WestDig - CSD
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Connecting Theory with Practicefor Western Digital
Control Systems Design,Tuning and Optimization with
MATLAB and Simulink
James AngApplication Engineer
TechSource Systems [email protected]
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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
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Lego : Using standard bricks to construct, assemble or build models.The pieces used can be taken apart again, used to create other objects.
Simulink
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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
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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
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W hat is Control Systems design?
PlantController/Feedback
Compensator+
-Input Output
Feedback loop
Servo system = Closed looped control system
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PlantModel
Controller Model
OutputInput
+ -
How to start?1. (a) Getting the plant model
Speed Control of a DC motor
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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
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Fi rst-Pr inc iples Model ing Data-Dr iv en Model ing
Use system test data to derive amathematical representation
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Use an understanding of thesystem¶s physics to derive amathematical representation
Two A pproaches to Modeling Dynamic Systems
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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
Fi rst-Pr inc iples Model ing Data-Dr iv en Model ing
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
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Tools That Span Both ModelingA
pproaches
Fi rst-Pr inc iples Model ing Data-Dr iv en Model ing
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
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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
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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
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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
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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
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M odeling
Design
Analysis
Key TakeawaysControl Systems toolbox
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System IdentificationToolbox
Model estimation usingtime & frequency domaindata
Data preprocessing toolsincluded
Blocks for directly addingdata-driven models toSimulink models
Key Takeaways
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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
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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.