跟踪问题或稳定问题的非线性系统是困难的，尤其是当不是所有的国家都可用。本研究提出的约束H∞和回路传递恢复（LTR）通过T-S模糊模型来控制非线性系 - 近系统的组合。一，高木 - 关野模糊模型被用来代表一个非线性系统。接着，基于模糊模型，卡尔曼滤波器被显影。控制器增益是通过使用约束H∞理论计算。 LTR，然后应用到加强了控制器的鲁棒性。模拟结果应用到两连杆机器人系统是数字高程模型了证实。所设计的系统的性能进行评估的频域，并通过时域仿真。仿真结果表明，亲提出的方法更适用于实际执行

Tracking problems or stabilization problems for nonlinear systems are difficult, especially when not all the state are available. This study proposed a combination of constrained H∞ and loop transfer recovery (LTR) to control nonli-near systems via Takagi-Sugeno fuzzy model. First, the Takagi-Sugeno fuzzy model is employed to represent a nonlinear system. Next, based on the fuzzy model, a Kalman filter is developed. The controller gain is calculated by using constrained H∞ theory. LTR is then applied to reinforce the robust property of the controller. Simulation results for application to a two-link robot system are dem-onstrated. The performance of the designed system is assessed in the frequency domain and via the time-domain simulation. The simulation shows that the pro-posed method is more applicable in practical implementation.

COVER i
ABSTRACT ii
ACKNOWLEDGMENT iii
CONTENTS iv
LIST OF FIGURES v
CHAPTER I INTRODUCTION 1
1.1 Background 1
1.2 Organization of the Thesis 3
CHAPTER II BASIC THEORY 4
2.1 Takagi Sugeno Fuzzy Model 4
2.2 Continous-Time T-S Controllers and Closed-Loop Stability 5
2.3 Loop Transfer Recovery 6
CHAPTER III FUZZY CONSTRAINED H∞/LTR CONTROL DESIGN 11
3.1 Introduction 11
3.2 Problem Statement 11
3.3 Fuzzy Constrained H∞/LTR Control Design 14
CHAPTER IV SIMULATION RESULT 23
CHAPTER V CONCLUSION AND FUTURE WORKS 42
5.1 Conclusion 42
5.2 Future Works 42
BIBLIOGRAPHY 43

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