机器人系列EE4314 Control .ppt

1、EE 4314: Control Systems,Lectures:Tue/Thu, 2:00-3:20, NH 106 Instructor: Dan Popa, Ph.D., Associate Professor, EE Office hours: Tue/Thu 11:30 pm 1:30 pm, NH 543, or by appointment.Course TAs: Isura Ranatunga, M. Rashid Pac Course info: http:/www.uta.edu/faculty/popa/control Grading policy:6 Homework

2、s 20%6 Labs 20%Midterm I (in-class) 20%Midterm II (take-home) 20%Final (in-class) 20% Grading criteria: on curve based on class average,Syllabus,Assignments: Homeworks contain both written and/or computer simulations using MATLAB. Submit code to the TAs if it is part of the assignments. Lab sessions

3、 are scheduled in advance, bi-weekly, so that the TAs can be in the lab (NH 250). While the lab session is carried out in a group, the Lab report is your own individual assignment. Reading Assignments: After each course, the assigned reading material wil help you better understand the concepts. Mate

4、rials from the reading assignments may also be part of course exams. Examinations: Three exams (midterms, final), in class or take home. In rare circumstances (medical emergencies, for instance) exams may be retaken and assignments can be resubmitted without penalty. Missed deadlines for take-home e

5、xams and homeworks: Maximum grade drops 15% per late day (every 24 hours late).,Honor Code,Academic Dishonesty will not be tolerated. All homeworks and exams are individual assignments. Discussing homework assignments with your classmates is encouraged, but the turned-in work must be yours. Discussi

6、ng exams with classmates is not allowed. Your take-home exams and homeworks will be carefully scrutinized to ensure a fair grade for everyone.Random quizzes on turned-in work: Every student will be required to answer quizzes in person at least twice during the semester for homework and take home exa

7、m. You will receive invitations to stop by during office hours. Credit for turned in work may be rescinded for lack of familiarity with your submissions.Attendance and Drop Policy: Attendance is not mandatory but highly encouraged. If you skip classes, you will find the homework and exams much more

8、difficult. Assignments, lecture notes, and other materials re going to be posted here, however, due to the pace of the lectures, copying someone elses notes may be an unreliable way of making up an absence. You are responsible for all material covered in class regardless of absences.,Textbooks & Des

9、cription,Textbook: G.F. Franklin, J.D. Powell, A. Emami-Naeni, Feedback Control of Dynamic Systems, 6th edition, Pearson Education, 2009, ISBN: 978-0-136019-69-5 Other materials (on library reserve) Student Edition of MATLAB Version 5 for Windows by Mathworks, Mathworks Staff, MathWorks Inc. O. Beuc

10、her, M. Weeks, Introduction to Matlab & Simulink, A project approach, 3-rd ed., Infinity Science Press, 2006, ISBN: 978-1-934015-04-9 B.W. Dickinson, Systems: Analysis, Design and Computation, Prentice Hall, 1991, ISBN: 0-13-338047-5. R.C. Dorf, R.H. Bishop, Modern Control Systems, 10th ed., Pearson

11、 Prentice Hall, 2005, ISBN: 0-13-145733-0 K. Ogata, Modern Control Engineering, 5-th ed, 2010, Pearson Prentice Hall ISBN13:9780136156734, ISBN10:0136156738 Catalog description: Catalog description: EE 4314. CONTROL SYSTEMS (3-0) Analyses of closed loop systems using frequency response, root locus,

12、and state variable techniques. System design based on analytic and computer methods. This is an introductory control systems course. It presents a broad overview of control techniques for continuous and discrete linear systems, and focuses on fundamentals such as modeling and identification of syste

13、ms in frequency and state-space domains, stability analysis, graphical and analytical controller design methods. The course material is divided between several areas: Control Systems: classification, modeling, and identification Basics of Feedback: performance and stability Control Design Methods: f

14、requency domain, state-space Programming excercises using MATLAB and Simulink Laboratory experiments,Tentative Course Schedule,Part 1: Introduction to systems & system modelingWeek 1 - January 18, 20, Lectures 1,2 Introduction to feedback control systems and brief history Review of basics: Matrix an

