Scalar control synthesis 1

Similar documents
CDS 101/110a: Lecture 8-1 Frequency Domain Design

Loop Design. Chapter Introduction

CDS 101/110: Lecture 8.2 PID Control

CDS 101/110a: Lecture 8-1 Frequency Domain Design. Frequency Domain Performance Specifications

Lecture 10. Lab next week: Agenda: Control design fundamentals. Proportional Control Proportional-Integral Control

Välkomna till TSRT15 Reglerteknik Föreläsning 8

CDS 101/110: Lecture 10-2 Loop Shaping Design Example. Richard M. Murray 2 December 2015

Servo Tuning. Dr. Rohan Munasinghe Department. of Electronic and Telecommunication Engineering University of Moratuwa. Thanks to Dr.

Andrea Zanchettin Automatic Control 1 AUTOMATIC CONTROL. Andrea M. Zanchettin, PhD Spring Semester, Linear control systems design

Chapter 4 PID Design Example

Advanced Servo Tuning

MTE 360 Automatic Control Systems University of Waterloo, Department of Mechanical & Mechatronics Engineering

CDS 101/110: Lecture 9.1 Frequency DomainLoop Shaping

(1) Identify individual entries in a Control Loop Diagram. (2) Sketch Bode Plots by hand (when we could have used a computer

This manuscript was the basis for the article A Refresher Course in Control Theory printed in Machine Design, September 9, 1999.

Application Note #2442

of harmonic cancellation algorithms The internal model principle enable precision motion control Dynamic control

Andrea Zanchettin Automatic Control 1 AUTOMATIC CONTROL. Andrea M. Zanchettin, PhD Winter Semester, Linear control systems design Part 1

Classical Control Design Guidelines & Tools (L10.2) Transfer Functions

Control Design for Servomechanisms July 2005, Glasgow Detailed Training Course Agenda

Lecture 9. Lab 16 System Identification (2 nd or 2 sessions) Lab 17 Proportional Control

Laboratory PID Tuning Based On Frequency Response Analysis. 2. be able to evaluate system performance for empirical tuning method;

Linear Control Systems Lectures #5 - PID Controller. Guillaume Drion Academic year

Glossary of terms. Short explanation

Load Observer and Tuning Basics

Latest Control Technology in Inverters and Servo Systems

Chapter 5 Frequency-domain design

Elmo HARmonica Hands-on Tuning Guide

Active Vibration Isolation of an Unbalanced Machine Tool Spindle

Automatic Control Motion control Advanced control techniques

ME451: Control Systems. Course roadmap

Fundamentals of Servo Motion Control

Tutorial on IMCTUNE Software

ADJUSTING SERVO DRIVE COMPENSATION George W. Younkin, P.E. Life Fellow IEEE Industrial Controls Research, Inc. Fond du Lac, Wisconsin

A Machine Tool Controller using Cascaded Servo Loops and Multiple Feedback Sensors per Axis

Feedback (and control) systems

Procidia Control Solutions Dead Time Compensation

EE 482 : CONTROL SYSTEMS Lab Manual

Modified ultimate cycle method relay auto-tuning

TRACK-FOLLOWING CONTROLLER FOR HARD DISK DRIVE ACTUATOR USING QUANTITATIVE FEEDBACK THEORY

Design and Implementation of the Control System for a 2 khz Rotary Fast Tool Servo

Gain From Using One of Process Control's Emerging Tools: Power Spectrum

Structure Specified Robust H Loop Shaping Control of a MIMO Electro-hydraulic Servo System using Particle Swarm Optimization

EES42042 Fundamental of Control Systems Bode Plots

GE420 Laboratory Assignment 8 Positioning Control of a Motor Using PD, PID, and Hybrid Control

An Introduction to Proportional- Integral-Derivative (PID) Controllers

Robust Haptic Teleoperation of a Mobile Manipulation Platform

EC CONTROL SYSTEMS ENGINEERING

Testing Power Sources for Stability

2.7.3 Measurement noise. Signal variance

Position Control of DC Motor by Compensating Strategies

EE 370/L Feedback and Control Systems Lab Section Post-Lab Report. EE 370L Feedback and Control Systems Lab

+ + G c (s G p (s. a) What is overall transfer closed-loop transfer function θ(s)

Controller Tuning for Disturbance Rejection Associated with Delayed Double Integrating Process, Part III: PI-PD Controller

Position Control of AC Servomotor Using Internal Model Control Strategy

Basic Tuning for the SERVOSTAR 400/600

SECTION 6: ROOT LOCUS DESIGN

Compensation of a position servo

Key words: Internal Model Control (IMC), Proportion Integral Derivative (PID), Q-parameters

CDS 110 L10.2: Motion Control Systems. Motion Control Systems

BUCK Converter Control Cookbook

Performance Optimization Using Slotless Motors and PWM Drives

Intelligent Learning Control Strategies for Position Tracking of AC Servomotor

Microelectronic Circuits II. Ch 9 : Feedback

Nonlinear Control Lecture

Specify Gain and Phase Margins on All Your Loops

PID control of dead-time processes: robustness, dead-time compensation and constraints handling

A NEW EDUCATIONAL SOFTWARE TOOL FOR ROBUST CONTROL DESIGN USING THE QFT METHOD

Consider the control loop shown in figure 1 with the PI(D) controller C(s) and the plant described by a stable transfer function P(s).

