signal processor (DSP), and a ramp comparison current-controlled PWM. First, an adaptive SMC based on GA is proposed. An adaptive algorithm is utilized to estimate the bound of uncertainties, and a real-time GA is developed to search the favorable adaptive parameter and switching parameter. Next, a GA-based fuzzy SMC system is proposed, which combines the merits of the SMC, the fuzzy inference mechanism and the GA. The fuzzy inference mechanism is utilized to estimate the bound of uncertainties, and the parameters of fuzzy inference mechanism are on-line tuning via GA. Then, a particular incremental motion control problem, which is specified by the trapezoidal speed command profile using GA-based multi-segment sliding-mode control (MSSMC), is proposed to control the IM servo system to match the desired speed or acceleration of speed command profile. Moreover, a GA is developed to search the favorable control gain of MSSMC. The chattering phenomena in the torque current commands are much reduced and robust tracking response can be obtained for the proposed control schemes. Finally, the effectiveness is demonstrated by some simulated and experimental results.