Application of Artificial Neural Networks for Active Roll Control Based on Actor-Critic Reinforcement Learning
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Springer International Publishing
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http://link.springer.com/content/pdf/10.1007/978-3-030-55867-3_4
Reference15 articles.
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2. Boada, M., Boada, B., Gauchia Babe, A., Calvo, J., Diaz, V.: Active roll control using reinforcement learning for a single unit heavy vehicle. Int. J. Heavy Veh. Syst. 16(4), 412–430 (2009)
3. Fu, Z.-J., Li, B., Ning, X.-B., Xie, W.-D.: Online Adaptive optimal control of vehicle active suspension systems using single-network approximate dynamic programming. Math. Probl. Eng. 2017 (2017). 9 p.
4. Bahr, M., Reicherts, S., Sieberg, P., Morss, L., Schramm, D.: Development and validation of active roll control based on actor-critic neural network reinforcement learning. In: Proceedings of the 9th International Conference on Simulation and Modeling Methodologies, Technologies and Applications, pp. 36–46. SCITEPRESS, Prague (2019)
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