Evaluation and Tuning of Robust PID Controllers

MMTO Internal Technical Memorandum #03-5

CHAPTER 9 FEEDBACK. NTUEE Electronics L.H. Lu 9-1

Laboratory Assignment 5 Digital Velocity and Position control of a D.C. motor

JNTUWORLD. 6 The unity feedback system whose open loop transfer function is given by G(s)=K/s(s 2 +6s+10) Determine: (i) Angles of asymptotes *****

Study on Repetitive PID Control of Linear Motor in Wafer Stage of Lithography

M s Based Approach for Simple Robust PI

Chapter Ten. PID Control Basic Control Functions

Robot Joint Angle Control Based on Self Resonance Cancellation Using Double Encoders

Introduction to Signals and Systems Lecture #9 - Frequency Response. Guillaume Drion Academic year

EE 435. Lecture 16. Compensation Systematic Two-Stage Op Amp Design

Closed-loop force control for a semi-automatic grinding system

Optimizing Performance Using Slotless Motors. Mark Holcomb, Celera Motion

DYNAMICS and CONTROL

Module 08 Controller Designs: Compensators and PIDs

Rotary Motion Servo Plant: SRV02. Rotary Experiment #03: Speed Control. SRV02 Speed Control using QuaRC. Student Manual

Designing PID controllers with Matlab using frequency response methodology

THE K FACTOR: A NEW MATHEMATICAL TOOL FOR STABILITY ANALYSIS AND SYNTHESIS

Feedback controller tuning on a humanoid robot

Optimized Tuning of PI Controller for a Spherical Tank Level System Using New Modified Repetitive Control Strategy

Getting the Best Performance from Challenging Control Loops

Optimal Control System Design

R. W. Erickson. Department of Electrical, Computer, and Energy Engineering University of Colorado, Boulder

PID-control and open-loop control

EE 560 Electric Machines and Drives. Autumn 2014 Final Project. Contents

Introduction to Servo Control & PID Tuning

CONTROLLER DESIGN FOR POWER CONVERSION SYSTEMS

LABORATORY #3 QUARTZ CRYSTAL OSCILLATOR DESIGN

Electronic Circuits EE359A

ANNA UNIVERSITY :: CHENNAI MODEL QUESTION PAPER(V-SEMESTER) B.E. ELECTRONICS AND COMMUNICATION ENGINEERING EC334 - CONTROL SYSTEMS

Automatic Controller Dynamic Specification (Summary of Version 1.0, 11/93)

Transcription:

Lecture 4 Scalar control synthesis The lectures reviews the main aspects in synthesis of scalar feedback systems. Another name for such systems is single-input-single-output(siso) systems. The specifications include ability to follow reference signals, to attenuate load disturbances and measurement noise and to reduce the effects of process variations. In the presentation, we separate the solution into feedback control and feedforward control. 4. Specifications Recall from Lecture the illustration of the design process shown in Figure 4.. WhileLecture2wasmainlyconcernedwithanalysis,wearenowfocusingonthe three neighboring blocks: Specification, Analysis and Synthesis. Matematical model and specification Idea/Purpose Analysis Experiment Synthesis Implementation Figure 4. Schematic overview of the design process We will restrict attention to the following structure(figure 4.2), with a scalar transferfunctionfortheplant.thissetupwasstudiedinthebasiccourseandis sufficient for many practical situations. The controller consists of two transfer functions, the feedback part C(s) and the feedforward part F(s). The control objective is to keep the process output x close to the reference signal r, in spite of load disturbances d. The measurement yiscorruptedbynoisen. WrittenbyA.RantzerwithcontributionsbyK.J.Åström

