Electromechanical servo system with anisotropic regulator

: pp. 49-58
State Institution «Institute of Technical Problems of Magnetism of the National Academy of Sciences of Ukraine»
State Institution «Institute of Technical Problems of Magnetism of the National Academy of Sciences of Ukraine»
Kharkiv National Automobile and Highway University
Ukrainian Engineering and Pedagogical Academy
Ukrainian Engineering and Pedagogical Academy

A method of multiobjective synthesis for nonlinear multi-mass electromechanical servo systems with uncertain plant parameters based on feed-forward robust stochastic anisotropic control to improve the accuracy of such systems is developed. The method is based on the choice of the robust control target vector  by solving the corresponding problem of multiobjective nonlinear programming in which the components of the target function vectors are direct quality indicators that are specified to the system in various modes of its operation. The calculation of the target function vector componentrs and the constraints is algorithmic and is related to the synthesis of anisotropic robust regulators  and to the modelling of a synthesized nonlinear system for different operating modes of the system, with different input signals and for various values of the plant parameters. The components of the unknown vector are the required weight matrices which form the target  vector of robust control. The synthesis of anisotropic regulators is reduced to the solution of a system of four related Riccati equations. The solution to the problem of multiobjective nonlinear programming is based on particle swarm optimization algorithms. The results of theoretical and experimental research into the effectiveness of a two-mass nonlinear robust electromechanical servo system with synthesized anisotropic robust regulators are presented. The comparison of the dynamic characteristics of the synthesized electromechanical servo system showed that the application of synthesized anisotropic robust regulators improves the parameters of accuracy and reduces the sensitivity of the system to changes in the plant parameters compared to the existing system. 

