Identification of continuous-time systems using digital signal processing techniques ディジタル信号処理手法による連続系の同定に関する研究
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著者
書誌事項
- タイトル
-
Identification of continuous-time systems using digital signal processing techniques
- タイトル別名
-
ディジタル信号処理手法による連続系の同定に関する研究
- 著者名
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楊, 子江
- 著者別名
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ヨウ, シコウ
- 学位授与大学
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九州大学
- 取得学位
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工学博士
- 学位授与番号
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甲第2937号
- 学位授与年月日
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1992-03-27
注記・抄録
博士論文
1 Introduction 2 Reexamination of the Integral-Equation Approach to Identification of Continuous-Time Systems 3 A Unified Approach to Identification of Continuous-Time Systems Using Digital Low-Pass Filters 4 Recursive Identification Algorithms for Continuous-Time Systems Using an Adaptive Procedure 5 Identification in the Presence of Input-Output Measurement Noises Using Bias-Compensated Least-Squares Method 6 Identification in the Presence of Input-Output Measurement Noises Using Bias-Compensated Instrumental Variable Method 7 Parameter Identification of Distributed Parameter Systems in the Presence of Measurement Noise 8 Implementation of Multi-Rate Model Reference Adaptive Control for Continuous-Time Systems 9 Conclusion
主1-参1
システム情報_電気工学（？）
目次
- Contents / p1 (0003.jp2)
- Preface and Acknowledgements / p5 (0007.jp2)
- Abbreviations / p7 (0009.jp2)
- 1 Introduction / p1 (0010.jp2)
- 2 Reexamination of the Integral-Equation Approach to Identification of Continuous-Time Systems / p10 (0019.jp2)
- 2.1 Introduction / p10 (0019.jp2)
- 2.2 Briefview of the integral-equation approach / p11 (0020.jp2)
- 2.3 New integral-equation aooroach / p14 (0023.jp2)
- 2.4 Effects of the measurement noise / p17 (0026.jp2)
- 2.5 Illustrative example / p18 (0027.jp2)
- 2.6 Conclusion / p22 (0031.jp2)
- 3 A Unified Approach to Identification of Continuous-Time Systems Using Digital Low-Pass Filters / p23 (0032.jp2)
- 3.1 Introduction / p23 (0032.jp2)
- 3.2 Statement of the problem / p25 (0034.jp2)
- 3.3 Approximated discrete-time estimation models / p26 (0035.jp2)
- 3.4 Recursive identification algorithms / p32 (0041.jp2)
- 3.5 Illustrative example / p37 (0046.jp2)
- 3.6 Unification of the other methods / p41 (0050.jp2)
- 3.7 Discussions on the problem of the initial conditions / p47 (0056.jp2)
- 3.8 Conclusion / p52 (0061.jp2)
- 4 Recursive Identification Algorithms for Continuous-Time Systems Using an Adaptive Procedure / p53 (0062.jp2)
- 4.1 Introduction / p53 (0062.jp2)
- 4.2 Estimation model / p55 (0064.jp2)
- 4.3 Estimation methods / p57 (0066.jp2)
- 4.4 Recursive estimation algorithms / p63 (0072.jp2)
- 4.5 Implementation of the algorithms / p66 (0075.jp2)
- 4.6 Illustrative examples / p68 (0077.jp2)
- 4.7 Conclusion / p82 (0091.jp2)
- 5 Identification in the Presence of Input-Output Measurement Noises Using Bias-Compensated Least-Squares Method / p83 (0092.jp2)
- 5.1 Introduction / p83 (0092.jp2)
- 5.2 Statement of the problem / p85 (0094.jp2)
- 5.3 Discrete-time estimation models / p85 (0094.jp2)
- 5.4 LS method and its bias / p87 (0096.jp2)
- 5.5 BCLS method / p91 (0100.jp2)
- 5.6 Estimation of [数式] and [数式] / p97 (0106.jp2)
- 5.7 Implementation of the algorithm / p100 (0109.jp2)
- 5.8 Illustrative examples / p103 (0112.jp2)
- 5.9 Conclusion / p109 (0118.jp2)
- 6 Identification in the Presence of Input-Output Measurement Noises Using Bias-Compensated Instrumental Variable Method / p110 (0119.jp2)
- 6.1 Introduction / p110 (0119.jp2)
- 6.2 Statement of the problem / p111 (0120.jp2)
- 6.3 IV method and its bias / p112 (0121.jp2)
- 6.4 BCIV method / p116 (0125.jp2)
- 6.5 Estimation of [数式] / p118 (0127.jp2)
- 6.6 Implementation of the algorithm / p119 (0128.jp2)
- 6.7 Illustrative examples / p122 (0131.jp2)
- 6.8 Conclusion / p130 (0139.jp2)
- 7 Parameter Identification of Distributed Parameter Systems in the Presence of Measurement Noise / p131 (0140.jp2)
- 7.1 Introduction / p131 (0140.jp2)
- 7.2 Estimation model / p133 (0142.jp2)
- 7.3 Estimation methods / p135 (0144.jp2)
- 7.4 Illustrative examples / p139 (0148.jp2)
- 7.5 Conclusion / p144 (0153.jp2)
- 8 Implementation of Multi-Rate Model Reference Adaptive Control for Continuous-Time Systems / p145 (0154.jp2)
- 8.1 Introduction / p145 (0154.jp2)
- 8.2 Brief review of bilinear transformation,delta operator and BPFs / p147 (0156.jp2)
- 8.3 Relation between the BPF model and the ZOH sampled model / p151 (0160.jp2)
- 8.4 Basic design of the indirect MRACS / p154 (0163.jp2)
- 8.5 Digital implementation of the algorithm / p156 (0165.jp2)
- 8.6 Numerical examples / p160 (0169.jp2)
- 8.7 Conclusion / p171 (0180.jp2)
- 9 Conclusion / p172 (0181.jp2)
- References / p176 (0185.jp2)