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Demonstrator of advanced controllers

Master of Science assignment. Demonstrator of advanced controllers. Hans Dirne. May 25 th , 2005. Supervisors prof.dr.ir. J. van Amerongen dr.ir. J.F. Broenink dr.ir. T.J.A. de Vries ir. P.B.T. Weustink. Why this assignment?. The Major ‘Mechatronics’ provides several courses

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Demonstrator of advanced controllers

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  1. Master of Science assignment Demonstrator of advanced controllers Hans Dirne May 25th, 2005 Supervisors prof.dr.ir. J. van Amerongen dr.ir. J.F. Broenink dr.ir. T.J.A. de Vries ir. P.B.T. Weustink

  2. Why this assignment? The Major ‘Mechatronics’ provides several courses in control theory, in which the theory is often supported by simulations. A physical setup might, in addition to simulations, be an enrichment for demonstrating control theory. Such a demonstration setup will be able to make the theory more insightful and will show real limitations in practical setups. Demonstrator of advanced controllers

  3. To design, build and test a mechatronic demonstration setup, with which several control algorithms can be shown in practice To be able to demonstrate performance differences of control algorithms in practice Objectives Demonstrator of advanced controllers

  4. Demonstration setup options Control systems Design of the new demonstrator Experiments Demonstration Conclusions & recommendations Overview Demonstrator of advanced controllers

  5. Demonstration setup options Demonstrator of advanced controllers

  6. Mechatronic system Portable and easy to set up Robust, safe and failsafe design High level of observability Representable by linear 4th order model Clear link with well known device Criteria Demonstrator of advanced controllers

  7. Three options • ‘Linix’ laboratory setup 2. Setup of ‘Controllab Products B.V.’ 3. New build Demonstrator of advanced controllers

  8. Option 1: ‘Linix’ Laboratory Setup Demonstrator of advanced controllers

  9. ‘Linix’ Laboratory Setup encoders motor inertia 2 inertia 1 transmission Demonstrator of advanced controllers

  10. ‘Linix’ Laboratory Setup Demonstrator of advanced controllers

  11. ‘Linix’ Laboratory Setup Major disadvantage: slip between belt and inertias Demonstrator of advanced controllers

  12. Option 2: CLP setup Demonstrator of advanced controllers

  13. CLP setup Demonstrator of advanced controllers

  14. CLP setup Demonstrator of advanced controllers

  15. Sensor positions Demonstrator of advanced controllers

  16. Option 3: New Build Advantage • Pure design freedom Disadvantage • Requires very much time and effort to design Demonstrator of advanced controllers

  17. Overview demonstrators

  18. Control Systems Demonstrator of advanced controllers

  19. Viscous PLUS coulomb friction Mathematical model – 6th order Demonstrator of advanced controllers

  20. Focus • Linear Quadratic Gaussian (LQG) • Proportional, Integral, Differential (PID) Demonstrator of advanced controllers

  21. LQG explanation A LQG control algorithm is a combination of • Lin. Quad. Regulator (state feedback) • Lin. Quad. Estimator (state estimation) 4th order linear model required! Demonstrator of advanced controllers

  22. 4th order linear model Required steps: • Downsize system order • Linearize system: discard coulomb friction Result: linear 4th order model (e.g. State Space) Demonstrator of advanced controllers

  23. LQG controlled system Demonstrator of advanced controllers

  24. PID Demonstrator of advanced controllers

  25. Tuning (1) For proper comparison of the PID with the LQG controlled system, tuning with the same criteria is required. • Avoid actuator saturation • Minimization of criterion: position error controller output Demonstrator of advanced controllers

  26. Tuning (2) Tuning procedure: • Set Q and R • Minimize criterion J by optimizing controller gains (KLQG and KP,KI,KD) Demonstrator of advanced controllers

  27. Tuning (3) Optimization results KP = 15.7 KI = 42 KD = 1.6 KLQG = [3.7, 74, 8.2, 70]T Demonstrator of advanced controllers

  28. PID vs LQG (1) • The PID controlled system consumes twice the power of the LQG system • The maximum frame movement in the PID controlled system is twice compared to LQG Demonstrator of advanced controllers

  29. PID vs LQG (2) The LQG control algorithm leads to an unacceptable position error with the nonlinear process Demonstrator of advanced controllers

  30. LQG+ Demonstrator of advanced controllers

  31. LQG+ vs LQG Effect of integrator: Static error is minimized! Interesting to see the performance of LQG+ in practice… Demonstrator of advanced controllers

  32. Design of the new demonstrator Demonstrator of advanced controllers

  33. Procedure Goal: to test a control algorithm on a physical setup How? Demonstrator of advanced controllers

  34. System overview (1) Client: • Runs MS Windows • Generating models • Model control (start/stop/upload/delete) • Setting parameters of controlled system real-time • View parameters of controlled system real-time Server: • Runs Linux, with real-time kernel • Runs control system • Performs I/O Demonstrator of advanced controllers

  35. System overview (2) Demonstrator of advanced controllers

  36. Realization Mechatronics Embedded PC + I/O Power (CPU) Power (motor) Motor amplifier Demonstrator of advanced controllers

  37. Experiments Demonstrator of advanced controllers

  38. Experiments • Comparison of PID/LQG/LQG+ performance on the new demonstration setup • Same controller parameters used as in simulation (after tuning) • Performance comparison on: • Static error • Frame vibration • Power usage Demonstrator of advanced controllers

  39. Demonstrator of advanced controllers

  40. Results The LQG+ controlled system outperforms the PID controlled system: • Maximum frame movement differs factor 3 • Total power consumption differs a factor 2 • Both control algorithms minimize the static error, but the LQG controlled system is faster More performance increase is expected with a better model Differences in performance between 2nd order PID and 4th order LQG have now been demonstrated in practice Demonstrator of advanced controllers

  41. Demonstration Demonstrator of advanced controllers

  42. Demonstration What will be shown: • ‘Homing’ of the demonstrator • Determining absolute position • PID controller in practice with various controller gains Furthermore: • Online adjustment of parameters • Real-time variable monitoring • Real-time animation of demonstration setup Demonstrator of advanced controllers

  43. Conclusions & Recommendations Demonstrator of advanced controllers

  44. Conclusions • The new mechatronic demonstration setup is a compact, integrated machine that forms a versatile development environment for testing various control algorithms in practice • The new demonstrator allows for easy comparison of different control algorithms 3. Non-linear friction elements in the process will lead to lower performance in position control of a 4th order LQG-controlled system compared to a 2nd order PID control algorithm 4. Addition of an integrating term leads to an ‘LQG+’ control algorithm that can compensate for differences between process and reference model. Demonstrator of advanced controllers

  45. Recommendations Hardware • Expand safety system • Reduce weight of the demonstrator (next version) • Add parallel processing (e.g. distributed control) Software / control • Experiment with more control systems (MRAS, (L)FF, ILC etc) • Perform system identification General 1. Set up lab work assignments for student Demonstrator of advanced controllers

  46. Questions…? Demonstrator of advanced controllers

  47. THANK YOU FOR YOUR ATTENTION you are all invited for DRINKS at ‘De Tombe’, floor 0 Demonstrator of advanced controllers

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