Prof. SHEN's Group
Distributed Artificial Intelligence Laboratory, ERC-FCDE, MoE
School of Mathematics, Renmin University of China

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Graduate Courses

1113700120046 (D) 2113700120058 (M), Parallel Computation, 2021 Spring, RUC, Teach Bldg 4109, Thur. 11-13
Lecture 01: What is computation
Lecture 02: to be continued...

1xxxxx, Linear Systems, 2021 Fall, RUC, in preparation
Lecture 01: to be continued...
Lecture 02: to be continued...

Undergradute Courses

21012575, Freshman Seminar Course, 2021 Spring, RUC, Teach Bldg 2212, Mon. 7-8
Subject: Mathematics in Modern Information Technology
Lecture 01: Review of Mathematical Thinking
Lecture 02: to be continued...

21024231, Advanced Algebra II, 2021 Spring, RUC, Class 02, Qiushi 0324, Wed. 1-2 & Fri. 3-4
Lecture 01:
Lecture 02:

21022441, Advanced Algebra I, 2020 Fall, RUC, Class 03, Qiushi 0224, Wed. 1-2 & Fri. 3-4,
21021248, Advance Algebra II, 2020 Spring, RUC, Class 03, Qiushi 0324, Mon. 1-2 & Thur. 3-4, closed


Courses at Beijing University of Chemical Technology, closed

EE511, Adaptive Control, BUCT, Spring semester, 2014-2019, Graduate Course, closed
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 2019 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
       Material: Survey on Kalman-Yakuborich-Popov Lemma
       Material: Stability Analysis for the Case n^\star>1
Lecture 5: Least Square Estimation

Lecture 6: Self-tuning Minimum Variance Control 

EEE34400C, Principle of Automatic Control(II), BUCT, Fall semester, 2014-2018, Undergraduate Course, closed
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

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)