Abstract
This article studies formation control consideration of cooperative path following problem in a group of multiple Surface Vehicles (SVs). A proposed formation control protocol that contains optimal control problem in two subsystems of each SV with Model Predictive Control (MPC) and Approximate/Adaptive reinforcement Learning (ARL) Controller. The MPC is developed for nonlinear sub-system of SV with the tracking performance to be guaranteed by considering an appropriate optimization problem. Moreover, RL control design is carried out for time-varying sub-system by indirect method. Finally, the proposed control protocol is demonstrated by simulation result to show the effectiveness of this control protocol.
Supported by School of Electrical and Electronic Engineering, Hanoi University of Science and Technology.
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References
Dai, S.-L., Lu, K., Jin, X.: Fixed-time formation control of unicycle-type mobile robots with visibility and performance constraints. IEEE Trans. Ind. Electron. 68(12), 12 615–12 625 (2020)
Dai, S.-L., Lu, K., Fu, J.: Adaptive finite-time tracking control of nonholonomic multirobot formation systems with limited field-of-view sensors. IEEE Trans. Cybernet. 52, 10695–10708 (2021)
Huang, Y., Wu, D., Li, L., Feng, N.: Event-triggered cooperative path following control of multiple underactuated unmanned surface vehicles with complex unknowns and actuator saturation. Ocean Eng. 249, 110740 (2022)
Dao, P.N., Nguyen, H.Q.: Robust model predictive kinematic tracking control with terminal region for wheeled robotic systems. Automatika časopis za automatiku, mjerenje, elektroniku, računarstvo i komunikacije 62(3-4), 513–519 (2021)
Dao, P.N., Liu, Y.-C.: Adaptive reinforcement learning in control design for cooperating manipulator systems. Asian J. Control 24, 1088–1103 (2022)
Pham, T.L., Dao, P.N., et al.: Disturbance observer-based adaptive reinforcement learning for perturbed uncertain surface vessels. ISA Trans. 130, 277–292 (2022)
Vu, V.T., Tran, Q.H., Pham, T.L., Dao, P.N.: Online actor-critic reinforcement learning control for uncertain surface vessel systems with external disturbances. Int. J. Control Autom. Syst. 20(3), 1029–1040 (2022)
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Cao, T.T., Vu, M.H., Nguyen, V.C., Nguyen, T.A., Dao, P.N. (2023). Formation Control Scheme of Multiple Surface Vessels with Model Predictive Technique. In: Nguyen, T.D.L., Verdú, E., Le, A.N., Ganzha, M. (eds) Intelligent Systems and Networks. ICISN 2023. Lecture Notes in Networks and Systems, vol 752. Springer, Singapore. https://doi.org/10.1007/978-981-99-4725-6_39
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DOI: https://doi.org/10.1007/978-981-99-4725-6_39
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