ISSN 0021-3454 (print version)
ISSN 2500-0381 (online version)
Menu

10
Issue
vol 62 / November, 2019
Article

DOI 10.17586/0021-3454-2016-59-12-1003-1009

UDC 519.7

SUBOPTIMAL SPEED CONTROL BY MULTI-AGENT SYSTEMS UNDER INFORMATION CONSTRAINTS

I. B. Furtat
Institute of Problems of Mechanical Engineering, Russian Academy of Sciences, Saint Petersburg, 199178, Russian Federation; ITMO University, Saint Petersburg, 197101, Russian Federation; Leading scientific researcher$ Professor


Read the full article 

Abstract. A robust suboptimal control solution of the speed control is proposed for multi-agent systems described by nonstationary nonlinear differential equations with uncertain parameters, disturbances, communication delay, and possible information constraints in the measurement channels. To compensate for disturbances, the method of auxiliary loop method is used with the loop presented by a parallel reference model for each agent. Classical methods of optimal control are used for speed control, and therefore calculation of optimal control may be carried out with the use of standard packages of existing software, e.g. MatLab. Simulation results are presented to demonstrate the effectiveness of the proposed scheme under uncertainties, delay, and information constraints. The results show that the control accuracy can be improved by increasing the gain in the control law, reduce the high frequency gain in the auxiliary loop, and increase the feedback gain of the observer.
Keywords: multi-agent system, robust control, optimal control, communication delay, information constraints

References:
  1. Pupkov K.A., Egupov N.D., eds., Metody klassicheskoy i sovremennoy teorii avtomaticheskogo upravleniya. Teoriya optimizatsii avtomaticheskogo upravleniya (Methods of Classical and Modern Automatic Control Theory. Optimization Theory, Automatic Control), Moscow, vol. 4, 2004. (in Russ.)
  2. Bukov V.N. Vlozhenie sistem. Analiticheskiy podkhod k analizu i sintezu matrichnykh sistem (Inclusion of Systems. Analytical Approach to Analysis and Synthesis of Matrix Systems), Kaluga, 2006. (in Russ.)
  3. Nikiforov V.O. Adaptivnoe i robastnoe upravlenie s kompensatsiey vozmushcheniy (Adaptive and Robust Control with Disturbance Compensation), St. Petersburg, 2003. (in Russ.)
  4. BobtsovA.A. JournalofComputerand Systems Sciences International, 2003, no. 2, pp. 93–97. (in Russ.)
  5. Bobtsov A.A. Automatic and Remote Control, 2003, no. 8(64), pp. 943–950. (in Russ.)
  6. Tsykunov A.M. Automation and Remote Control, 2007, no. 7(68), pp.1213–1224.
  7. Voronov A.A., ed., Teoriya avtomaticheskogo upravleniya. Teoriya nelineynykh i spetsial'nykh sistem avtomaticheskogo upravleniya (Theory of Automatic Control. Theory of Nonlinear and Special Systems of Automatic Control), Moscow, 1986. (in Russ.)
  8. Atassi A.N., Khalil H.K. IEEE Trans. Automat. Control, 1999, no. 9(44), pp.1672–1687.
  9. Furtat I.B. Mechatronics, Automation, Control(Mehatronika, Avtomatizacia, Upravlenie), 2009, no. 7, pp. 7–12. (in Russ.)
  10. Furtat I., Fradkov A., Tsykunov A. Intern. J. of Robust and Nonlinear Control, 2014, no. 17(24), pp.2774–2784.
  11. Furtat I.B., Putov V.V. Proc. of the 2nd IFAC Workshop on Research, Education and Development of Unmanned Aerial Systems, Compiegne, France, November 20–22, 2013, no. 1(2), pp.276–282.
  12. Furtat I.B. Proc. of the 19th International Conference on Methods and Models in Automation and Robotics, MMAR 2014, Międzyzdroje, Poland, September 2–5, 2014, рp. 532–537.
  13. Furtat I.B. Proc. of the 11th IFAC International Workshop on Adaptation and Learning in Control and Signal Processing, University of Caen Basse-Normandie, Caen, France, July 3–5, 2013, рp. 227–232.
  14. Furtat I.B., Tsykunov A.M. Izv. vuzov. Priborostroenie, 2005, no. 7, pp. 15–19. (in Russ.)
  15. Furtat I.B., Fradkov A.L., Liberzon D. Automatica, 2015, no. 60, pp.239–244.