近年來服務型機器人之產品需求日與遽增，而關節馬達為服務型機器人之重要關鍵零組件，其應用於機器手臂與足型結構。關節馬達之控制模式複雜，需動態調整控制策略，以適應不同肢體方位和外加負載之變化。有鑑於此，本論文提出一考量動態負載之適應性機器人關節控制器研究。本研究分為兩部分進行，第一部分以傳統PID位置控制方法進行關節馬達控制器之開發，實作上除了以dsPic實現控制器之外，亦以一具12自由度之雙足人形機器人進行步行測試，以驗證此一控制器之有效性。第二部分考量以S曲線進行關節馬達之速度規劃，以控制關節馬達於規劃速度時間內完成角度位移目標值。此外，為了適應不同馬達部位負載差異以及外加負載之變化，本研究以模糊理論針對速度誤差與速度誤差變化量為考量因子，進行動態比例增益以及微分增益之調整，以適應負載之變化。此一部分以Matlab Simulink建構馬達以及負載模型，並以不同負載干擾進行測試
，以驗證本文所提出之控制方法。實驗結果顯示動態比例增益之調整改善了傳統固定比例增益以及微分增益之速度響應，並大幅降低因突然外加負載之震盪幅度以及影響時間。

Demand of service robots is fast increasing in recent years. Joint motors are key components of service robots, and they are usually applied to manipulators and biped robots. Joint motor control systems are complicated, because they have to adjust their control gains according to the changes of unpredictable loads. Therefore, this study develops an adaptive robotic joint motor controller with dynamic load interventions. This thesis is organized as two parts. The first part realizes a dsPic based proportional–integral–derivative (PID) controller to deal with position servo controls of DC motors. At the same time, twelve PID controllers are connected via half-duplex serial communications to control a twelve degree-of-freedom (DOF) biped humanoid robot. Successful walking experiments demonstrated the effectiveness of the proposed PID joint motor controller. The second part is to control the joint motor based on the S-curve velocity planning approach so that the joint motor may achieve a desired angular position within a given time. In order to deal with load variations from different limb postures and external load interventions, a fuzzy logic based adaptive control gain generator is developed according to the factors of velocity errors and velocity error variations. Therefore, the proportional and derivative gains are capable of self-adjustments with respect to load changes. The fuzzy logic control system is modeled and evaluated using the Matlab Simulink. Finally, several load intervention conditions are examined based on the proposed controller. Simulation results demonstrated the proposed fuzzy controller reduces the amplitudes and time of oscillations with respect to load variations when compared to fixed control gain conditions.

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