本研究針對自主水面無人載具設計一套具備控制力分配與致動器建模功能之控制架構。針對水下噴水推進器所具備之可旋轉特性與非線性輸出行為，本研究將推力與方向角，建立推力配置矩陣並導入具輸出限制條件之最佳化控制分配方法，使用拉格朗日乘數法求解各致動器命令，以提升控制輸出之可實現性與容錯彈性。
在致動器建模方面，本研究利用徑向基底函數（RBF）神經網路進行系統鑑別，分別建構轉速與推力、電壓與轉速之間的非線性對應模型，使控制命令得以經由連續映射，準確轉換為實體驅動輸出。反映致動器之真實響應，有助於提升整體系統的實作穩定性。
控制系統整合包含岸端遙控模組、導航感測、電源與致動控制，支援自主與手動雙模式切換，並由中央控制單元統籌各模組運作。透過模擬操作中對致動器輸出命令是否落於限制範圍內、以及載具狀態是否準確追蹤控制目標之觀察，進一步驗證所提控制分配設計的整體可行性。

This study presents a control architecture for autonomous unmanned surface vehicles (AUSVs), featuring control allocation and actuator modeling capabilities. The system is developed based on a three-degree-of-freedom (3-DOF) dynamic model. To address the directional flexibility and nonlinear output characteristics of waterjet propulsion units, this work decouples thrust magnitude and steering angle, constructs a thrust configuration matrix, and introduces an output-constrained optimal control allocation strategy. Actuator commands are derived using the Lagrange multiplier method to enhance feasibility and fault tolerance of control outputs. For actuator modeling, a radial basis function (RBF) neural network is adopted for system identification. The network captures the nonlinear relationships between rotational speed and thrust, as well as between voltage and speed, allowing control commands to be accurately mapped to physical actuator outputs through continuous transformation. This approach reflects the real behavior of the actuators and improves the robustness of the overall system implementation. The integrated control system includes shore-based remote operation, navigation sensing, power distribution, and actuator control modules, supporting both autonomous and manual modes. A centralized control unit coordinates all subsystems. The feasibility of the proposed control allocation design is verified through simulation by examining whether actuator commands remain within constrained bounds and whether the vehicle accurately tracks the intended control objectives.

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