westdig - csd

8/8/2019 WestDig - CSD

http://slidepdf.com/reader/full/westdig-csd 1/19

Connecting Theory with Practicefor Western Digital

Control Systems Design,Tuning and Optimization with

MATLAB and Simulink

James AngApplication Engineer

TechSource Systems [email protected]



© 2010 TechSource Systems

AgendaBrief Introduction to Simulink

Introduction to Controls System Design

Various approaches in Plant Modeling

± First Principles Method + demo ± Data Driven Modeling (Blackbox method) + demo

± Parameter Estimation (Graybox Method) + demoCompensator Design

± Design Challenges

± Controls Design, Tuning and Optimization demoSummary

Question and Answers




Lego : Using standard bricks to construct, assemble or build models.The pieces used can be taken apart again, used to create other objects.

Simulink




Simulink ®

Block-diagram environment

Model, simulate, and analyze time-varying systems ± Control systems ± Signal processing systems ± Communications systems ± Other dynamic systems

A ccurately design, implement, and test

Platform for Model-Based Design




Simulink ® BlocksetsSimulink blocksets offers a customized set of block libraries thatlet you design, implement, verify and validate various time-varying systems.

SignalProcessing

Video & ImageProcessing

Communications SimMechanics

Simulink

ControlDesign

RF

And manymore




W hat is Control Systems design?

PlantController/Feedback

Compensator+

-Input Output

Feedback loop

Servo system = Closed looped control system




PlantModel

Controller Model

OutputInput

+ -

How to start?1. (a) Getting the plant model

Speed Control of a DC motor




Fi rst-Pr inc iples Model ing

Use an understanding of thesystem¶s physics to derive amathematical representation

Two A pproaches to Modeling Dynamic Systems




Fi rst-Pr inc iples Model ing Data-Dr iv en Model ing

Use system test data to derive amathematical representation

¼¼¼¼

½

»

¬¬¬¬

-

«

!

13

231

)(

2

2

23

s s

s

s s

s

s H

Use an understanding of thesystem¶s physics to derive amathematical representation

Two A pproaches to Modeling Dynamic Systems




Both A pproaches Have A dvantages & Disadvantages

A d v antages:M odel provides insight into thesystem¶s underlying behavior

Disad v antages:M odel does not accurately matchmodel outputSystem contains unknown,nonlinear parameters like frictionTime consuming to developHighly nonlinear systems difficultto express in first principles


A d v antages:F ast to develop a modelUsually highly accurate

Disad v antages:R equires a physical system toacquire test dataM odel lacks description of physics of the systemNeed many data sets to cover range of system operation




Tools That Span Both ModelingA

pproaches


SimulinkDesign

Optimization

Complete Model ing En vi ronment

Simulink

Sim M echanics

SimDrivelineSimPowerSystems

AerospaceBlockset

First-Pr

inc

iples

Neural NetworkToolbox

SystemIdentification

Toolbox

F uzzy LogicToolbox

Data-Dr iv

en




PlantModel

Controller Model

OutputInput

+-

Controller - Speed Control of a DC motor

How to start?1. (a) Getting the plant model2. (b) Design the Controller model Controller Design and

Simulation




Control Challenges

Common Method : Trial andError tuning of feedback controllers

Tuning challenges

± Tuning is not systematic and istime consuming ± Tuning on a real system can be

costly ± Impossible to tell if you re at

optimal solution




A controller changes the natural plant response into a desiredresponse

A controller helps makethe natural plant responsego from this«natural plant response

« to become

like this

desired plant response




Control systems design

Building the model ± First-Principles Modeling (Simulink), Data-Driven Modeling (System

identification Toolbox), Using Root locus and bode diagram todesign the controller (SISO tool),

Optimize your model ± specify the desired output (Simulink DesignOptimization)

Summary and Wrap up




M odeling

Design

Analysis

Key TakeawaysControl Systems toolbox




System IdentificationToolbox

Model estimation usingtime & frequency domaindata

Data preprocessing toolsincluded

Blocks for directly addingdata-driven models toSimulink models

Key Takeaways




T uned Parameters

Des ired Response

R ise time, settling time,% overshoot

Key TakeawaysSimulink Design Optimization

Estimate and Optimize modelparameters

Interactive data preprocessing

Model validation using residualplots




Do you have any questions?

Tel: 603Tel: 603 8076 1953 Fax: 6038076 1953 Fax: 603 8076 19548076 1954Email:Email: [email protected]@techsource.com.my W eb:W eb: www.techsource.com.mywww.techsource.com.myTechTech--Support:Support: [email protected]@techsource.com.my

T hank you for your attendance.

westdig - csd

Documents