30220363 (Automatic Control Systems)

Course Name: Automatic Control Systems

Course Number: 30220363

Program: Undergraduate program

Type: Required

Credits: 3

Term Offered: Fall

Prerequisite(s): Signal Processing, Linear Algebra, Physics, Differential Equations

Instructor(s): Chen Shen


Pengsheng Su and Lianwei Jiao. Principles of Automatic Control, Electronic Industry Press, 2003. (in Chinese)


Benjamin C Kuo. Automatic Control Systems (7th edition), John Wiley & Sons, Inc., 1995

Richard C DorF and Robert H Bishop. Modern Control Systems (8th edition), Addison Wesley Longman, Inc., 1998

Granham C Goodwin, Stefan F Graebe and Mario E Salgado. Control System Design, Tsinghua University Press, Pretice Hall, Inc., 2002

Katsuhiko Ogata. Modern Control Engineering (4th edition), Pretice Hall, Inc., 2002

Gene F Franklin, David J Powell and Micheal L Workman. Digital Control of Dynamic Systems (3rd edition), Tsinghua University Press, Addison Wesley Longman, Inc., 2001


Course Description:

This course introduces basic concepts, terminologies, methods and theories of control engineering for linear time invariant systems. It covers basic analysis and synthesis approaches in classical control, modern control and digital control theories. Methods in different control theories pertaining to modeling, stability assessment, steady-state error calculation, transient performance analysis and controller design are detailed.


Course Objectives and Outcomes:

Numbers in brackets are linked to department educational outcomes

1.Students should skillfully master the methods for analyzing and synthesizing simple linear time-invariant systems. [1, 2]

2.Students should be familiar with a certain number of terminologies in control engineering, which will be used repeatedly in the successive learning and studying. [5]

3.Students should be familiar with various ideas in control engineering, e.g. equivalent transform perspective, abstract perspective, and engineering approximation perspective [3, 5, 11]


Course Topics:

1.Characteristics of a linear time-invariant system, how to linearize a nonlinear system;

2.How to build up mathematical models for linear systems in different mathematical forms, such as differential equations, transfer functions and  state-space equations;

3.Grasp different graphical representations of a LTI system, such as block diagram, signal flow graph (SFG), state diagram;

4.How to use Mason formula to derive the transfer function between the input and output of a system represented by a SFG;

5.Definition of Lyapunov stability and Bounded-Input Bounded-Output stability; conditions for system to be stable in terms of different stability definitions;

6.Concepts of steady response and transient response; performance indices for evaluating the two kinds of response;

7.Steady-state error of a system, using Laplace final-value theorem to calculation the error; Formulas to calculate transient performance indices;

8.Routh-Hurwitz criterion, how to construct the Routh table for a system and how to handle exceptions in construction;

9.What is root locus? Rules for sketching root loci of a control system;

10.Methods of using root loci to design controllers;

11.Concepts about frequency response, frequency analysis; Learn how to express the frequency response of a system in polar plot;

12.Understand concept of encirclement, enclosure, understand principle of argument;

13.Master the concept of Nyquist path, Nyquist plot and Nyquist criterion; know how to use Nyquist criterion to assess the stability of a system;

14.Concepts of Bode plot, know how to draw Bode plot for a system; performance indices in frequency domain;

15.Concepts of Minimum-phase system, phase margin and gain margin;

16.Controller design using frequency domain method, mainly the Bode plot;

17.Concepts of controllability and observability, methods to evaluate the controllability and observability of a system;

18.Understand the idea of state feedback control, master undetermined coefficient method to design feedback gains;

19.Learn the concept of dynamic expansion; master the method of introducing error as a new state variable, then design a state feedback controller to improve control precision;

20.Concept of observer, know how to design an observer, know how to design a state feedback controller with a state observer.

21.Know the difference between a continuous control system and a discrete-date control system, grasp the mathematical description of ideal sampler and zero-order-hold;

22.Understand z-transformation; know how to calculate the pulse transfer function of a digital control system;

23.Comparison of analysis methods between continuous control systems and digital control systems in classical control theory;

24.Modern control theory for discrete control systems, such as discrete state equations, controllability and observability;

25.Be able to design simple digital controllers either directly using discrete-date controller design methods or using continuous controller design method then discretize it.



l  Generator Excitation System Modeling and Compensation

 Understand the function of a generator excitation system, setup mathematical model for the generator and its excitation system, sketch root loci for the whole system and assess its stability and calculate its steady-state error, design a compensator to make the output voltage of the generator errorless, use Matlab simulink toolbox to verify the design.


Course Assessment:

  Homework measures, 15 points.

  Pop quiz measures, 15 points.

  Comprehensive training project measures, 10 points.

  Final exam score, 60 points.