Dan O. Popa, Linear Systems EE 3417, Fall 2015 EE 3417: Linear Systems Continuous Signals and Systems Lectures: Tue/Thu, 12:30-1:50 pm, NH 229 Instructor: Dan Popa, Ph.D., Associate Professor, EE Course TAs: Rommel Alonzo, Yathartha Tulhadar Lab/Recitation Section for EE 3417 students, Tue/Thu 11:00- 12:20, 2:00-3:20 – ELAB 256 Instructor Office hours: Tue/Thu 9:30-11 am NH543 Course info: http://www.uta.edu/faculty/popa/linsys Grading policy: Grading criteria: on curve based on class average, generally >80% will be an A, 60-80% B, 50-60% C, 30-50% D, <30% F. 6 Homeworks – 20% Midterm 1 (in-class) – 20% Midterm 2 (take-home) – 20% 6 Quizzes – 20% Final (in-class) – 20%
28
Embed
Dan O. Popa, Linear Systems EE 3417, Fall 2015 EE 3417 : Linear Systems Continuous Signals and Systems Lectures: Tue/Thu, 12:30-1:50 pm, NH 229 Instructor:
This document is posted to help you gain knowledge. Please leave a comment to let me know what you think about it! Share it to your friends and learn new things together.
Transcript
Dan O. Popa, Linear Systems EE 3417, Fall 2015
EE 3417: Linear SystemsContinuous Signals and Systems
Lectures: Tue/Thu, 12:30-1:50 pm, NH 229 Instructor: Dan Popa, Ph.D., Associate Professor, EECourse TAs: Rommel Alonzo, Yathartha TulhadarLab/Recitation Section for EE 3417 students, Tue/Thu 11:00-12:20, 2:00-
3:20 – ELAB 256Instructor Office hours: Tue/Thu 9:30-11 am NH543Course info: http://www.uta.edu/faculty/popa/linsys Grading policy:
Grading criteria: on curve based on class average, generally>80% will be an A, 60-80% B, 50-60% C, 30-50% D, <30% F.
– Homeworks: 6 Homeworks contain both written and/or computer simulations using MATLAB. Submit code to TA’s if it is part of the assignments.
– Reading Assignments: After each course. The assigned reading material is given out in order to make you better understand the concepts. Materials from the reading assignments may be part of course exams.
– Examinations: Midterm 1(in-class), Midterm 2 (take-home), 6 quizzes (at lab for EE 3417) and one final (in-class).
– EE 3417 students – LAB session in ELAB 256, Tue/Thu, covers – problems (recitation), MATLAB and SIMULINK, LABVIEW
– In rare circumstances (medical emergencies) exams may be retaken and assignments can be resubmitted without penalty.
– Missed deadlines for take-home exams and homeworks: Maximum grade drops 25% per late day.
Dan O. Popa, Linear Systems EE 3417, Fall 2015
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. Discussing 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 exam. 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 difficult. Assignments, lecture notes, and other materials re going to be posted here, however, due to the pace of the lectures, copying someone else's notes may be an unreliable way of making up an absence. You are responsible for all material covered in class regardless of absences.
Dan O. Popa, Linear Systems EE 3417, Fall 2015
Textbooks & Description• Textbook:
– B.P. Lathi, Linear Systems and Signals, 2nd ed. (required), Oxford Press, ISBN-13: 978-0-19-515833-5.
• Other materials (on library reserve)– Student Edition of MATLAB Version 5 for Windows by Mathworks, Mathworks Staff,
MathWorks Inc.– R.D. Strum, D.E. Kirk, Contemporary Linear Systems using MATLAB, PWS Publishing,
• Catalog description: – EE 3317. LINEAR SYSTEMS (3-0) For non-electrical engineering majors. Time-domain
transient analysis, convolution, Fourier Series and Transforms, Laplace Transforms and applications, transfer functions, signal flow diagrams, Bode plots, stability criteria, and sampling. Classes meet concurrently with EE 3417.
