Abstract
The paper discusses optimal stabilization problem for the MagLev transport platform. The platform has a specific levitation system with four combined suspensions which include both electromagnets and permanent magnets. The presence of permanent magnets makes the problem nonlinear and incompletely controllable and causes the main challenge for this paper. In order to address it, we propose to optimize the controller with respect to the bunch of possible trajectories taking into account the mentioned nonlinearities. The controller has a dynamical structure and includes a Kalman filter with feedback on the platform gaps and electromagnet coil currents. The introduced approach allows operating in real-time even when platform parameters and mass change and in the presence of noise and disturbances. Optimization of stabilizing controller improves both energy costs and control accuracy.
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References
Amoskov, V.M.: Global computational models for analysis of electromagnetic transients to support ITER tokamak design and optimization. Fusion Eng. Des. 87, 1519–1532 (2012)
Amoskov, V.M., et al.: Computation technology based on KOMPOT and KLONDIKE codes for magnetostatic simulations in tokamaks. Plasma Devices Oper. 16(2), 89–103 (2008). https://doi.org/10.1080/10519990802018023
Amoskov, V.M., et al.: Simulation of electrodynamic suspension systems for levitating vehicles. III. continuous track systems. In: Vestnik of Saint Petersburg University Applied Mathematics Computer Science Control Processes, (4), pp. 4–21 (2015)
Amoskov, V.M., et al.: Simulation of electrodynamic suspension systems for levitating vehicles. iv. discrete track systems. In: Vestnik of Saint Petersburg University Applied Mathematics Computer Science Control Processes, vol. 3, pp. 4–17 (2016)
Amoskov, V.M., et al.: Modeling EMS maglev systems to develop control algorithms. Cybern. Phys. 7(1), 11–17 (2018)
Amoskov, V.M., et al.: Simulation of maglev eds performance with detailed numerical models. In: Vestnik of Saint Petersburg University Applied Mathematics Computer Science Control Processes, (4), pp. 286–301 (2018)
Amoskov, V.M., et al.: Magnetic model MMTC-2.2 of ITER tokamak complex. In: Vestnik of Saint Petersburg University Applied Mathematics Computer Science Control Processes, vol. 15(1) (2019). https://doi.org/10.21638/11702/spbu10.2019.101
Andreev, E.N., et al.: Combined electromagnetic suspensions with reduced energy consumption for levitation vehicles. Tech. Phys. 64(7), 1060–1065 (2019). https://doi.org/10.1134/s1063784219070041
Long, Z., Wang, Z., Cheng, H., Li, X.: A novel design of electromagnetic levitation system for high-speed maglev train. Transp. Syst. Technol. 4(3 suppl. 1), 212–224 (2018). https://doi.org/10.17816/transsyst201843s1212-224
Nagurka, M.L., Wang, S.K.: A superconducting maglev vehicle/guideway system with preview control: Part i–vehicle, guideway, and magnet modeling. J. Dyn. Syst. Meas. Control 119(4), 638–643 (1997). https://doi.org/10.1115/1.2802372
Nise, N.S.: Control System Engineering, 6th edn. Wiley (2011)
Nuchkrua, T., Parnichkun, M.: Identification and optimal control of quadrotor. Sci. Technol. Asia 17(4), 36–53 (2012)
Ovsyannikov, D., Zavadskiy, S.: Optimization approach to the synthesis of plasma stabilization system in tokamak ITER. Probl. Atom. Sci. Technol. 116(4), 102–105 (2018)
Ovsyannikov, D., Zavadskiy, S.: Pareto-optimal choice of controller dimension for plasma stabilization system. IFAC-PapersOnLine 51(32), 175 – 178 (2018). 17th IFAC Workshop on Control Applications of Optimization CAO 2018
Sarhang, A., Mohammadi, A.: A new method for quadrotor attitude estimation based on kalman-bucy filtering. Int. J. Mechatron. Electr. Comput. Technol. 170–186 (2014)
Talagaev, Y.: State estimation, robust properties and stabilization of positive linear systems with superstability constraints. Cybern. Phys. 6(1), 32–39 (2017)
Wang, S.K., Nagurka, M.L.: A superconducting maglev vehicle/guideway system with preview control: Part II–controller design and system behavior. J. Dyn. Syst. Measur. Control 119(4), 644–649 (1997). https://doi.org/10.1115/1.2802373
Wang, Z.L., Xu, Y.L., Li, G.Q., Yang, Y.B., Chen, S.W., Zhang, X.L.: Modelling and validation of coupled high-speed maglev train-and-viaduct systems considering support flexibility. Veh. Syst. Dyn. 57(2), 161–191 (2018). https://doi.org/10.1080/00423114.2018.1450517
Zavadskiy, S., Lepikhin, T.: Dynamics characteristics optimization for the UAV ensemble of motions. In: Convergent Cognitive Information Technologies, pp. 175–186. Springer International Publishing (2020). https://doi.org/10.1007/978-3-030-37436-5_16
Zavadskiy, S., Sharovatova, D.: Improvement of quadrocopter command performance system. In: 2015 International Conference "Stability and Control Processes" in Memory of V.I. Zubov (SCP). IEEE (2015). https://doi.org/10.1109/scp.2015.7342220
Zavadskiy, S.V.: Concurrent optimization of plasma shape and vertical position controllers for ITER tokamak. In: 2014 20th International Workshop on Beam Dynamics and Optimization (BDO). IEEE (2014). https://doi.org/10.1109/bdo.2014.6890102
Zavadsky, S., Ovsyannikov, A., Sakamoto, N.: Parametric Optimization for Tokamak Plasma Control System. In: World Scientific Series on Nonlinear Science Series B, pp. 353–358. World Scientific (2010). https://doi.org/10.1142/9789814313155_0054
Zavadsky, S.V., Ovsyannikov, D.A., Chung, S.L.: Parametric optimization methods for the Tokamak Plasma control problem. Int. J. Mod. Phys. A 24(05), 1040–1047 (2009). https://doi.org/10.1142/s0217751x09044486
Acknowledgements
Anna Golovkina and Sergey Zavadskiy acknowledge Saint Petersburg State University and JTI for organization of rearch visit to Nagoya University in March 2020 (projects ID: 52673807, 52673749). It brought fruitful discussions and promoted further collaborative research with Prof. Noboru Sakamoto on this topic.
Anna Golovkina also acknowledges Russian Science Foundation for grant (project No. 19-71-00074).
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Zavadskiy, S. et al. (2022). Optimization of a Real-Time Stabilization System for the MIMO Nonlinear MagLev Platform. In: Smirnov, N., Golovkina, A. (eds) Stability and Control Processes. SCP 2020. Lecture Notes in Control and Information Sciences - Proceedings. Springer, Cham. https://doi.org/10.1007/978-3-030-87966-2_31
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DOI: https://doi.org/10.1007/978-3-030-87966-2_31
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