Matteo Macchini
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Matteo Macchini Student meeting - May 2014 Motion control design for the new BWS Matteo Macchini Technical student BE-BI-BL Supervisor: Jonathan Emery
description
Motion control design for the new BWS. Matteo Macchini Technical student BE-BI-BL. Supervisor: Jonathan Emery. Matteo Macchini. Student meeting - May 2014. Outline. Beam Wire Scanner overview Motor selection and sizing procedure Motor control Tuning of the controllers Simulations. - PowerPoint PPT Presentation
Transcript of Matteo Macchini
Matteo Macchini Student meeting - May 2014
Motion control design for the new BWS
Matteo MacchiniTechnical student
BE-BI-BLSupervisor:Jonathan Emery
Matteo Macchini
Outline
Student meeting - May 2014
• Beam Wire Scanner overview
• Motor selection and sizing procedure
• Motor control
• Tuning of the controllers
• Simulations
Matteo Macchini
Beam Wire Scanner
Student meeting - May 2014
Purpose:
Evaluate the profile of the beam into the accelerators
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Beam Wire Scanner
Student meeting - May 2014
Electromechanical system
• Motor• Position/speed sensors• Thin wire • Scintillator• Photomultiplier
Matteo Macchini
Desired wire motion
Student meeting - May 2014
Three phases
• “Constant” acceleration• Constant speed
(beam crossing)• “Constant” deceleration
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Motor selection and sizing
Student meeting - May 2014
• Air-gap thickness• Torque to inertia ratio• Vacuum compatibility
• Radiation tolerance• Temperature tolerance• Torque ripple
Specifications
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Permanent Magnet Synchronous Motor
Student meeting - May 2014
Model:PARKEM k500300-5Y
Air gap thickness: 0.3mm ÷ 0.75mm
Inertia:0.00104kg*m2
Max torque:32.8Nm
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PMSM input
Student meeting - May 2014
Three phase sine wave
• Flux = LC of the 3ph fluxes
• Motion is achieved keeping the flux spin
• Torque = k*(Flux)x(Theta)
So MAX torque ↔ Flux Theta ⊥
Matteo Macchini Student meeting - May 2014
Three phase static↕
CLARKE↕
Two phase static↕
PARK↕
Two phase rotating
Clarke – Park decomposition
Matteo Macchini Student meeting - May 2014
Simulated system
Overall system
Simplified system
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Motor control
Student meeting - May 2014
FOC – Field Oriented Control
Control method
T = k*iq (if id=0)
Double feedback control• Current
Quadriture (αT) Direct (αF)
• Speed
Space Vector Modulation
Controllers
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PID controllers
Student meeting - May 2014
PID (t )=Kp∗ f (t )+Ki∗∫ f (t )dt+¿Kd∗ df (t)dt
¿
PID (s )=Kp+ Kis +Kd∗ s
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PID controllers
Student meeting - May 2014
PID(s) G(s)uer y+
-
𝑇𝐹 𝑐𝑙𝑜𝑠𝑒𝑑𝑙𝑜𝑜𝑝 (𝑠 )=𝑃𝐼𝐷 (𝑠 )∗𝐺(𝑠)1+𝑃𝐼𝐷 (𝑠)∗𝐺(𝑠)
𝑇𝐹 𝑜𝑝𝑒𝑛𝑙𝑜𝑜𝑝 (𝑠)=𝑃𝐼𝐷 (𝑠 )∗𝐺(𝑠 )
Matteo Macchini
PID tuning
Student meeting - May 2014
THEORETICAL APPROACHES
Transfer function computationand simulation
Pole-zero compensation
… unpopular and not very efficient
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PI control and tuning
Student meeting - May 2014
EXPERIMENTAL APPROACHES
Open loop methods• Ziegler-Nichols• Cohen-Coon• Cooper
Closed loop methods• Z-N closed loop• ATV
Adaptive methods• PSO
“Modern” methods• H∞ controller• H2 controller• μ controller
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Particle Swarm Optimization
Student meeting - May 2014
Particle filter based on the behaviour of swarms of birds
Parametric optimization in order to follow local-global optimums
Looking for MIN of a quality function (IAE)
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Results classic tuning (so far…)
Student meeting - May 2014
Current loop Speed loop
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Results PSO (so far…)
Student meeting - May 2014
Current loop
Speed loop
i=1
i=1 i=4 i=7 i=10
i=4 i=7 i=10
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In the future…
Student meeting - May 2014
NEXT GOALS
• Space Vector PWM implementation
• Position loop
• Complete system simulation
• See what happens with the real system!
