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Mechatronics at the University of Calgary: Concepts and Applications

Mechatronics at the University of Calgary: Concepts and Applications. Jeff Pieper. Outline. Mechatronics Past and Present Research Results Undergraduate Program Directions for the Future Summary. What is Mechatronics?.

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Mechatronics at the University of Calgary: Concepts and Applications

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  1. Mechatronics at the University of Calgary: Concepts and Applications Jeff Pieper

  2. Outline • Mechatronics • Past and Present Research Results • Undergraduate Program • Directions for the Future • Summary

  3. What is Mechatronics? • Synergistic combination of mechanics, electronics, microprocessors and control engineering • Like concurrent engineering • Does not take advantage of inherent uniqueness available • Control of complex electro-mechanical systems • Rethinking of machine component design by use of mechanics, electronics and computation • Allows more reconfigurablility

  4. What is Mechatronics • Design example: timing belt in automobile • Timing belt mechanically synchronizes and supervises operation • Mechatronics: replace timing belt with software • Allows reconfigurability online

  5. What is Mechatronics • Second example: Active suspension • Design of suspension to achieve different characteristics under different operating environments • Demonstrates fundamental trade-offs

  6. What is Mechatronics • Low tech, low cost, low performance: pure mechanical elements: spring shock absorber • Can use dynamic systems to find coefficients via time or frequency domain • mid tech, cost, performance: electronics: op amps, RLC circuits, hydraulic actuators • Typically achieve two operating regimes, e.g. highway vs off-road • High tech, cost , performance: microprocessor-based online adjustment of parameters • Infinitely adjustable performance *

  7. Research Projects • Discrete Sliding Mode Control with Applications • Helicopter Flight Control • OHS Aircraft Flight Control • Magnetic Bearings in Papermaking Systems • Robust Control for Marginally stable systems • Process Control and System ID • Controller Architecture *

  8. Theme of research • Control of • Uncertain • Nonlinear • Time-varying • Industrially relevant • Electro-mechanical systems • This is control applications side of mechatronics • Involves sensor, actuator, controller design

  9. What is control? • Nominal performance • Servo tracking • Disturbance rejection • Low sensitivity • Minimal effects of unknown aspects • Non-time-varying

  10. Feedback Control *

  11. Discrete Time Sliding Mode Control • Comprehensive evaluation of theoretical methodology • Optimization, maximum robustness • Applications: • Web tension system • Gantry crane

  12. Web Tension System

  13. Gantry Crane *

  14. Helicopter Flight Control • Experimental Model Validation • Model-following control design • Experimental Flight Control • Multivariable • Start-up and safety

  15. Helicopter Flight Control

  16. Helicopter Flight Control • Model-following vs. stability • Conflicting Multi-objective • Controller Optimization • Order reduction • System validation

  17. Helicopter Flight Control *

  18. OHS Aircraft Flight Control • Outboard Horizontal Stabilizer • Non-intuitive to fly • Developed sensors and actuators • Model identification and validation • Gain-scheduled adaptive control • Reconfigurable controller based upon feedback available

  19. OHS Aircraft * 15 m/s 20 m/s

  20. Magnetic Bearings in Papermaking Systems • System identification for magnetic bearings • Nonlinear, unstable system • Closed loop modeling • Control Design using Sliding Mode methods and state estimators • Servo-Control of shaft position

  21. Magnetic Bearings

  22. Magnetic Bearings in Papermaking Systems • Papermaking system modeling • Use of mag bearings for tension control actuation and model development • Control Design and implementation issues • Compare performance with standard roller torque control

  23. Papermaking Tension Control *

  24. x   Robust Control via Q-parameterization • Ball and beam application • Stability margin optimization: Nevanlinna-Pick interpolation

  25. Experimental Results • Large lag • Non-minimum phase behaviour • Friction, hard limits

  26. Robust Stability Margin * Delay Nominal Optimal 0 -0.27 -0.30 0.1 -0.26 -0.28 0.2 -0.19 -0.22 0.3 -0.07 -0.11 0.4 0.06 0.01 0.5 0.17 0.10 0.6 0.26 0.18 0.7 0.34 0.24 0.8 0.39 0.29 0.9 0.44 0.33 1 0.48 0.37 1.1 0.51 0.40 1.2 0.54 0.42 1.3 0.56 0.44 1.4 0.58 0.46 1.5 0.60 0.47

  27. Out2 Out1 Out2 Out1 Tank3 L3 Tank1 L1 G11 G21 Tank4 L4 Tank2 L2 G12 G22 PUMP1 PUMP2 Process Control and System ID: Quadruple-tank Process Diagram

  28. System ID: Model Fitting Tank4 process model with input u1 Tank2 process model with input u1

  29. Control Techniques • Classic PI control • Internal Model Control (IMC) • Model Predictive Control (MPC) • Linear Quadratic Regulator (LQR) Optimal Control

  30. MPC Control Results Different set points changes to test MPC controller performance Tank2 response Tank4 response

  31. Performance Comparison* Controllers Parameters

  32. Controller Architecture • Given conflicting and redundant information • Design controller with best practical behaviour • Good nominal performance • Robust stability • Implementable *

  33. Undergraduate Program: Mechatronics Lab with Applications • Developed lab environment for teaching and research • Two courses: - linear systems, - prototyping • Hands-on work in: • modeling • system identification • Sampled-data systems • Optical encoding • State estimation • Control design

  34. Mechatronics Lab with Applications • Multivariable fluid flow control system • Two-input-two-outputs • Variable dynamics • Model Predictive Control • Chemical Process Emulation

  35. Fluid Flow Control Quanser Product

  36. Mechatronics Lab with Applications • Ball and Beam system • Hierarchical control system • Motor position servo • Ball position • Solve via Q-parameterization • Robust stability and optimal nominal performance

  37. Ball and Beam System Quanser Product

  38. Mechatronics Lab with Applications • Heat Flow Apparatus • Unique design • Varying deadtime for challenging control • Demonstrate industrial control schemes • PID controllers • Deadtime compensators

  39. Heat Flow Apparatus * Quanser product

  40. Directions for the Future • Robust Performance • robust stability and nominal performance simultaneously guaranteed • Multiobjective Control Design • Systems that meet conflicting, and disparate objectives • Performance evaluation for soft measures • Fuzzy systems • Bottom line: Mechatronics *

  41. Summary • Control applications in electro-mechanical systems • Emphasis on usability • Complex problems from simple systems • Undergraduate program: hands-on learning and dealing with systems form user to end-effector

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