本論文主要探討參數空間中使用粒子群之最佳化與輻狀基底函數類神經網路演算法之最佳化PID控制系統。首先使用穩定邊界作圖法，定義出在已知微分增益或時間延遲下對應的穩定比例與積分增益值，接著使用粒子群最佳化演算法，求取在穩定空間中的最佳PID控制器之參數。為了讓該參數群組間產生關連性，於是更進一步地使用輻狀基底函數類神經網路演算法，將求取的參數群組作為訓練資料，求取出在已知微分增益或時間延遲之下，相對應輸出之比例與積分增益值，而達到調整控制器參數之目的。

整數階系統模擬部分以水平式風力發電葉槳控制系統為主，使用兩個例子來說明。分別改善發電經由動態調整輸入轉矩達到輸出穩定功率輸出，以及解決動態調整輸入風力葉片之葉槳角度，進而達到降低風機塔柱的疲勞負荷。

分數階系統模擬部分，則選用了含特定時間延遲之分數階控制系統為主體，同樣地提出兩個例子來說明。分別解決了衛星系統姿態控制問題，及降低具有時間延遲的分數階系統穩態誤差。
在實驗驗證方面，本論文選用無刷直流馬達系統。首先利用系統鑑別法，獲取此無刷直流馬達的系統轉移函式，再根據此數學模型結合所提出之方法，於數位訊號處理器上進行不同的時延參數之最佳PI控制器參數設計，並在馬達系統上完成驗證，獲致較佳的時域響應結果。

The main goal of this study is to find the optimal control parameters based on the stochastic inertia weight particle swarm optimization (SIWPSO) and radial basis function neural network (RBFNN) algorithm. First, a graphical approach is used to determine the stability region and set the parameters of the proportional integral derivative (PID) controller to achieve an arbitrary-order time delay system. Then, the SIWPSO algorithm is used to find the optimal control parameters from the stability region. To obtain the fitness curve for the optimal control parameters from the results of the SIWPSO algorithm, the RBFNN algorithm is applied to optimize the operating curve of the PID control parameters.

This study presents two cases of integer order PID (IOPID) control systems for horizontal-axis wind turbines. The first case is the power control problem in the drive train control of the wind turbine system. The second case is the fore-aft modal deflection control problem of the pitch angle controller for the wind turbine system.

Then, this study presents two cases of fractional order PID (FOPID) control systems with time delay. The first case is the attitude control of a bias-momentum satellite. The second case is a fractional order control system with time delay.

To emphasize that the SIWPSO-RBFNN method can be implemented in real systems, a digital signal processor (DSP) system is used to verify the reliability of the proposed method. The transfer function model, which is obtained from a brushless direct current (BLDC) motor, is used in the integer order proportional-integral (IOPI) controller design with time delay. The results of the simulations and experiments indicate that the proposed method, which finds the optimal IOPI control gains, has good time responses in different time delay conditions.

Contents
論文審定書 i
論文公開授權書 ii
致謝 iii
摘要 iv
Abstract v
Contents vii
List of Figures ix
List of Tables xii
Chapter 1 Introduction 1
1.1 Motivation 1
1.2 Paper Review 2
1.3 Organization of the Dissertation 8
Chapter 2 A Brief Review of Methods 9
2.1 Stability Analysis of PID Control Systems 9
2.2 Particle Swarm Optimization (PSO) Algorithm 13
2.3 Radial Basis Function Neural Network (RBFNN) Algorithm 16
Chapter 3 Design of IOPID Control Systems with SIWPSO-RBFNN 20
3.1 Brief Introduction of Wind Turbine Systems 20
3.2 Design Procedures 26
3.3 Simulation Results 27
Chapter 4 Design of FOPID Control Systems with SIWPSO-RBFNN 35
4.1 Brief Introduction of Fractional Order Control Systems 35
4.2 Design Procedures 36
4.3 Simulation Results 41
Chapter 5 PI Controller Design for BLDC Motor Using SIWPSO-RBFNN 53
5.1 Brief Introduction to DSP-based Control System 53
5.2 Platform of DSP-based Control System 54
5.3 System Identification 57
5.4 Design Procedures 60
5.5 Results and Discussion 61
Chapter 6 Conclusions and Future Works 71
6.1 Conclusions 71
6.2 Future Works 72
References 73

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