Abstract
In this paper, a robust optimal tracking strategy is presented for linear system with systems uncertainty and bounded disturbance. Firstly, an integral sliding mode control policy is designed to guarantee system trajectories tend to a defined sliding mode surface and the influence of system uncertainty is eliminated. Then the robust tracking control problem of original system is transformed into the \(H_\infty \) control problem of an auxiliary error system. Furthermore, an off-policy integral reinforcement learning (IRL) algorithm based \(H_\infty \) controller is designed, where the optimal tracking performance is guaranteed under the adverse effect of external disturbance. Finally, simulation test for near space vehicle (NSV) attitude model is introduced to verify the effectiveness of the proposed strategy.
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Xia, R., Wu, J., Shen, H. (2023). Integral Reinforcement Learning-Based \(H_\infty \) Tracking Control for Uncertain Linear Systems and Its Application. In: Ren, Z., Wang, M., Hua, Y. (eds) Proceedings of 2021 5th Chinese Conference on Swarm Intelligence and Cooperative Control. Lecture Notes in Electrical Engineering, vol 934. Springer, Singapore. https://doi.org/10.1007/978-981-19-3998-3_97
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DOI: https://doi.org/10.1007/978-981-19-3998-3_97
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