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A Design Method For Human-Friendly Man-Machine Systems

A Design Method For Human-Friendly Man-Machine Systems. Eri Itoh Research Fellow of Japan Society for the Promotion of Science, Department of Aeronautics and Astronautics, University of Tokyo. Contents. 1/26. 1. Introduction 2. Manual control experiments 3. New method

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A Design Method For Human-Friendly Man-Machine Systems

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  1. A Design Method For Human-Friendly Man-Machine Systems Eri Itoh Research Fellow of Japan Society for the Promotion of Science, Department of Aeronautics and Astronautics, University of Tokyo

  2. Contents 1/26 1. Introduction 2. Manual control experiments 3. New method for estimating workload levels 4. Controller design 5. Conclusion

  3. 1-a. Introduction 2/26 Background To realize human-friendly piloting, man-machine systems should reduce workload levels. Both the physical and the mental load in the course of carrying out the task.

  4. 1-b. Introduction 3/26 Past work in workload estimation 1. Handling qualities criteria 2. Subjective rating 3. Physiological response

  5. 1-c. Introduction 4/26 Conventional methods don’t quantitatively define workload. They are difficult to utilize as conceptual design condition of flight controller.

  6. 1-d. Introduction 5/26 Purposes 1. To propose a new method to quantitatively estimate WL levels . 2. To use the method, to design flight controller which guarantee human-friendly operation.

  7. 1-e. Introduction 6/26 To propose a method to estimate WL levels, this research relate pilot models to WL. Transfer functions which represent pilot operation

  8. 1-f. Introduction 7/26 Review of past work in pilot models In 1950’s to 70’s, pilots were modeled as low-order transfer functions. Recent high-performance vehicles impose difficult operation to pilots. Considering pilots as controllers, they have to have high-order dynamics.

  9. 1-g. Introduction 8/26 • This research adopts • high-order pilot models • 2-block pilot models Pilot models are identified by experiments.

  10. 2-a. Manual control experiments 9/26 Experimental apparatus These Experiments are analogous to longitudinal dynamics of aircraft in the effect of disturbance input.

  11. 2-b. Manual control experiments 10/26 Experimental procedures Block Diagram 2-block pilot models were identified with high-order transfer functions. WL level is commented by using a 5 point rating scale . 1・・・The most comfortable piloting 5・・・The most wearisome piloting

  12. 2-c. Manual control experiments 11/26 Experimental results – Gain plots of pilot models WL 1 WL 5 WL 3

  13. 2-d. Manual control experiments 12/26 Experimental results – Controllable Frequency Controlled dynamics (operator not included) Closed-loop systems (operator in the loop) The limit of controllable frequency is 4rad/sec.

  14. 2-e. Manual control experiments 13/26 Summary of experimental results 1. There exist ideal gain plots shape for pilot models which correspond to comfortable piloting. 2. The gap between the ideal gain plots shape for pilot models and the other ones indicate the increase of WL levels. 3. The limit of controllable frequency for pilots is 4 rad/sec.

  15. 3-a. New method for estimating WL levels 14/26 Estimation Indices Subject gain plots The ideal gain plots:WL1 Gain Plots of pilot models Estimation Index 1 Estimation Index 2

  16. 3-b. New method for estimating WL levels 15/26 The relation between WL comments and indices – H1

  17. 3-c. New method for estimating WL levels 16/26 The relation between WL comments and indices – H2

  18. 3-d. New method for estimating WL levels 17/26 Estimation method H1H2WL Level1Level11 Level1Level22 Level2Level12 Level2Level23 Level2Level34 Level3Level24 Level3Level35 Subjective WL comments and estimated WL levels agree to 95 %.

  19. 3-e. New method for estimating WL levels 18/26 Results achieved to date This research proposes a method which quantitatively estimates workload levels though pilot models. The proposed method enables us to design controller on assumed workload levels

  20. 4-a. Controller design 19/26 Design purposes • To ensure workload level 1. • To realize both ideal tracking performance • and disturbance rejection.

  21. 4-b. Controller design 20/26 Design procedures • Pick out pilot models and controlled dynamics. • H1, H2・・・WL level 1 P・・・WL level 5 • 2. Controller design to achieve • desired tracking performance • and disturbance rejection.

  22. 4-c. Controller design 21/26 What could be the desired performance? - Tracking performance • The droop, which means a drop in gain value from 0dB, becomes more than -5dB for low frequencies below • 4 rad/sec. • 2. The peak value of gain is less than 0dB.

  23. 4-d. Controller design 22/26 What could be the desired performance? - Disturbance rejection 3. The peak value of gain is less than -5dB.

  24. 4-e. Controller design 23/26 By usingloop shaping technique, flight controller is designed which satisfy these 3 conditions. Demonstration experiments were carried out :One with controller and another without controller.

  25. 4-f. Controller design 24/26 Effectiveness of Designed Controller Without controller : subjectively commented as WL 5 With controller : subjectively commented as WL 1 Pilot’s comments and the proposed method indicate designed flight controller worked well.

  26. 4-g. Controller design 25/26 Tracking performance Disturbance rejection Both of tracking performance and disturbance rejection satisfy 3 design conditions

  27. 5. Conclusion 26/26 1. The new method to quantitatively estimate workload levels was proposed. 2. Flight controller which ensure human-friendly operation is designed though the proposed estimation method. 3. Demonstration experiments showed the effectiveness of the designed controller.

  28. Thank you very much!

  29. APPENDIX 1-1 loop shaping technique Tracking performance - design condition2 Disturbance rejection – design condition 3

  30. APPENDIX 1-2 Tracking performance – design condition 1 Where . By using Wr, frequency range is limited.

  31. APPENDIX 1-3 Pilot models, H1 and H2 Controlled dynamics Weighting function Controller

  32. APPENDIX 1-4 By using LMI, the controller is designed.

  33. APPENDIX 2-1 White noise filtered through

  34. The end

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