近年來，在精密機械工業、半導體和生物產業的快速發展下，對於長行程與精密定位的伺服機構要求也越來越高。以往傳統PID控制器在精密定位控制的過程中需仰賴精確的系統數學模型，然而實際的系統參數容易受環境的影響而改變，尤其靜摩擦是高度非線性、時變性與隨位置變化。因此系統的數學模型參數難以估測，造成控制律設計複雜化。
目前許多研究採用智能控制方法應用在數學模型難以建立的系統與時變性的系統參數。其中模糊邏輯控制為仿效人類思維的方法，不需仰賴系統數學模型，有較佳的容錯性、適應性與強健性，較適合於非線性時變系統。但為了達到精密定位，仍須對靜摩擦力作定性分析，然後依賴操控者對於系統特性的瞭解，直覺地決定受控對象的控制策略。本研究以直流永磁旋轉馬達為對象，此馬達具有旋轉編碼器，解析度為1,620,000 count/rev，並以線性驅動器驅動馬達。
本研究使用模糊 控制器於直流永磁旋轉馬達，實驗結果顯示定位穩態誤差為 0 count，最大超越量約 3~8 counts。在不同負載狀態下仍能達到零穩態誤差。唯定位性能的重複率尚未能達到100%。

In recent years, servomechanisms need for long range and precision positioning because of the development of precision machinery industrial, semiconductor and biotechnology industry. In order to achieve precision positioning, the designs of the traditional PID controllers need accurate mathematical models. However, the actual system parameters are susceptible to the change of environment effects, especially friction. Friction is high-nonlinear, time-varying and position-varying. Due to that, it is difficult to estimate friction model and parameter, and it increases the complexity of control law design.
At present, many studies have used intelligent control on the difficult modeled system and time-varying parameters. Fuzzy logic control follows the human thinking. This kind of control design does not need system mathematical model, but has better fault tolerance, adaptability and robustness. It is suit for nonlinear time-varying system. In order to achieve precision positioning, it is necessary for qualitative analysis of static friction. Base on the understanding of properties of static friction, it is able to intuitively decide the control strategy with fuzzy controller. It can simple the complexity of control law design. The system hardware in this research is a PM DC motor. It is driven with a linear amplifier, and armed a rotary encoder, the resolution is 1,620,000 counts/rev.
A PI-like fuzzy controller is designed for the rotary motor to achieve precision positioning. The experimental result shows that the final positioning error is zero count and the overshoot is 3 to 8 counts. Under different loading, the positioning error still can achieve zero count. But the positioning performance didn’t provide 100 % repeatability.

[1]Tadahiko Murata, "Adjusting Membership Functions of Fuzzy Classification Rules by Genetic Algorithms," p 1819-1824, 1995.
[2]C. Canudas de Wit, H. Olsson, K.J. Astrom, P. Lischinsky, "New Model for Control of Systems with Friction," Automat. Control 40 (3) 419–425, 1995.
[3]H. Olsson, K.J. Åström, C. Canudas de Wit, M. Gäfvert and P. Lischinsky, "Friction Models and Friction Compensation," Eur. J. Control, vol. 4, no. 3, pp. 176–195, 1998.
[4]M. R. Popovic´, "High-Precision Positioning of a Mechanism with Nonlinear Friction Using a Fuzzy Logic Pulse Controller," IEEE Transactions on Control Systems Technology, Vol. 8, No. 1, January 2000.
[5]C. Hsieh and Y. C. Pan, "Dynamic Behavior and Modeling of the Pre-Sliding Static Friction," Wear, 242, 1-17, 2000.
[6]Ting-Yung Lin, Yih-Chieh Pan and Chen Hsieh, "Precision-Limit Positioning of Direct Drive Systems with the Existence of Friction," Control Engineering Practice, 233-244, 2003.
[7]M. A. El-Sharkawi, "Adaptive Fuzzy Control of a Belt-Driven Precision Positioning Table," IEEE. Yonghong. Guo. Computational Intelligence Laboratory p1504-1506, 2003.
[8]C Yueyan, "A high-precision fuzzy control algorithm with self-regulating factor for trajectory tracking in virtual-axis polishing machine tool," IEEE Conference, Industrial Electronics Society, Busan, Korea, 2004.
[9]S. Bhattacharya, "A new self-tuned PID-type fuzzy controller as a combination of two-term controllers," ISA Transactions 43, 413-426, 2004.
[10]Castro, P.A.D. "Learning and Optimization of Fuzzy Rule Base by Means of Self-Adaptive Genetic Algorithm," Proc., IEEE Int. Conf. on Fuzzy Systems, Vol. 2, Budapest, Hungary, 1037–1042. 2004.
[11]Shahzad Khan and Asif Sabanovic, "Discrete-Time Sliding Mode Control of High Precision Linear Drive using Frictional Model," IEEE, 739-743, 2006.
[12]Chen Hsieh and Cang-Chin Yang, "Fast Nanometer Positioning of Heavy Loads Using a Hybrid Driver," Materials Science Forum Vol. 594 pp 235-240, 2008.
[13]Her-Terng Yau and Jun-Juh Yan, "Adaptive Sliding Mode Control of a High-Precision Ball-Screw-Driven Stage," Nonlinear Analysis: Real World Applications 10, 1480-1489, 2009.
[14]Shiuh-Jer Huang and Su-Shan Wang, "Mechatronics and Control of a Long-Range Nanometer Positioning Servomechanism," Mechatronics, 19, 14-28, 2009.
[15]M. M. Rashid, "Fuzzy-PID Hybrid Controller for Point-to-point (PTP) Positioning System," American Journal of Scientific Research ISSN 1450-223X Issue 9, pp.72-80, 2010.
[16]Basem M. Badr and Wahied. G. Ali, "Nanopositioning Fuzzy Control for Piezoelectric Actuators," International Journal of Engineering & Technology, IJET-IJENS, Vol:10, No:01, 70-74, 2010.
[17]林冠禎，"順滑模態控制器於高精度定位控制之應用"，國立成功大學航空太空研究所，碩士論文，2002。
[18]陳繹光，"適應性基因演算法與混合式模糊PID控制器於線性馬達之定位控制"，國立中山大學，碩士論文，2003。
[19]吳龍朋，"自走式氣浮平台之研製"，國立臺灣大學機械工程研究所，碩士論文，2007。
[20]蔡啟南，"具動態規劃的高階順滑模態控制於點對點定位系統的應用"，國立成功大學航空太空研究所，碩士論文，2009。
[21]廖家賢，"在伺服系統中摩擦力控制與補償之研究"，國立中央大學，博士論文，2009。
[22]孫宗瀛、楊英魁，"Fuzzy 控制：理論、實作與應用 修訂版"，全華科技圖書，2005。
[23]馮國臣，"模糊理論 基礎與應用"，新文京開發出版，2007。
[24]石辛民、郝整清，"模糊控制及其MATLAB仿真"，清華大學出版社，北京大學出版社，2008。