– EE 3417 CONTINUOUS SIGNALS AND SYSTEMS (3-3) Time-domain transient analysis, convolution, state-space analysis, frequency domain analysis, Laplace transforms and transfer functions, signal flow and block diagrams, Bode plots, stability criteria, Fourier series and transforms. Applications from control systems and signal processing. Problems and numerical examples using MATLAB will be covered during recitation and computer laboratory sessions.
Dan O. Popa, Linear Systems EE 3417, Fall 2015
Description & Prerequisites• This is an introductory signal and systems course. It presents a broad
overview of continuous linear systems concepts and techniques, and focuses on fundamentals such as time-domain and frequency domain analysis, stability, and discretization (sampling).
• The course material is divided between several areas:– Signals and systems: classification, manipulation, modeling– Continuous time-domain analysis of systems– Continuous frequency domain analysis of systems– Sampling and Fourier analysis of signals– Programming excercises using MATLAB
• ME Majors Prerequisite: Grade C or better in MATH 3330, ME Majors Corequisite: EE 2320 or equivalent. BE Majors Prerequisite: Grade C or better in MATH 3319.
• EE 3417 prerequisite: Grade C or better in both EE 2347 and EE 2415.
Dan O. Popa, Linear Systems EE 3417, Fall 2015
Tentative Course SchedulePart 1: Introduction and Systems Analysis in the time domain• Week 1 - August 27, Lecture 1
– Introduction to signals and systems, syllabus and examples.
• Week 2 - Sept 1, 3 Lectures 2,3 – Review of basics: Matrix and vector algebra, complex numbers, integrals and series.
(Background), MATLAB programming– Homework #1 handed out on Sept 1
• Week 3 - Sept 8, 10, Lectures 4,5 – Signals: classification, operations, standard signals (Chapter 1)– Operations: Time Shifting, Scale, Reversal– Classification: analog, digital, periodic, aperiodic, finite, infinite, causal, anticausal, energy and
power signals, deterministic and stochastic.– Measures: Power, Energy– Signal spaces
Tentative Course SchedulePart 1: Introduction and Systems Analysis in the time domain• Week 5 - Sept 22, 24, Lectures 8, 9
– Quiz 2 @ Lab : Systems Sept 22– Time domain analysis of systems: (Chapter 2)– Differential equations and solutions– Response: zero input, impulse response
• Week 6 - Sept 29, Oct 1, Lectures 10, 11– Time domain analysis of systems: (Chapter 2)– Convolution integral– Response: zero state– Stability: internal/external– Intuitive insights into system behavior– Homework #2 due Sept 29, Homework #3 handed out
• Week 7 - Oct 6, 8, Lectures 12, 13 – Quiz 3 @ Lab: Time Domain I/O Analysis of Systems, Oct 6– State space analysis of systems: (Chapter 10)
• State equations, Time domain and solutions• System realizations
– Review list for Midterm 1
• Week 8 - Oct 13, 15, Lectures 14, 15– Homework #3 due Oct 13, – In-class Midterm on Oct 13: covers: basic signals, systems, time-domain analysis.
Dan O. Popa, Linear Systems EE 3417, Fall 2015
Tentative Course SchedulePart 2: System Analysis in Frequency Domain• Week 8 - Oct 13, 15, Lectures 14, 15
– Homework #4 handed out Oct 15– Frequency domain analysis of systems: (Chapter 4)
• Laplace transform
• Week 9 - Oct 20, 22, Lectures 16, 17 – Quiz 4 @ Lab: Laplace transforms Oct 22– Frequency domain analysis of systems: (Chapter 4)
• Properties and use of Laplace transform • Transfer functions and block diagrams • Frequency response - Bode plots
• Week 10 - Oct 27, 29, Lectures 18, 19– Homework #4 due Oct 29 , Homework #5 handed out– Frequency domain analysis of systems:
• Application to feedback control• Applications to filter design
• Week 11 - Nov. 3, 5 Lectures 20, 21– State space analysis of systems: (Chapter 10)
• Frequency Domain Solutions
– Midterm II (Take-home) handed out Nov 5, covers frequency domain.– Homework #5 due Nov. 5
Dan O. Popa, Linear Systems EE 3417, Fall 2015
Tentative Course SchedulePart 2: System Analysis in Frequency Domain• Week 12 - Nov. 10, 12 Lectures 22, 23
– Midterm #2 due Nov. 10 in class. Midterm 2 grades will be returned only by appointment (see instructions).
