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標題: 以實數結構型基因演算法實現微型直流無刷馬達控制器
Implementation of Micro DC Brushless Motor Controller based on Real Structured Genetic Algorithm
作者: 蔡志瑋
Tsai, Chih-Wei
關鍵字: Genetic algorithms;基因演算法;Micro brushless DC motor feedback system;DSP;SinCos encoder;微型直流無刷馬達;數位訊號處理器;光學弦波編
出版社: 電機工程學系所
引用: 1. Liaw C.M., Shue R.Y., Chen H.C., and Chen S.C., “Development of a Linear Brushless DC Motor Drive with Robust Position Control,” Proc. Inst. Elect. Eng. Elect. Power Applicat., vol. 148, pp.111-118, 2001. 2. Fidel F.B., Aurelio G.C., and Roberto F., “Model-Based Loss Minimization for DC and AC Vector-Controlled Motors Including Core Saturation,” IEEE Trans. Ind. Elect., vol. 36, pp. 755-763, 2000. 3. Butler H., Honderd G., and Amerongen J. van, “Model Reference Adaptive Control of a Direct-Drive DC Motor,” IEEE Contr. Systems Magazine, vol. 9, pp. 80-84, 1989. 4. Kazmierkowski M.P., and Malesani L., “Current Control Techniques for Three-Phase Voltage-Source PWM Converter: A Survey,” IEEE Trans. Ind. Elect, vol. 45, pp. 691-703, 1998. 5. Jouve D., Rognon J.P., and Roye D., “Effective Current and Speed Controllers for Permanent Magnet Machines: A Survey,” in Conf. Applied Power Electronics and Exposition, pp. 384-393, 1990. 6. Mammano R.A., and Galvin J.J., “Driving Three-Phase Brushless DC Motors-a New Low Loss Linear Solution,” in Conf. Proc. Applied Power Elect. Conf. and Exposition, pp. 75-80, 1989. 7. Iwasaki M., Matusi N., “Robust Speed Control of IM with Torque Feedforward Control,” IEEE Trans. Ind. Elect., vol. 40, pp. 553-560, 1993. 8. Baik I.C., Kim K.H., and Youn M.J., “Robust Nonlinear Speed Control of PM Synchronous Motor Using Boundary Layer Integral Sliding Mode Control Technique,” IEEE Trans. Contr. Systems Technology, vol. 8, pp. 47-54, 2000. 9. Low K.S., and Hualiang Z., “Robust Model Predictive Control and Observer for Direct Drive Application,” IEEE Trans. Power Elect., vol. 15, pp. 1018-1028, 2000. 10. Holland J.H.: ‘Adaptation in Natural and Artificial Systems' (Cambridge, MIT Press, MA, 1975). 11. Gen M. and Cheng R.: ‘Genetic Algorithms and Engineering Optimization' (Wiley, New York, 2000). 12. Goldberg D.E., “Real-Coded Genetic Algorithms, Virtual Alphabets and Blocking,” Complex Systems, vol. 5, pp. 139-167, 1991. 13. Dasgupta D. and McGregor D. R., “A Structured Genetic Algorithm: the Model and the First Results,” Univ. strathclyde, U.K., Res, Rep. IKBS-2-91, 1991. 14. Lai C.C., and Chang C.Y., “A Hierarchical Genetic Algorithm Based Approach for Image Segmentation,” in Proc. IEEE Int. Conf. on Networking, Sensing and Control, Taipei, Taiwan, pp. 1284-1288, 2004. 15. Chen B.S., and Cheng Y.M., “A Structure-Specified Optimal Control Design for Practical Applications: A Genetic Approach,” IEEE Trans. Control System Technology, 6, (6), pp. 707-718, 1998. 16. Kang K.S., Man K.F., and Gu D.W., “Structured genetic algorithm for robust control system design”, IEEE Trans. Ind. Electronics, vol. 43, no. 5, pp. 575-582, 1996. 17. Cheung N. C. “An Innovative Method to Increase the Resolution of Optical Encoders in Motion Servo Systems,” IEEE 1999 International Conference on Power Electronics and Drive Systems, PEDS''99, vol. 2, pp. 797-802, Hong Kong, 1999. 18. Lin C. L. and Jan H. Y. “Mixed/Multiobjective PID Control for a Linear Brushless DC Motor: An Evolutionary Approach,” Control and Intelligent Systems, vol. 33, no. 2, 2005. 19. Jan H. Y, Wu M. T., Chen C. N., Lin, T. W. and Lin C. L. “Implement of Intelligent Servo Controllers for Micro Brushless DC Motors” Proceedings of Automation 2005 The Eighth International Conference on Automation Technology Conference Taichung, Taiwan, May 5-6, 2005.

This thesis presents the realization of a micro brushless DC motor (MBDCM) feedback system based on a real ordered genetic algorithm (RSGA) approach, which combines the advantages of conventional real genetic algorithms (RSGA) and structured genetic algorithms (SGA), for determining an optimal controller. A dynamic crossover and mutation probability adjusting method based on Butterworth filters was proposed to improve the overall searching performance of the RSGA. The optimal MBDCM controller is realized on the TMS320F240 digital signal processing (DSP) development board to achieve hardware compactness. Control design requirements include robust stability, control consumption and tracking performance. A SinCos encoder with a line drive of 128 sin/cos signals per revolution was implemented to achieve and position control. SinCos encoders have the inherent advantage of providing high resolutions via signal interpolation. The interpolation method inherited is simple yet effective, based on logic devices.
To verify the effectiveness of the proposed methodology, simulations are performed on MATLAB and an experimental platform involving a motor driver, a micro brushless DC motor, and a SinCos encoder was built to verify the applicability of the proposed method in practical situations.
Simulation studies and experimental results show that the proposed algorithm converges faster, excels in performance, and yields better performance for a motor feedback controller in comparison to traditional approaches.
其他識別: U0005-3007200816001900
Appears in Collections:電機工程學系所

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