15、d vector algebra, complex numbers, integrals and series, Differential equations and linear systems Homework #1 handed out on January 20 Week 2 - January 25, 27, Lectures 3,4 Online material Dynamic Models: examples of circuits and mechatronic systems. MATLAB Programming Week 3 - Feb 1, 3, Lectures 5

16、,6 Dynamic Models: examples of circults and thermo-fluidic systems Block diagrams Lab #1: Matlab and Simulink Hands on Lab Session,Tentative Course Schedule,Part 2: Feedback and Its Time Domain AnalysisWeek 4 - Feb 8, 10, Lectures 7,8 Stability System Identification: first order systems Basic Proper

17、ties of Feedback: Sensitivity Homework #1 due Feb 10, Homework #2 handed out Week 5 - Feb 15, 17, Lectures 9, 10 Basic Properties of Feedback: Steady state errors 2nd order system response, system type Lab #1 Due Feb 17, Lab #2: Identificaton of a Transfer Function Week 6 - Feb 22, 24, Lectures 11,

18、12 State-space system intro State-space system controller design Homework #2 due Feb 24 , Homework #3 handed out Week 7 - March 1,3, Lectures 13, 14 Lab #2 Due March 3,Lab #3: Identificaton of a State-Space Model Full-state feedback, Ackermans Formula Estimator design. Week 8 - March 8, 10, Lectures

19、 15, 16 Optimal control Linear Quadratic Regulation. In-class Midterm I on March 10, covers: system modeling, basic feedback, and state-space methods. Midterm study guide Homework #3 due on March 10, Homework #4 handed out,Tentative Course Schedule,Part 3: Feedback and Design Methods in Frequency Do

20、main Week 9 - March 15,17, Spring Break Week 10 - March 22, 24 Lectures 17, 18 PID control Root-locus design method Lab #3 due, Lab #4: Speed Motor Control using PID Week 11 - March 29, 31, Lectures 19, 20 Root-locus design method Homework #4 due on March 29, Homework #5 handed out. Week 12 - April

21、5, 7, Lectures 21, 22 Frequency-Response design method Lab #4 due, Lab #5: LQR Controller Week 13 - April 12, 14 Lectures 23, 24 More on PM, GM Homework #5 due April 12 Midterm II (Take Home), posted April 12, due April 19, covers frequency domain techniques,Tentative Course Schedule,Part 4: Digital

22、 ControlWeek 14 - April 19, 21, Lectures 25, 26 Digital Control Homework #6 handed out Lab #6: Digital Control Week 15 - April 26, 28, Lectures 27, 28 Digital Control Lab #5 due Week 16 - May 4, 6, Lectures 29, 30 Course recap and exam preparation Lab #6 due May 6 Homework #6 due May 6 Week 17 - May

23、 10 Final exam (in-class) (comprehensive) in class, no calculator Bring a 5-page, double-sided cheat sheet, handwriting only,Course Objectives,Students should be familiar with the following topics: Modeling of physical dynamic systems Block diagrams Specifications of feedback system performance Stea

24、dy-state performance of feedback systems Stability of feedback systems Root-locus method of feedback system design Frequency-response methods Nyquists criterion of feedback loop stability Design using classical compensators State variable feedback,Textbook Reading and Review,Course Refresher: Math:

25、complex numbers, matrix algebra, vectors and trigonometry, differential equations. Programming: MATLAB & Simulink EE 3317, 3318 For weeks 1 & 2 Read Chapter 1, Appendices A, B, C of Texbook Read History of Feedback Control by Frank Lewis http:/arri.uta.edu/acs/history.htm Purpose of weekly assigned

26、textbook readings To solidify concepts To go through additional examples To expose yourselves to different perspectives Reading is required. Problems or questions on exams might cover reading material not covered in class.,Signals and Systems,What are linear systems and why is it important to study

27、them? Signal: Conventional Electrical or Optical signals Any time dependent physical quantity System: Object in which input signals interact to produce output signals. Static vs dynamic systems Fundamental properties that make it predictable: Sinusoid in, sinusoid out of same frequency (when transie

