本研究利用前饋（Feedforward）、反饋（Feedback）和複合（Hybrid）三種架構實現耳機的主動式噪音控制。
第一步是由電聲模型設計前饋、反饋控制器，模擬演算法的效果和可實現性。第二步是建立實際的耳機模型，使電聲模型更為精確。
在控制器的部分，前饋和反饋分開設計。其中前饋使用模型匹配（Model Matching）的方法，由外耳麥克風接收噪音，經過控制器處理後產生其反向波形在耳機內和噪音互相抵消，達到噪音降低的效果。而反饋則用最佳化控制中的線性二次高斯控制（Linear Quadratic Gaussian Control），其設計受到二次成本函數的限制，可自行調配出最想要的結果。複合則是將兩者的結構串接，使得噪音控制的效果更大。
最後以DSP用不同種類的噪音測試此控制方法的效果，可在200~2kHz頻段中降低噪音10~15dB。

This research mainly focuses on the implement of three structures which includes feedforward, feedback and hybrid applied to active noise control of headset.
First design the feedback and feedforward controllers with electroacoustic model and simulate the effect and realizability of the algorithm. The second step is to establish the actual headset model to make electroacoustic model more accurate.
In the part of the controllers, we design the feedback and feedforward controllers separately. In feedforward, model matching method is applied. Noise from the external-ear microphone is processed by the controller to produce its reverse waveform to cancel itself in the headset which can achieve noise reduction. In feedback, we use linear quadratic Gaussian control, one of the most optimal control. Its design is constrained by the quadratic cost function. We can adjust the parameters for the most desired result. Hybrid concatenates the two structures above to enhance the effect of noise control.
At last, DSP is applied to test the noise reduction effect with different kinds of noise. It can reduce 10-15dB broadband noise in 200-2kHz.

摘要 1
ABSTRACT 4
TABLE OF CONTENTS 5
LIST OF FIGURES 8
Chapter 1 INTRODUCTION 13
Chapter 2 LINEAR QUADRATIC GAUSSIAN (LQG) CONTROL 18
2.1 Linear Quadratic Regulator (LQR) 18
2.2 Linear Quadratic Estimator (LQE) 21
Chapter 3 EMA ANALOGOUS CIRCUITS WITH TS PARAMETER 23
3.1 Mechanical System 23
3.2 Acoustic System 25
3.3 The Electroacoustic Analysis of the Headset System 28
3.4 The Electroacoustic Analysis of the Headset System with Disturbance 30
Chapter 4 ADAPTIVE FILTER 36
4.1 Adaptive Systems 36
4.2 Adaptive Algorithms 38
4.3 Least-Mean-Squares (LMS) Algorithm 39
4.4 Normalized Least-Mean-Squares (NLMS) Algorithm 41
Chapter 5 REAL HEADSET SYSTEM IDENTIFICATION 43
5.1 Measurement of Electrical and Mechanic Electroacoustic Parameters 43
5.2 The Verification of the Electroacoustic Analysis 44
5.3 System Identification by Adaptive Filter 45
5.4 Eigensystem Realization Algorithm (ERA) 46
Chapter 6 FEEDFORWARD CONTROLLER DESIGN 64
6.1 The Model Matching 64
6.2 The Filtered-X NLMS Algorithm 68
Chapter 7 MULTIRATE SIGNAL PROCESSING 77
7.1 Multirate Signal Processing Theory 77
7.2 The Simulation of Multirate Signal Processing 79
Chapter 8 FEEDBACK CONTROLLER DESIGN AND THE HYBRID STRUCTURE 90
8.1 Feedback Controller Design 90
8.2 The Hybrid Structure 92
Chapter 9 DSP IMPLEMENTATION 103
Chapter 10 CONCLUSIONS 116
REFERENCES 117

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