Lecture4. Scalarcontrolsynthesis d n r e u v x F(s) Σ C(s) Σ P(s) Σ y Controller Process Figure 4.2 A Controller with two degrees of freedom Several types of specifications could be relevant for this control loop. A: Reduce the effects of load disturbances B: Control the effects of measurement noise C: Reduce sensitivity to process variations D: Make the output follow command signals A useful synthesis approach is to first design C(s) to meet the specifications A,B,andC,thendesignF(s),todealwiththeresponsetoreferencechanges,D. However, the two steps are not completely independent: A poor feedback design will have a negative influence also on the response to reference signals. The following relations hold between the Laplace transforms of the signals in the closed loop system. X(s)= PCF PC R(s) +PC +PC N(s)+ P +PC D(s) V(s)= CF +PC R(s) C +PC N(s)+ +PC D(s) Y(s)= PCF +PC R(s)+ +PC N(s)+ P +PC D(s) Several observations can be made: The signals in the feedback loop are characterized by four transfer functions (sometimes called The Gang of Four) + P(s) + C(s) + + In particular, we recognize the first one as the sensitivity function and the last one as the complementary sensitivity. The total system with a controller having two degrees of freedom is characterized by six transfer functions(the Gang of Six). To fully understand the properties of the closed loop system, it is necessary to look at all the transfer functions. It can be strongly misleading to only show properties of a few input-output maps, for example a step response from reference signal to process output. This is a common mistake in the literature. The properties of the different transfer functions can be illustrated in several ways, by time- or frequency-responses. For a particular example, we show below first the six frequency response amplitudes, then the corresponding six step responses. Itisworthwhiletocomparethefrequencyplotsandthestepresponsesandto relate their shape to the specifications A-D: 2

4. Specifications PCF/(+PC) PC/(+PC) P/(+PC) CF/(+PC) C/(+PC) /(+PC) Figure4.3 FrequencyresponseamplitudesforP(s)=(s+) 4,C(s)=.775(s /2.5+) whenf(s)isdesignedtogivepcf/(+pc)=(.5s+) 4.5 PCF/(+PC).5 PC/(+PC).5 P/(+PC).5.5.5.5 2 3 CF/(+PC).5 2 3.5 2 3 C/(+PC).5 2 3.5 2 3 /(+PC).5 2 3 Figure 4.4 StepresponsesforP(s)=(s+) 4,C(s)=.775(s /2.5+)when F(s)is designedtogivepcf/(+pc)=(.5s+) 4 Disturbance rejection The two upper right plots show the effect of the disturbance d in process output x and input v respectively. The resulting process error shouldnotbetoolargeandshouldsettletozeroquicklyenough.thecontrolinput would cancel the disturbance exactly if the mid upper step response would be an ideal step. In a short time-scale this is impossible, since the control input will not change until the effect of the disturbance has appeared in the process output and been available for measurement. However, slow disturbances should normally be cancelled by u. Equivalently, the sensitivity function /( + PC) should be small for low frequencies. This specification is usually corresponds to an integrator in the controller. Suppression of measurement noise The second specification was to limit the effect of measurement noise, typically a high frequency phenomenon. The mid upper frequency plot shows good attenuation of measurement noise above the cut off frequencyofhz.inthisexample,thisismainlyaneffectoftheprocessdynamics. A more interesting question is maybe the gain from measurement noise to control input, since fast oscillations in the control actuator are usually undesir- 3

Lecture4. Scalarcontrolsynthesis Magnitude 2 2 3 4 5 6 7 P(iω)C(iω) w w Frequency (rad/sec) Robustness Disturbance rejection Figure 4.5 Frequency specifications for the closed loop system; for the sensitivity function S= +L andforthecomplementarysensitivityfunctiont= L +L,can(approximately)beinterpreted as frequency specifications in open loop for the loop transfer matrix L = P(iω)C(iω), suchthatlshouldhavesmallnorm P(iω)C(iω) athighfrequencies,whileatlowthefrequenciesinstead [P(iω)C(iω)] shouldbesmall. able. For this aspect, the mid lower frequency plot, showing the Bode amplitude fromntov,isofinterest. Robustness to process variations As shown in the previous lecture, the robustness to process variations is determined by the sensitivity functions. In this example,thelowerrightfrequencyplothasamaximalvalueof2,whichshows thatasmallrelativeerrorintheprocesscangiverisetoarelativeerrorofdouble size in the closed loop transfer function. The maximal amplitude of the frequency plot for the complementary sensitivity function is.35, so the small gain theorem provesstabilityoftheclosedloopsystemaslongastherelativeerrorintheprocessmodelisbelow74%=/.35.infact,mostprocessmodelsareinaccurateat high frequencies, so the complementary sensitivity function PC/( + PC) should be small for high frequencies. Command response The upper left corner plot shows the map from reference signalrtoprocessoutputx.usingtheprefilter F,itispossibletogetabetter stepresponseherethanintheuppermidplot.theprizetopayisthatthecorresponding response in the control signal gets higher amplitude. This can be seen bycomparingthelowerleftplot,showingthemapfromrtov,tothelowermid plot,whichshowsthecorrespondingmapwhenf. 4.2 Loop shaping The closed loop performance depends critically on the loop transfer function L(s) = Inparticular,thesensitivityfunctionscanbewrittenasS=(+L) andt= L(+L) respectively.apopularapproachtocontrolsynthesis,knownasloop shaping,istofocusontheshapeofthelooptransferfunctionandkeepmodifying C(s) until the desired shape is obtained. Recall that proper disturbance rejection requires small sensitivity S(large L) for for small frequencies, while process uncertainty requires the complementary sensitivity function to be small(small L) for high frequencies, see Fig. 4.5. On theother hand, iftheamplitude of Ldecreases very rapidly, thephase tends 4

