SYNTHESIS OF CONTROL FOR GROUP OF AUTONOMOUS ROBOTS WITH PHASE CONSTRAINTS BY MULTI-LAYER NETWORK OPERATOR WITH PRIORITIES

Abstract


We consider a control system synthesis problem for the small group of autonomous robots with state constraints and several possible initial conditions. The main control task for team of robots is to move the robots out of some current position to the specified terminal position without colliding with each other. Typically, the control synthesis for the group of robots consists of two phases: stabilization of the robot with respect to some point of the state space and the design of optimal trajectories. The trajectories must ensure that the robots move from the initial states to certain states of the terminal set without collisions. To avoid collision, the control system uses priorities based, for example, on a distance between the robot and its end position. Since there are phase constraints, ordinary stabilization of robots cannot ensure the safe movement of robots from different initial conditions to the terminal positions. The paper presents our new approach to solving the stabilization problem with phase constraints by multi-layer network operator. We show an example of synthesis of control for the group of four robots.

Askhat I Diveev

aidiveev@mail.ru
RUDN University, Engineering Academy
Miklukho-Maklaya str., 6, Moscow, Russia, 117198

Doctor of technical sciences, professor, chief of sector of Cybernetic problems

Elizaveta Yu Shmalko

e.shmalko@gmail.com
RUDN University, Engineering Academy
Miklukho-Maklaya str., 6, Moscow, Russia, 117198

candidate of technical sciences, senior researcher

  • Arutyunov, A.V., Karamzin, D.Yu. and Pereira, F.L. Maximum Principle in Problems with Mixed Constraints under Weak Assumptions of Regularity, J. of Optimization. Vol. 59. Issue 7. 2010. Pp. 1067-1083.
  • Kaviczky T., Borelli F., Fregene K., Godbole D. and Balas G.J. Decentralized Receding Horizon Control and Coordination of Autonomous Vehicle Formations, IEEE Trans. on Cont. Syst. Tech., 2008. V. 16, 1. Pp. 19-33.
  • O’Neill, M. and Ryan, C. Grammatical Evolution. IEEE Trans. Evol. Comput. 5, 2001. Pp. 349-358.
  • Zelinka, I. Analytic programming by means of new evolutionary algorithms. In: Proceedings of 1st International Conference on New Trends in Physics’01, Brno, Czech Republic, 2001. Pp. 210-214.
  • Diveev, A.I. and Sofronova, E.A. Application of network operator method for synthesis of optimal structure and parameters of automatic control system. In: Proceedings of 17-th IFAC World Congress, Seoul, 2008, 05.07.2008 - 12.07.2008. Pp. 6106-6113.
  • Diveev, A.I. and Sofronova, E.A. Numerical method of network operator for multi-objective synthesis of optimal control system. In: Proceedings of Seventh International Conference on Control and Automation (ICCA’09) Christchurch, New Zealand, December 9-11, 2009. Pp. 701- 708.
  • Diveev, A.I. A Numerical Method for Network Operator for Synthesis of a Control System with Uncertain Initial Values. Journal of Computer and Systems Sciences International. 2012. Vol. 51. No. 2. Pp. 228-243.
  • Koza, J.R., Keane, M.A., Yu, J., Bennett, F.H., Mydlowec, W., and Stiffelman, O. Automatic Synthesis of both the Topology and Parameters for a Robust Controller for a Non-Minimal Phase Plant and a Three-Lag Plant by Means of Genetic Programming In Proceedings of the 38 Conference on Decision & Control Phoenix, Arizona USA - December 1999. Pp. 5292-5300.
  • Koza, J.R., Keane, M.A., Yu, J., Mydlowec, W., and Bennett, F.H. Automatic Synthesis of Both the Control Law and Parameters for a Controller for a Three-Lag Plant with Five-Second Delay using Genetic Programming and Simulation Techniques. In Proceedings of the American Control Conference Chicago, Illinois June 2000. Pp. 453-458.
  • Yu, J., Keane, M.A., and Koza, J.R. Automatic Design of Both Topology and Tuning of a Common Parameterized Controller for Two Families of Plants using Genetic Programming. In Proceedingsof the 2000 IEEE International Symposium on Computer-Aided Control System Design Anchorage, Alaska, USA September 25-27, 2000. Pp. 234-242.
  • Cpałka, K., Łapa, K, and Przybył, A. A New Approach to Design of Control Systems Using Genetic Programming. Information technology and control. 2015. V. 44. No. 4. Pp. 433-442.
  • Diveev A.I. Small Variations of Basic Solution Method for Non-numerical Optimization. In Proceedings of 16th IFAC Workshop on Control Applications of Optimization, October 6th-9th, 2015. Garmisch-Partenkirchen. Pp. 28-33.
  • Diveev, A.I. and Shmalko, E.Yu. Optimal Control Synthesis for Group of Robots by Multilayer Network Operator. In Proceedings of 3rd International Conference on Control, Decision and Information Technologies (CoDIT’16). St. Paul’s Bay - Malta on April 6-8, 2016. Pp. 077-082.
  • Diveev, A.I. and Shmalko, E.Yu. Optimal Motion Control for Multi-Robot System by Multilayer Network Operator. In Proceedings of the 11th IEEE Conference on Industrial Electronics and Applications (ICIEA 2016), 5-7 June 2016, Hefei, China. Pp. 2164-2169.
  • Дивеев А.И., Софронова Е.А., Шмалько Е.Ю. Эволюционные численные методы решения задачи синтеза системы управления группой роботов // Информационные и математические технологии в науке и управлении. Иркутск: ИСЭМ СО РАН, 2016. № 3. С. 11-24. [Evolutsyonnye chislennye metody reshenia zadachi sinteza sistemy upravlenia gruppoi robotov = Evolutionary computational methods to solve problems of control system synthesis for groups of robots // Informacionnye i matematicheskie tehnologii v nauke i upravlenii = Information and mathematical technologies in science and management. Publ. Irkutsk: Melentiev Energy Systems Institute SB RAS, 2016. № 3. S. 11-24].

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