本研究目的提出與傳統控制架構相異之高效能運動控制架構, 是一種效果加
乘之控制架構概念, 控制架構以PID 為基底加入類神經網路、前饋摩擦模型與反
覆控制, 本研究實現控制架構於線性壓電陶瓷馬達平台之運動控制, 達到精密定
位功能。控制架構的建立為提出一個概念性的高效能運動控制架構並根據系統特
性進行補償, 我們藉此作為控制線性壓電陶瓷馬達平台的運動控制。本研究首先
依據系統特性, 我們使用PID 控制作一個全域性的控制, 其次, 我們使用智慧型
控制中的類神經控制器控制系統不確定項。再者, 我們建立系統摩擦模型進行摩
擦補償並對系統所要追蹤的週期訊號使用反覆控制可以進一步改善PID控制所無
法降低的週期誤差並透過控制器加乘的概念達到改善系統效能。實驗部分, 我們
首先探討各單獨的控制器與前饋摩擦模型控制器組合的結果作比較, 最後, 本研
究依據本文中所提出的架構結合前饋摩擦模型補償平台的摩擦力, 透過軌跡追蹤
的運動控制中, 經由實驗驗證能確實的提升控制器效能。

Linear Piezoelectric Ceramic Motors (LPCM) have been recognized as one kind of useful actuators in recent mechatronics and automation industries. Due to their dominant nonlinear effects such as friction and hysteresis, controller design for LPCM has become a challenging task for researchers. The current literature related to motion control of LPCM shows that the designers mostly suffer from either complicated friction modeling for compensation or numerous parameters tuning by using intelligent control algorithms. Following the idea of “add-ons” controller design, this thesis proposes a novel hybrid control structure, comprising of PID control, repetitive control, and neural network adaptive control, to achieve high performance and easy maintainability for motion control of LPCM. The experimental results on tracking motion control of a LPCM demonstrate the effectiveness of the proposed method. Moreover, the study also adds a LuGre friction model based feedforward compensator to the hybrid controller for comparison purposes and further performance improvement. Biaxial motion control experiments are finally provided to justify the applicability of this method.

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