4.2 Loopshaping tobecomelowerthan 8 andthesystembecomesunstable.loopshapingis therefore a trade-off between different kinds of specifications. Many control problems can be adequately solved by PID controllers, which can be viewed a combination of one lag compensator and one lead compensator. For more advanced applications, like resonant systems, higher order controllers are desirable.anexampleofsuchasystemistheflexibleservotreatedinlab. Magnitude 2 2 6 Phase 3 3 6 2 2 Figure 4.6 Bode diagrams for lag compensator s+ s+ (left) and lead compensator s+ s+ (right) Graphical illustrations in Bode- or Nichols- diagrams are typically used to support the design. These diagrams are convenient because of the logarithmic scale, where the controller contributes additively to the loop transfer function: log L(iω) =log P(iω) +log C(iω) arg L(iω) =argp(iω)+argc(iω) From the basic course, recall the following essential properties of lead and lag compensators, illustrated in Figure 4.6: Lag compensator Increases low frequency gain: Can be used to reduce stationary errors Decreases phase, which may reduce stability margins Lead compensator Increases high frequency gain: Can be used for faster closed loop response Increases phase, which may improve stability margins Loopshapingdesignofhighordercontrollerswillbeexercisedinlab.Wewill firstdesignacontrollerc (s)forlowfrequencies,thenkeepaddingcompensator links C 2 (s),c 3 (s),...to modify the dynamics at higher and higher frequencies untilasatisfactorycontroller C(s)=C (s) C m (s)isobtained.lead/laglinks are often sufficient, but occasionally it is useful to also consider controllers with polesorzerosoutsidetherealaxis.thefigurebelowshowsthebodediagramfor cases with stable complex zeros(left) and complex poles(right). 5

Lecture4. Scalarcontrolsynthesis Magnitude 2 3 2 3 9 9 Phase 45 45 45 45 9 9 Figure4.7 Notchcompensator s2 +.s+ (s+) 2 (left)andresonantcompensator (s+) 2 s 2 +.s+ (right) r u F(s) C(s) P(s) Σ y Figure 4.8 The feedforward filter F(s) is used to improve the response to reference signals 4.3 Feedforward synthesis Let us finally consider the design of F(s) to shape the response to reference signals. See Figure 4.8. The usual interpretation of the reference signal r is that it specifies thedesiredvalueofy.hencethetransferfunctionfromrtoyshouldbeasclose to identity as possible, ideally F(s)= orequivalently F(s)=+ + Unfortunately, this is impossible to achieve because PC/( + PC) generally has morepolesthanzeros(poleexcess)andhencef(s)wouldnotbeproper. Instead, F(s) is usually chosen to approximate( + PC)/(PC) at small frequencies. The simplest (and most common) choice is to make F constant and equal to Amoreadvancedoptionistochoose +P()C() P()C() + F(s)= (st+) d forsomesuitabletimeconstanttandwithdlargeenoughtomakefproperand implementable. ExampleIf P(s)= (s+) 4 + F(s)= (st+) 4 thentheclosedlooptransferfunctionfromrtoubecomes C(s) (s+)4 F(s)= + (st+) 4 6

4.3 Feedforwardsynthesis Thegainisforlowfrequencies(s )but/t 4 fors=.hence,fastresponse (T small) requires high controller gain. Bounds on the control signal therefore limit how fast response we can obtain. In servo systems and motion control of mechanical systems like industrial robots, it is very common to have a cascaded controller structure with an inner velocity control and an outer position control. Not only does it simplify tuning of the servos, but it also lends itself to a natural feedforward structure; when generating trajectories for the position reference the corresponding velocity and torque references should also be generated and used as feedforward signals to the inner velocity controller and actuator, respectively, see Fig 4.9. vel ref τ ref pos ref Σ G R2 (s) r Σ G R (s) u G P (s) vel s pos Figure 4.9 Cascaded controller for servo control with feedforward control of velocity references and torque references, consistent with the desired position references(generated together). 7