CDS 101, Lecture 1.129 Sep 03R. M. Murray, Caltech1CDS 101: Lecture 1.1Introduction to Feedback and ControlRichard M. Murray29 September 2003Goals:y Give an overview of CDS 101/110; describe course structure, administration y Define feedback/control systems and learn how to recognize main featuresy Describe what control systems do and the primary principles of controlReading (available on course web page): y Astrom and Murray, Analysis and Design of Feedback Systems, Ch 1y “For the Spy in the Sky, New Eyes”, NY Times, June 2002.29 Sep 03 R. M. Murray, Caltech CDS 2Course AdministrationCourse syllabusy CDS 101 vs CDS 110aby Lecturesy Gradingy Homework policyy Course text and referencesy Office hoursy Class homepagey Softwarey Course outliney Video tapes: 102 Steele, Box Gy Course load: keep track of hoursCDS 101, Lecture 1.129 Sep 03R. M. Murray, Caltech229 Sep 03 R. M. Murray, Caltech CDS 3CDS 101/110 Instructional StaffLecturer: Richard Murray (CDS)y Overall course managementCo-Instructorsy Michael Dickinson (BE/Bio)y Steven Low (CS/EE)y Hideo Mabuchi (Ph/CDS)y Doug MacMartin (CDS)Head TA: Lars Cremean (ME)y Coordinate course infrastructure, TAsTAsy Michael Reiser (BE)y Demetri Spanos (CDS)y Abhishek Tiwari (EE)y Stephen Waydo (CDS)Warning: objects in picture may be 10 years older than they appear.DickinsonMabuchi MacMartinLowCremeanMichael DemetriAbhishek Steve29 Sep 03 R. M. Murray, Caltech CDS 4Mud CardsMud cardsy 3 x 5 cards distributed at each lecturey Describe “muddiest” part of the lecturey Turn in cards at end of classy Responses posted on FAQ list by 8 pm on the day of the lecture (make sure to look!)Class FAQ listy Searchable database of responses to mud cards and other frequently asked questions in the classWhat does closed loopmean? You used this term without defining it.FAQCDS 101, Lecture 1.129 Sep 03R. M. Murray, Caltech329 Sep 03 R. M. Murray, Caltech CDS 5CDS 101/110/111 Course SequenceCDS 101 – Introduction to the principles and tools of control and feedbacky Summarize key concepts, w/ examples of fundamental principles at worky Introduce MATLAB-based tools for modeling, simulation, and analysisCDS 110a – Analytical understanding of key concepts in controly Detailed description of classical control and state space conceptsy Provide knowledge to work with control engineers in a team settingCDS 110b – Detailed design tools for control systemsy Estimation and robust control tools for synthesis of control lawsCDS 111 – Implementation of control systems for engineering applicationsy Lab-based implementation of computer control on physical systemsCDS Minor: CDS 110, CDS 140, Senior thesis or Ae/CDS 125FallWinter Spring29 Sep 03 R. M. Murray, Caltech CDS 6What is Feedback?Miriam Webster:the return to the input of a part of the output of a machine, system, or process (as for producing changes in an electronic circuit that improve performance or in an automatic control device that provide self-corrective action) [1920]Feedback = mutual interconnection of two (or more) systemsy System 1 affects system 2y System 2 affects system 1y Cause and effect is tricky; systems are mutually dependentFeedback is ubiquitous in natural and engineered systemsTerminologySystem 2System 1System 2System 1System 2System 1ClosedLoopOpenLoopCDS 101, Lecture 1.129 Sep 03R. M. Murray, Caltech429 Sep 03 R. M. Murray, Caltech CDS 7Example #1: Flyball Governor“Flyball” Governor (1788)y Regulate speed of steam engine y Reduce effects of variations in load (disturbance rejection)y Major advance of industrial revolutionBalls fly out as speed increases,Valve closes,slowing enginehttp://www.heeg.de/~roland/SteamEngine.htmlBoulton-Watt steam engineFlyballgovernorSteamengine29 Sep 03 R. M. Murray, Caltech CDS 8Other Examples of FeedbackBiological Systemsy Physiological regulation (homeostasis)y Bio-molecular regulatory networksEnvironmental Systemsy Microbial ecosystemsy Global carbon cycleFinancial Systemsy Markets and exchangesy Supply and service chainsESECDS 101, Lecture 1.129 Sep 03R. M. Murray, Caltech529 Sep 03 R. M. Murray, Caltech CDS 9Control = Sensing + Computation + ActuationSenseVehicle SpeedComputeControl “Law”ActuateGas PedalIn Feedback “Loop”Goalsy Stability: system maintains desired operating point (hold steady speed)y Performance: system responds rapidly to changes (accelerate to 65 mph)y Robustness: system tolerates perturbations in dynamics (mass, drag, etc)29 Sep 03 R. M. Murray, Caltech CDS 10Two Main Principles of ControlRobustness to Uncertainty through Feedbacky Feedback allows high performance in the presence of uncertaintyy Example: repeatable performance of amplifiers with 5X component variationy Key idea: accurate sensing to compare actual to desired, correction through computation and actuationDesign of Dynamics through Feedbacky Feedback allows the dynamics of a system to be modifiedy Example: stability augmentation for highly agile, unstable aircrafty Key idea: interconnection gives closed loop that modifies natural behaviorCDS 101, Lecture 1.129 Sep 03R. M. Murray, Caltech629 Sep 03 R. M. Murray, Caltech CDS 11Example #2: Cruise Controlengine hillengine des()mv bv u uukvv=− + +=−Control System++-disturbancereferenceStability/performancey Steady state velocity approaches desired velocity as k →∞y Smooth response; no overshoot or oscillationsDisturbance rejectiony Effect of disturbances (hills) approaches zero as k →∞Robustnessy Results don’t depend on the specific values of b, m, or k for k sufficientlylargess des hill1kvv ubk bk=+++timevelocityvdes→ 1 ask →∞→ 0 ask →∞“Bob”29 Sep 03 R. M. Murray, Caltech CDS 12Example #3: Insect FlightMore information:y M. D. Dickinson, Solving the mystery of insect flight, Scientific American, June 2001y CDS 101 seminar : Friday, 10 Oct 03ACTUATIONtwo wings(di-ptera)specialized“power”musclesSENSINGneuralsuperpositioneyeshind winggyroscopes(halteres)COMPUTATION~500,000 neuronsCDS 101, Lecture 1.129 Sep 03R. M. Murray, Caltech729 Sep 03 R. M. Murray, Caltech CDS 13Modern Engineering Applications of ControlFlight Control Systemsy Modern commercial and military aircraft are “fly by wire”y Autoland systems, unmanned aerial vehicles (UAVs) are already in placeRoboticsy High accuracy positioning for flexible manufacturingy Remote environments: space, sea, non-invasive surgery, etc.Chemical Process Controly Regulation of flow rates, temperature, concentrations, etc.y Long
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