模型預測控制(Model Predictive Control)是一種以受控體模型為基礎的進階控制技術，其概念是以受控體之預測模型為基礎，採用即時計算二次最佳化性能指標和回授修正的策略，以克服受控對象之建模誤差、未知結構參數與外界環境等不確定因素的影響，有效地彌補一般控制理論面對複雜受控對象所無法處理之處，也改善了無窮時域最佳控制只適用在非時變系統的不足。
本研究旨在探討模型預測控制策略，及提出一相關控制參數設計流程，並應用於雙線性馬達同動系統，透過模型預測控制處理多變數系統的優勢，提出一應用模型預測控制之整合型同動控制架構。此方式能交互回授各軸之輸出資訊，且統整了每軸之迴路控制器，以達到控制上之耦合，並藉由模型預測控制之移動時域(Receding Horizon)最佳化，克服了一般有限時域最佳控制無法即時且連續計算之問題，即時地對系統不同步之行為進行補償，有效降低同動誤差，達到協調各軸運動及提升系統同步性能之效果。實驗結果顯示，不論雙線性馬達間是否存在耦合機構，本整合型同動控制架構皆能有效降低雙軸之同動誤差，尤其在高速(700mm/sec)運行時，更可明顯改善雙馬達運動不同步之現象。

Model Predictive Control (MPC) is a popular method for the control of industrial process systems such as chemical plants and oil refineries since the 1980s. The basic concept of MPC is to solve an on-line optimization problem to compute the optimal control input sequence over a finite future. The main characteristic is that only the first element of the control sequence is implemented as the current input in the repeated calculation. Hence, it is more suitable for time-varying systems than conventional infinite horizon control.
Therefore, this thesis proposes an integrated control scheme which is applied to the synchronous control of a twin linear servo system by utilizing MPC for its superiority to deal with multivariable systems. The proposed method can control the movement of each axis based on the information of the other axes to eliminate the asynchronous behavior of two linear motors. The experimental results demonstrate that the proposed control scheme can reduce the synchronization error effectively with/without a coupled mechanism between the linear motors, particularly at high speed movement (700mm/sec).

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