Center of Intelligent and Learning Systems Prof. Dong SHEN's Group College of Information Science and Technology, Beijing University of Chemical Technology |

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Graduate Courses

EE511, Adaptive Control, BUCT, Spring semester, since 2014-

In this course, the primary principle of two adaptive control methods are illustrated. The first is model reference adaptive control (MRAC) and the other one is self-tuning regulator (STR). The lecture notes for 2017 Spring course are listed as follows.

Lecture 1: Introduction

Lecture 2: Adaptive Control with all states

Lecture 3: Adaptive Control Using only Input-Output Measurements

Lecture 4: Adaptive Control Using only Input-Output Measurements: stability analysis

Lecture 5: Linear Parameter Estimation

Lecture 6: Self-tuning Minimum Variance Control

Final Exam Paper and Referential Solutions

EEE34400C, Principle of Automatic Control(II), BUCT, Fall semester, since 2014-

In this course, we brief the modern control theory, especially state space theory, sampled control theory, and nonlinear control. The lecture notes for 2018 Fall course are listed as follows.

Lecture 01: State Space Model for Linear Systems

Lecture 02: State Analysis for Linear Time-invariant Systems

Lecture 03: Controllability and Observability for Linear Time-invariant Systems

Lecture 04: State Feedback and Pole Assignment for Linear Systems

Lecture 05: State Observer

Lecture 06: Introduction to Sampled Control Systems

Lecture 07: Signal Sampling and Holding

Lecture 08: Z-transform of Sampled Signals

Lecture 09: Mathematical Model for Discrete-time Systems

Lecuter 10: Transforms among Different Models for Sampled Systems

Lecture 11: Performance Analysis of Sampled Systems

Lecture 12: Introduction to Nonlinear Control Systems

Lecture 13: Describing Function Method

Lecture 14: Phase-Plane Method

Lecture 15: Lyapunov Stability Theory

For 2018 Fall course (1601, 1602, 1603 in automation department), the followings are the scanned textbook.

Chapter 7: State Space-based Analysis and Design Methods (about 22 MB)

Chpater 7 attachment (about 7 MB)

Chapter 8: Samped Control Systems and Its Analysis (about 20 MB)

Chapter 8 attachement (about 3 MB)

Chapter 9: Nonlinear Control Systems (about 14 MB)

Chapter 9 attachment (about 4 MB)

Important: Course Exercises

Important: The following report includes selected mathematics results for your reference while learning the course. This report will be updated as the course proceeds.

Selected Mathematics Results in Automatic Control

The followings are notes for the 2018 seminar.

2018-10-16 Lecture Note 4

2018-10-09 Lecture Note 3

2018-09-25 Lecture Note 2

2018-09-18 Lecture Note 1

Important: The followings are Homeworks for the 2018 seminar.

2018-09-25-Homework 1 submitted before 2018-10-09

Solutions for Homework 1

2018-10-09-Homework 2 submitted before 2018-10-16

Solutions for Homework 2

2018-10-30-Homework 3 submitted before 2018-11-06

Solutions for Homework 3

2018-11-13-Homework 4 submitted before 2018-11-20

Solutions for Homework 4

2018-11-20 in class quiz

2018-12-04-Homework 5 submitted before 2018-12-11 NEW

Solutions for Homework 5

GST34220G, Introduction to Control and Optimization Algorithms Principle, BUCT, Spring semester, since 2017-

In this seminar, we aim to help the students to learn the design principles and techniques of the common control and optimization algorithms through subject discussions. The following subjects are included.

Lecture 1: Least Square Algorithm

Lecture 2: Kalman Filtering Algorithm

Lecture 3: Gradient Algorithm

Lecture 4: Stochastic Approximation Algorithm

Lecture 5: Genetic Algorithm

Lecture 6: Partical Swarm Optimization Algorithm

Lecture 7: Ant Colony Algorithm

Lecture 8: Artificial Fish Swarm Algorithm

CSE20000C, Literature Searching, BUCT, Fall 2012, Fall 2013

EEE34201T, Scientific Writing, BUCT, Fall 2012, Fall 2013