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Mechatronics at the University of Calgary: Concepts and Applications

Explore the interdisciplinary field of mechatronics combining mechanics, electronics, and control engineering at the University of Calgary. Delve into research projects, control applications, and future directions in this dynamic field.

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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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