對於改善生產力及品質而言，機械手臂的精密運動控制是重要的。然而，機械手臂為多變數非線性動態系統，其數學模式難以建立。因此，難以設計以模式為基礎的控制器，以控制機械手臂系統。有鑑於此，本研究使用模式自由的模糊控制器以控制機械手臂系統，以達到精密運動控制的目的。但是，傳統模糊控制器有著尋找模糊控制規則及選擇適當的隸屬函數之困難。此外，傳統模糊控制器的控制規則一旦設定以後，模糊控制規則即是固定的，其不能根據系統響應及期望的控制性能做即時的調整。為了改善上述的問題，本研究發展自組織模糊控制器，以評估機械手臂系統之精密運動控制的控制性能。在控制的過程中，自組織模糊控制器不斷地更新學習策略。其規則表能夠從零初始模擬規則開始，如此不僅克服傳統模糊控制器設計的困難，而且建立合適的模糊規則，方便模糊控制器在機械手臂系統控制之實際地應用。為了驗證所提出智慧型控制器的可用性，本研究改裝一臺舊式機械手臂控制系統以評估精密運動控制的可行性。實驗結果證實，自組織模糊控制器在減少關節空間軌跡追蹤誤差上比傳統模糊控制器有較佳的控制性能。

The precise motion control of robotic manipulators is important in improving productivity and quality. However, robotic manipulators are multivariable nonlinear dynamic systems. Designing a model-based controller for robotic system control is difficult because its mathematical model is hard to establish. Hence, this study employed a model-free fuzzy controller to control the robotic system in order to achieve precise motion control. Nevertheless, the design of the traditional fuzzy controller (TFC) presents difficulties in finding control rules and selecting an appropriate membership function. Moreover, the database and fuzzy rules of a TFC are fixed after the design step and then cannot appropriately regulate them real time according to the system output response and the desired control performance. To solve the above problem, this work develops a self-organizing fuzzy controller (SOFC) for precise motion control to evaluate control performance of the robotic system. The SOFC continually updates the learning strategy in the form of fuzzy rules, during the control process. The fuzzy rule table of this SOFC can be begun with zero initial fuzzy rules which not only overcome the difficulty in the TFC design, but also establish a suitable fuzzy rules table, and support practically convenient fuzzy controller applications in robotic systems control. To confirm the applicability of the proposed intelligent controllers, this work retrofitted an old robot for a control system to evaluate the feasibility of precise motion control. The SOFC has better control performance in reducing the tracing errors of the joint-space trajectory than does the TFC, as verified in experimental results.