– Homework #6 handed out on Nov. 10– Fourier analysis of signals (Chapter 6)
• For weeks 1,2 – Read Preface, and Background section of Textbook
• Purpose of weekly assigned 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.
Dan O. Popa, Linear Systems EE 3417, Fall 2015
Research in Multiscale Robotics and Systems – Next Gen Systems (NGS)
Robotics
Control Systems
Manufacturing & Automation
Established Technologies Emerging Technologies
Micromanufacturing
Microrobotics
Microassembly
Micropackaging
Sensors & Actuators
NanoManufacturing
Microsystems & MEMS
Nanotechnology
Biotechnology
Small-scale Robotics & Manufacturing
Modeling & Simulation
Control Theory
Algorithms
Tools and Fundamentals
Sensor networks
Surgical robotics
Human-like robots
Distributed systems
New applicationsfor small-scale systems
Dan O. Popa, Linear Systems EE 3417, Fall 2015
Micro-Robotics at Next Gen Systems (NGS)
05/05/11 14
Mobility
Challenge
Micro
Assembly
Event
Vibration
Actuated
Laser
Actuated
Dan O. Popa, Linear Systems EE 3417, Fall 2015
“Manufacturable” microrobot families at NGS
04/19/23 15
Copter
quad rotor
Pede
Microcrawler
Blimp
Microballoon
Family of Microrobots made by assembly and 3D die/wafer stacking
Cover (handle)
Cover (device)
Actuator (handle)
ChannelsO/P Port (+x)
O/P Port (-x) Actuator (device)
Dan O. Popa, Linear Systems EE 3417, Fall 2015
Human Robot Interaction Research @ NGS
16
Dan O. Popa, Linear Systems EE 3417, Fall 2015
Lecture 1: Intro to Linear Signals and Systems
• What are linear systems and why is it important to study 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 transients settle)– Double the amplitude in, double the amplitude out (when initial state
conditions are zero)
Dan O. Popa, Linear Systems EE 3417, Fall 2015
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, or 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
Dan O. Popa, Linear Systems EE 3417, Fall 2015
Types of Models
• White Box – derived from first principles laws: physical,
– Control of dynamical systems• Feedback control, prediction/estimation/identification of systems, robotics,
micro and nano systems
Dan O. Popa, Linear Systems EE 3417, Fall 2015
Linear vs. Nonlinear
• Why study 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 reasonably well, for nonlinear systems as well
– If you don’t understand linear dynamical systems you certainly can’t understand nonlinear systems
Dan O. Popa, Linear Systems EE 3417, Fall 2015
LTI Models
• Continuous-time linear dynamical system (LDSC) has the form
dx/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 state (vector)– u(t) Rm is the input or control– y(t) Rp is the output
Dan O. Popa, Linear Systems EE 3417, Fall 2015
Linear Systems in Practice
• most linear systems encountered are time-invariant: A, B, C, D are constant, i.e., don’t depend on t– Examples: second-order electromechanical systems with constant
coefficients
• when there is no input u (hence, 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
Dan O. Popa, Linear Systems EE 3417, Fall 2015
Week 1, Lectures 1-2: ReviewThese lectures cover math concepts related to:
- White Box Systems Examples: RLC circuit, MSD mechanical system
- 1st order ODE equations – solving- Review of Taylor series, derivation, integration- Complex numbers and examples, rings and fields- Rational polynomials fractions and partial fraction
expansions- Vectors and matrices, vector spaces, linear mappings- Systems of linear equations
- Example exercises:- B.1, B.2: polar to cartesian, cartesian to polar conversion- B.3, B.4: multiplication/division and addition/subtraction of complex