Robust Estimation and Failure Detection

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Robust Estimation and Failure Detection

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Robust Estimation and Failure Detection

  • 品牌: Unbranded

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14天退货政策

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描述

Robust Estimation and Failure Detection

1 Introduction. - 2 Estimation and Failure Detection: An Overview. - 2. 1 Introduction. - 2. 2 Ever Since Wiener. - 2. 3 Failure Detection and Isolation. - 2. 4 Summary. - 3 Discrete-Time Robust Estimation. - 3. 1 Introduction. - 3. 2 Plants with an Uncertain Noise Model. - 3. 3 Plants with Uncertain Dynamics and Noise Model. - 3. 4 Extension to Steady State. - 3. 5 Robust Fixed-Interval Smoothing. - 3. 6 Numerical Examples. - 3. 7 Related Work. - 4 Stochastic Interpretation of Robust Estimation: Risk Sensitivity. - 4. 1 Introduction. - 4. 2 The Risk Sensitive Optimal Estimation Problem. - 4. 3 Extension to Systems with Modeling Uncertainty. - 4. 4 Numerical Comparison of Error Density Functions. - 4. 5 Summary. - 5 Robust Failure Detection and Isolation. - 5. 1 Introduction. - 5. 2 Problem Description. - 5. 3 A Likelihood Ratio Test with Robustness Properties. - 5. 4 Likelihood Ratio Tests and Plant Uncertainties. - 5. 5 FDI with Robustness to Failure Mode Noise and Plant Uncertainties. - 5. 6 Summary. - 6 Two Applications. - 6. 1 Introduction. - 6. 2 Application to an Underwater Vehicle. - 6. 3 Application to Reentry Vehicle attitude Control Systems. - A The Kalman Filter. - A. 1 Problem Description. - A. 2 The One-Step Predictor. - A. 3 Measurement Update and the Filtered Estimate. - A. 4 Gaussian Disturbance. - A. 5 The Innovation Process. - A. 6 Linear Time-Invariant Systems. - A. 7 The Wiener Filter. - A. 8 Smoothing. - A. 8. 1 Fixed-Interval Smoothing. - A. 8. 2 Fixed-Point and Fixed-Lag Smoothing. - A. 9 The Extended Kaiman Filter (EKF). - A. 10 Summary of Equations and Additional Remarks. - B Outputs of Linear Systems and Their Quadratic Forms. - B. 1 Moments of Linear Systems Outputs. - B. 2 Probability Density Functions of Gaussian Quadratic Forms. - C Continuous-Time Robust Estimation. - C. 1 Introduction. - C. 2 Problem Formulation. - C. 3 Derivation of the Estimator. - C. 4 Related Work. - D Application Data. - D. 1 Underwater Vehicle Application. - D. 1. 1 The Plant. - D. 1. 2 Description of Robust Filter Design. - D. 2 Reentry Vehicle Application. - D. 2. 1 The Plant. - D. 2. 2 The Filters. Language: English
  • 品牌: Unbranded
  • 类别: 教育
  • 语言: English
  • 出版日期: 2012/03/22
  • 艺术家: Rami S. Mangoubi
  • 页数: 222
  • 出版社/标签: Springer
  • 格式: Paperback
  • Fruugo ID: 337866136-741525388
  • ISBN: 9781447115885

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