An adaptive supervisory sliding fuzzy cerebellar model articulation controller for sensorless vector-controlled
Shun-Yuan Wang1, Chwan-Lu Tseng2, Shou-Chuang Lin3
1Department of Electrical Engineering, National Taipei University of Technology, No. 1, Sec. 3, Chung-Hsiao E. Rd., Taipei 10608, Taiwan. sywang@ntut.edu.tw.
Sensors (Basel, Switzerland)
|March 28, 2015
Summary
A novel adaptive supervisory sliding fuzzy cerebellar model articulation controller (FCMAC) significantly enhances induction motor drive performance in speed sensorless vector control. This intelligent controller improves system responsiveness and reduces errors compared to other advanced control schemes.
Area of Science:
- Electrical Engineering
- Control Systems
- Artificial Intelligence
Background:
- Induction motors (IM) are crucial in industrial applications, requiring precise speed control.
- Sensorless vector control eliminates the need for speed sensors, reducing cost and complexity.
- Existing control methods may face challenges with steady-state errors and responsiveness.
Purpose of the Study:
- To implement and evaluate an adaptive supervisory sliding fuzzy cerebellar model articulation controller (FCMAC) for speed sensorless vector control of induction motors.
- To compare the performance of the proposed controller against other intelligent control schemes.
- To demonstrate the effectiveness of the integrated supervisory controller, integral sliding surface, and adaptive FCMAC.
Main Methods:
- Development of an adaptive supervisory sliding FCMAC integrating a supervisory controller, integral sliding surface, and adaptive FCMAC.
- Application of the Lyapunov approach for controller design, ensuring learning-error convergence.
- Experimental validation of the proposed controller against adaptive sliding FCMAC and adaptive sliding CMAC in a sensorless vector-controlled IM drive system.
Main Results:
- The adaptive supervisory sliding FCMAC demonstrated superior performance in the sensorless vector control of induction motors.
- The integral sliding surface effectively minimized steady-state errors and improved system response.
- The proposed controller significantly outperformed adaptive sliding FCMAC and adaptive sliding CMAC, as evidenced by lower Root Mean Square Error (RMSE).
Conclusions:
- The adaptive supervisory sliding FCMAC is a highly effective intelligent control strategy for speed sensorless vector-controlled induction motor drives.
- The controller's architecture, combining supervisory control with an integral sliding surface and adaptive FCMAC, leads to enhanced system dynamics and accuracy.
- This approach offers a robust solution for improving the performance of induction motor drives in demanding applications.
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