Advertisement

Dynamic Torque Control Incorporating Tracking Differentiator for Motor-Driven Load Simulator

  • Kang Chen
  • Hang Guo
  • Li Sun
  • Jie Yan
Part of the Communications in Computer and Information Science book series (CCIS, volume 402)

Abstract

Widely used in the static/dynamic stiffness test of aircraft actuation systems, Motor-driven load simulator (MDLS) simulates the aerodynamic load and exerts the load on actuation system. MDLS endures position coupling disturbance from active motion of actuation system, and this inherent disturbance is called extra torque. However, to eliminate the influence of extra torque is the key issue regarding to the MDLS controller design, as the extra torque may degrade the performance of MDLS seriously. A compound torque control algorithm based on tracking differentiator (TD) is proposed for MDLS in this paper. This algorithm reflects the essential characteristics of MDLS and guarantees transient tracking performance as well as final tracking accuracy. In detail, firstly, the mathematical models of MDLS are derived, and the influence of the extra torque is also studied. Tracking differential filter is then utilized to identify the actuator’s velocity, acceleration and jerk, which can compensate the extra torque. Finally, based on the structural invariability theory, a compound controller is developed, which consists of forward path corrector, feed-forward controller and differential tracking filter. Simulation and experiment comparative results are obtained to verify the high-performance nature of the proposed control strategy; the tracking accuracy and bandwidth are greatly improved.

Keywords

flight simulation electric load simulator tracking differentiator compound control 

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

References

  1. 1.
    Jiao, Z.X., Gao, J.X., Hua, Q., et al.: The velocity synchronizing control on the electrohydraulic load simulator. Chinese Journal of Aeronautics 17(1), 39–46 (2004)CrossRefGoogle Scholar
  2. 2.
    Nam, Y., Hong, S.: Force control system design for aerodynamic load simulator. Control Engineering Practice 10(5), 549–558 (2002)CrossRefGoogle Scholar
  3. 3.
    Li, H.: Development of hybrid control of electrohydraulic torque load simulator. Journal of Dynamic Systems Measurement and Control 124(3), 415–419 (2002)CrossRefGoogle Scholar
  4. 4.
    Zhou, J.: Control strategy of the synchrodrive electro-hydraulic servo system. In: Proceedings of International Conference on Fluid Power, pp. 365–367 (2006)Google Scholar
  5. 5.
    Wu, S.L.: Study on control of twin-hydraulic motor synchrodrive system. Chinese Journal of Mechanical Engineering 6(3), 165–170 (1993)Google Scholar
  6. 6.
    Liu, C.N.: The optimized design theory of hydraulic servo system. Metallurgical Industry Press, Beijing (1989) (in Chinese) Google Scholar
  7. 7.
    Yao, J.Y., Shang, Y.X., Jiao, Z.X.: The velocity feed-forward and compensation on eliminating extra torque of electro-hydraulic load simulator. In: Proceedings of the Seventh International Conference on Fluid Power Transmission and Control, pp. 462–465 (2009)Google Scholar
  8. 8.
    Plummer, A.R.: Control techniques for structural testing: a review. Proceedings of the Institution of Mechanical Engineers, Part I: Journal of Systems and Control Engineering 221(12), 139–167 (2007)CrossRefGoogle Scholar
  9. 9.
    Chantranuwathana, S., Peng, H.: Adaptive robust force control for vehicle active suspensions. International Journal of Adaptive Control and Signal Processing 18(2), 83–102 (2004)CrossRefGoogle Scholar
  10. 10.
    Mare, J.C.: Dynamic loading systems for ground testing of high speed aerospace actuators. Aircraft Engineering and Aerospace Technology 78(4), 275–282 (2006)CrossRefGoogle Scholar
  11. 11.
    Truong, D.Q., Ahn, K.K.: Force control for hydraulic load simulator using self-tuning grey predictor—fuzzy PID. Mechatronics 19(2), 233–246 (2009)CrossRefGoogle Scholar
  12. 12.
    Kanellakopoulos, I., Kokotovic, P.V., Morse, A.S.: Systematic design of adaptive controllers for feedback linearizable systems. IEEE Transactions on Automatic Control 36(11), 1241–1253 (1991)MathSciNetCrossRefzbMATHGoogle Scholar
  13. 13.
    Yang, Y.S.: Direct robust adaptive fuzzy control (DRAFC) for uncertain nonlinear systems using small gain theorem. Fuzzy Sets and Systems 151(1), 79–97 (2005)MathSciNetCrossRefzbMATHGoogle Scholar
  14. 14.
    Yang, Y.S., Zhou, C.J.: Adaptive fuzzy H∞ stabilization for strict-feedback canonical nonlinear systems via backstepping and small-gain approach. IEEE Transactions on Fuzzy Systems 13(1), 104–114 (2005)CrossRefGoogle Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2013

Authors and Affiliations

  • Kang Chen
    • 1
  • Hang Guo
    • 1
  • Li Sun
    • 1
  • Jie Yan
    • 1
  1. 1.College of AstronauticsNorthwestern Polytechnical UniversityXi’anChina

Personalised recommendations