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控制原理與設計期中報告 指導教授:曾慶耀 學 號: 10167030 學 生:楊長諺.  Introduction  System Modeling of the PMAC Motor  Neural - Network - Based Self - Tuning PI Control System.

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Presentation on theme: "控制原理與設計期中報告 指導教授:曾慶耀 學 號: 10167030 學 生:楊長諺.  Introduction  System Modeling of the PMAC Motor  Neural - Network - Based Self - Tuning PI Control System."— Presentation transcript:

1 控制原理與設計期中報告 指導教授:曾慶耀 學 號: 學 生:楊長諺

2  Introduction  System Modeling of the PMAC Motor  Neural - Network - Based Self - Tuning PI Control System for PMAC Motors  Experiments and Discussions  Conclusion

3  PI control schemes  The artificial neural network technique

4 A-1. Electrical Governing Equation:

5 A-2. Mechanical Governing Equation:

6 B. Neural-Network-Based Friction Model

7 C. Complete Model of the PMAC Motor

8

9 D. PMAC Motor PI Control

10 A. Controller Structure

11 B. NNPT Training k 1 =100 k 2 =5 k 3 =100

12 C. System Integration

13 D. Computer Simulations 1) Self-Tuning PI Control versus Fixed-Gain PI Control:

14 2)Self-Tuning PI Control versus Gain-Scheduling PI Control:

15

16  Neural-Network-Based Self-Tuning PI Control:

17

18

19  Neural-Network-Based Self-Tuning PI versus Fixed- Gain

20  In this paper, a new neural-network-based self-tuning PI controller design method was proposed to increase the robustness of the conventional fixed-gain PI control scheme.  a well-trained neural network supplies the PI controller with suitable gain according to each feedback operating condition pair (torque, angular velocity, position error).


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