0. 1 About system identification
0.2 Application and Development of System Identification
0.3 About adaptive control
0.4 Application and Development of Adaptive Control System
1 Theory, method and application of partial system identification
1 Chapter Basic Concepts of System Identification
1. 1 Basic principles of system identification
Mathematical model of 1.2 system description
Description and analysis of 1.3 random signal
1.4 white noise and pseudo-random code
1.5 steps and contents of system identification
Basic application of 1.6 system identification
The second chapter is the classical method of system identification.
2. 1 step response system identification
2.2 Frequency response method system identification
2.3 Association analysis system identification
Chapter 3 Least Square Algorithm for System Identification
3. 1 least squares principle
3.2 Recursive algorithm of least squares estimation
3.3 slow time-varying parameter least squares recursive algorithm
3.4 Generalized Least Squares Method
3.5 auxiliary variable method
3.6 Joint estimation of parameters and states
3.7 Least Square Identification of Multivariable Systems
Chapter four: random approximation method, maximum likelihood method and prediction error method of system identification.
4. 1 System Identification and Training Stochastic Approximation (SAA)
4.2 Maximum Likelihood Method (ML) for System Identification
4.3 Prediction Error Method (PE) for System Identification
Chapter 5 Structure Identification of Digital Model
5. 1 Estimate the order of the model according to the Hangel moment.
5.2 Estimate the order of the model according to the product moment matrix.
5.3 Estimate the order of the model according to the sum of squares of residuals.
5.4 Estimate the membership degree of the model according to the information standard.
Chapter 6 Identification of Closed-loop System
6. 1 identifiability of closed-loop system
6.2 Closed-loop identification method and identifiable conditions
6.3 Application of Least Square Method and Auxiliary Variable Method in Closed-loop Identification
Chapter 7: The development of system identification and its application in production practice.
7. 1 fuzzy relation model identification and application
7.2 Fault detection and prediction using identification technology
7.3 Self-tuning Predictor
The second part is adaptive control
Chapter 8 Introduction of Adaptive Control
8. 1 What is an adaptive control system?
8.2 Why do you need adaptive control
8.3 Adaptive Control Scheme
8.4 Design and theoretical problems of adaptive control
Chapter 9 Model Reference Adaptive Control
9. 1 model reference adaptive control
9.2 Design method based on local parameter optimization theory
9.3 Design a model reference adaptive control system based on Lyapunov stability theory.
Chapter 10 self-adjusting control (1)
10. 1 Overview of self-tuning control
10.2 single-step output predictive self-tuning control
10.3 control weighted self-tuning control
Chapter 1 1 Self-tuning Control (2)
1 1. 1 pole configuration self-tuning control
1 1.2 self-tuning PID control
1 1.3 expert self-tuning PID controller
1 1.4 generalized predictive control
Chapter 12 multivariable self-tuning control
12. 1 multivariable self-tuning regulator
12.2 multivariable self-tuning controller
12.3 multivariable pole assignment self-tuning controller
Self-tuning decoupling control of 12.4 multivariable system
13 development and application of adaptive control system
13. 1 development of adaptive control technology
13.2 weighted generalized predictive self-tuning control for industrial boilers
Self-tuning intelligent pole assignment internal model control for 13.3 large time-delay systems
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