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Discrete Feedback Systems 2.
Modern Control
Maximum Likelihood Estimation (MLE)
Tartalomjegyzék
- DISCRETE FEEDBACK SYSTEMS II. Modern Control
- COPYRIGHT PAGE
- 1. Introduction
- PART I – State-Space Methods
- 2. State-Space Analysis
- 3. State Estimation and Kalman filtering
- 4. Model predictive control
- Part II – System Identification
- 5. System identification
- 5.1. Models of Linear Time-Invariant Systems
- 5.2. Nonparametric Techniques
- 5.3. Least Squares (LS) Parameter Estimation
- 5.4. Maximum Likelihood and Bayesian Estimation
- 5.5. The Prediction Error Parameter Estimation Approach
- 5.6. Instrumental Variable Approach
- 5.7. Subspace Identification Methods
- 5.8. Model Structure Selection and Model Validation
- 5. System identification
- Appendix
- A. Appendix
- Basic notations
- A.1 Basic facts
- A.2 Elements of Probability Theory
- A.3 System connections
- A.4 The set of all stabilizing controllers
- A.5 Continuous Time (CT) systems: an overview
- A.6 Lyapunov Stability
- A.7 Discrete Euler-Lagrange Equation
- A.8 Discrete Maximum Principle
- A.9 Dynamic Programming
- A.10 The Multivariate Gaussian
- A.11 Optimal Estimation
- A.12 Constrained Optimization for MPC
- A.13 Multi-Parametric Programming
- Basic notations
- A. Appendix
- Bibliography
Kiadó: Akadémiai Kiadó
Online megjelenés éve: 2019
ISBN: 978 963 454 373 2
The classical control theory and methods that we have been presented in the first volume are based on a simple input-output description of the plant, expressed as a transfer function, limiting the design to single-input single-output systems and allowing only limited control of the closed-loop behaviour when feedback control is used. Typically, the need to use modern linear control arises when working with models which are complex, multiple input multiple output, or when optimization of performance is a concern. Modern control theory revolves around the so-called state-space description. The state variable representation of dynamic systems is the basis of different and very direct approaches applicable to the analysis and design of a wide range of practical control problems. To complete the design workflow, finally some introduction into system identification theory is given.
Hivatkozás: https://mersz.hu/gaspar-szabo-bokor-discrete-feedback-systems-2//
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