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Supervised Parameter Estimation for Road Vehicles, Mitigating Powertrain Induced Uncertainty.

, , and . IEEE Trans. Veh. Technol., 69 (7): 7000-7013 (2020)

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Deep Learning for Autonomous Vehicle Control: Algorithms, State-of-the-Art, and Future Prospects, , , and . Synthesis Lectures on Advances in Automotive Technology Morgan & Claypool Publishers, (2019)Robust adaptive finite-time parameter estimation and control of nonlinear systems., , , , and . ISIC, page 1014-1019. IEEE, (2011)Adaptive Observer-Based Parameter Estimation With Application to Road Gradient and Vehicle Mass Estimation., , , , and . IEEE Trans. Ind. Electron., 61 (6): 2851-2863 (2014)Supervised Parameter Estimation for Road Vehicles, Mitigating Powertrain Induced Uncertainty., , and . IEEE Trans. Veh. Technol., 69 (7): 7000-7013 (2020)Electric vehicles with individually controlled on-board motors: Revisiting the ABS design., , , and . ICM, page 323-328. IEEE, (2015)A Survey of Deep Learning Applications to Autonomous Vehicle Control, , , , and . (2019)cite arxiv:1912.10773Comment: 23 pages, 3 figures, Accepted in IEEE Transactions on Intelligent Transportation Systems.Computation of an optimal communication schedule in a nonlinear networked control system using sum-of-squares., , , and . Syst. Control. Lett., 61 (3): 387-396 (2012)A Survey of Deep Learning Applications to Autonomous Vehicle Control., , , , and . IEEE Trans. Intell. Transp. Syst., 22 (2): 712-733 (2021)Nonlinear observer design for discrete MIMO systems with unknown time delay., , , and . CDC, page 6137-6142. IEEE, (2009)