28、nts settle) Double the amplitude in, double the amplitude out (when initial state conditions are zero),System Modeling,Building mathematical models based on observed data, or other insight for the system. Parametric models (analytical): ODE, PDE Non-parametric models: ex: graphical models - plots, o

29、r look-up tables. Mental models Ex. Driving a car and using the cause-effect knowledge Simulation models ex: Many interconnect subroutines, objects in video game,Types of Models,White Box derived from first principles laws: physical, chemical, biological, economical, etc. Examples: RLC circuits, MSD

30、 mechanical models (electromechanical system models). Black Box model is entirely derived from measured data Example: regression (data fit) Gray Box combination of the two,White Box vs Black Box Models,This course deals with both white and black models which are linear,Linear vs. Nonlinear,Why study

31、 continuous linear analysis of signals and systems when many systems are nonlinear in practice? Basis for digital signals and systems Many dynamical systems are nonlinear but some techniques for analysis of nonlinear systems are based on linear methods Methods for linear systems often work reasonabl

32、y well, for nonlinear systems as well If you dont understand linear dynamical systems you certainly cant understand nonlinear systems,LTI Models,Continuous-time linear dynamical system (LDSC) has the formdx/dt= A(t)x(t) + B(t)u(t), y(t) = C(t)x(t) + D(t)u(t) where: t R denotes time x(t) Rn is the st

33、ate (vector) u(t) Rm is the input or control y(t) Rp is the output,Linear Systems in Practice,most linear systems encountered are time-invariant: A, B, C, D are constant, i.e., dont depend on t Examples: second-order electromechanical systems with constant coefficients when there is no input u (henc

34、e, no B or D) system is called autonomous Examples: filters, uncontrolled systems when u(t) and y(t) are scalar, system is called single-input, single-output (SISO) when input & output signal dimensions are more than one, MIMO Example: Aircraft MIMO,Linear System Description in Frequency Domain,Auto

35、matic Control,Control: process of making a system variable converge to a reference value If ref_value=constant - servo (tracking control) If ref_value=changing - regulation (stabilization) Open Loop vs. closed loop control,Feedback System Block Diagram,Feedback System Block Diagram,Temperature contr

36、ol system,Feedback System Block Diagrams,Automobile Cruise Control,Brief History of Feedback Control,The key developments in the history of mankind that affected the progress of feedback control were:1. The preoccupation of the Greeks and Arabs with keeping accurate track of time. This represents a

37、period from about 300 BC to about 1200 AD. (Primitive period of AC) 2. The Industrial Revolution in Europe, and its roots that can be traced back into the 1600s. (Primitive period of AC) 3. The beginning of mass communication and the First and Second World Wars. (1910 to 1945). (Classical Period of

38、AC) 4. The beginning of the space/computer age in 1957. (Modern Period of AC).,Primitive Period of AC,Float Valve for tank level regulators Drebbel incubator furnace control (1620) (antiquity),Primitive Period of AC,James Watt Fly-Ball GovernorFor regulating steam engine speed(late 1700s),Classical

39、Period of AC,Stability Analysis: Maxwell, Routh, Hurwitz, Lyapunov (before 1900). Electronic Feedback Amplifiers with Gain for long distance communications (Black, 1927) Stability analysis in frequency domain using Nyquist criterion (1932), Bode Plots (1945). PID controller (Callender, 1936) servome

40、chanism control Root Locus (Evans, 1948) aircraft control Most of the advances were done in Frequency Domain.,Modern Period of AC,Time domain analysis (state-space) Bellmann, Kalman: linear systems (1960) Pontryagin: Nonlinear systems (1960) IFAC Optimal controls H-infinity control (Doyle, Francis,

41、1980s) loop shaping (in frequency domain). MATLAB (1980s to present) has implemented math behind most control methods.,MATLAB Exercises,Run the following MATLAB demos: Type “demo” at the MATLAB prompt Watch “Getting Started” Videos Run as many Simulink Demos as you can. For each one: Double click all the model boxes and look inside Try to modify parameters which make sense to you and see their effects by running the model.,