  1. M. Howse, “More Electric Technologies for the 21st Century”, Institute of Electrical Engineers Power electronics, Machines and Drives, 16-18 April 2002.
  2. LF. Faleiro, “Power Optimised Aircraft – The Future of Aircraft Systems”, in Proc. AIAA/ICAS International Air and Space Symposium and Exposition: The Next 100 Years, paper number AIAA 2003-PP10127, Dayton, Ohio, USA. 4-17 July 2003.
  3. S. J. Cutts, “A collaborative Approach to the More Electric Aircraft”, Institute of Electrical Engineers Power electronics, Machines and Drives, pp. 223-228, 16-18 April 2002.
  4. G. M. Raimondi, et al., “Aircraft Embedded Generation Systems”, Institute of Electrical Engineers Power Electronics, Machines and Drives, 16-18 April 2002.
  5. J. S. Cloyd, “Status of the United States Air Force’s More Electric Aircraft Initiative”, IEEE AES Systems Magazine, pp. 17-22, April 1998.
  6. “Power Optimised Aircraft, contract G4RD-CT-2001-00601 under the European Communities 5th Framework Programme for Research. Periodic Reporting for period 1 - EMA4FLIGHT (Development of Electromechanical Actuators and Electronic control Units for Flight Control Systems). JTI-CS2-2016-CFP03-SYS-02-14 - Development of electromechanical actuators and electronic control units for flight control systems. EMA4FLIGHT. Project ID: 738042. Funded under: H2020-EU. – ITD Systems”, https://cordis.europa.eu/result/rcn/233254_en.htm
  7. “All Electric Combat Vehicles (AECV) for Future Applications”, The Research and Technology Organisation (RTO) of NATO Applied Vehicle Technology Panel (AVT) Task Group AVT-047 (WG-015), 2004.
  8. M1 Abrams Main Battle Tank 1982-1992. New Vanguard 2, Oxford, UK: Osprey Publishing 1993.
  9. Challenger 2 Main Battle Tank 1987-2006. New Vanguard 112, Oxford, UK: Osprey Publishing 2006.
  10. Marsh Gelbart, Merkava – A History of Israel’s Main Battle Tank, Germany: Tankograd Publishing, 2005.
  11. “Gun turret drives: Electric stabilization systems for military ground vehicles”, https://www.jenoptik.com/products/defense-and-security/stabilization-sys...
  12. A. Eliseyev, “Main directions of development of modern tank armament stabilizers”, News of Tula State University. Technical sciences, vol. 2, issue 11, pp. 3-9, 2012. (Russian)
  13. “Stabilizer of new generation tank armament”, Army and Navy Review, no.4, pp.41-42, 2014.
  14. O.V. Shamarih, “Electromechanical stablizers of tank armaments”, Bulletin of armored vehicles, no.1, pp. 23-26, 1985.
  15. V.V. Kozyrev, “Ways and prospects for improving the stabilizers of tank-water weapons”, Defense equipment, No. 2-3, pp. 65-71, 2005.
  16. V.L. Chernyshev, A.A. Tarasenko, and S.V.Ragulin, “Comparative evaluation of tactical and technical and structural parameters of T-64B tanks (BM “Bulat”) and Leopard-2A4” http://btvt.narod.ru/raznoe/bulat-leo2.htm
  17. V.V. Koshelev, B.P. Lavrishchev, V.Ya. Sokolov, E.K. Potemkin, and V.N. Prutkov, “Accuracy of complexes of tank-army armament according to military test data”, Bulletin of armored vehicles, no. 4, pp. 58-24, 1985.
  18. “Features of the upgraded tanks T-64BV of Ukraine Armed Forces”, https://diana-mihailova.livejournal.com/2524539.html
  19. “Stabilization Systems in Modern Tanks”, Military Technology, Special Issue No 3, pp. 78–79, 2001.
  20. W. Binroth, Closed-loop optimization program for the M60A1 tank gun stabilization system. February 1975.
  21. Е. Aleksandrov, I. Bogaenko, and B. Kuznetsov. Parametric synthesis of tank weapon stabilization system., Кyiv, Ukraine: Теkhika, 1997.
  22. S. Peresada, S. Kovbasa, S. Korol, and N. Zhelinskyi, “Feedback linearizing field-oriented control of induction generator: theory and experiments”, Tekhnichna elektrodynamika, № 2, pp. 48-56, 2017.
  23. S. Buriakovskyi, An. Masliy, and Ar. Masliy, “Determining parameters of electric drive of a sleeper-type turnout based on electromagnet and linear inductor electric motor”, Eastern-European Journal of Enterprise Technologies, № 4/1(82), pp. 32-41, 2016.
  24. W McEneaney, Max-plus methods for nonlinear control and estimation. Berlin, Germany: Birkhauser Boston, 2006.
  25. W. Rugh, Nonlinear system theory the Volterra/ Wiener Approach. Baltimor, MD, USA: The Johns Hopkins University Press, 2002.
  26. O. Tolochko, “Analysis of Observed-Based Control Systems with Unmeasured Disturbance”, in Proc. 2017 IEEE First Ukraine Conference on Electrical and Computer Engineering (UKRCON),  pp. 1006-1010, Kyiv? Ukraine, 2017.
  27. Z. Ren, M. Pham, and C. Koh, “Robust global optimization of electromagnetic devices with uncertain design parameters: comparison of the worst case optimization methods and multiobjective optimization approach using gradient index”, Magnetics, IEEE transactions on, no. 49, pp. 851-859, 2013.
  28. P. Diamond, I. Vladimirov, A. Kurdjukov, and A. Semyonov, “Anisotropy-based Performance Analysis of Linear Discrete Time Invariant Control Systems”, Int. J. Control, vol. 74, pр. 28-42, 2001.
  29. V. Galchenko and A. Yakimov, “A turmitobionic method for the solution of magnetic defectometry problems in structural-parametric optimization formulation”, Russian Journal of Nondestructive Testing, vol. 50, issue 2, pp. 59-71, 2014.
  30. V. Galchenko, A. Yakimov, and D. Ostapushchenko, “Pareto-optimal parametric synthesis of axisymmetric magnetic systems with allowance for nonlinear properties of the ferromagnet”, Technical Physics, vol. 57, Issue 7, pp. 893–899, 2012.
  31. Y. Shoham and K. Leyton-Brown, Multiagent Systems: Algorithmic, Game-Theoretic, and Logical Foundations. Cambridge, UK: Cambridge University Press, 2009.
  32. X. Yang, C. Zhihua, X. Renbin, A. Gandomi, and M. Karamanoglu, Swarm Intelligence and Bio-Inspired Computation: Theory and Applications. Amsterdam, Netherlands: Elsevier, 2013.