T. Zheng 's Advanced Model Predictive Control PDF

By T. Zheng

ISBN-10: 9533072989

ISBN-13: 9789533072982

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3. Simplified model of the parallel Hybrid Diesel Electric Vehicle. , 2008) for more details. Also, in this figure the engine Fast Model Predictive Control and its Application toControl Energy of Hybrid Electric Fast Model Predictive and its Management Application to Energy Management of Hybrid ElectricVehicles Vehicles 21 19 brake torque and the CIMG torque are estimated feedback signals. However, the details of the estimation approach are not included here. For the sake of simplicity, in this work we shall assume that both engine and CIMG output torques are available to measure.

D. & Anderson, J. (2010). Electric and Hybrid Cars: A History, 2nd Edition, McFarland & Co Inc. ; Wachter, A. T. (2000). Active set vs. interior point strategies for model predictive control, Proc. , Vol. 6, pp. 4229-4233. C. & Rizzoni, G. (2000). Mechatronic design and control of hybrid electric vehicles, IEEE/ASME Trans. On Mechatronics, 5(1): 58-72. ; Frasca, R. ; . (2007). Explicit Hybrid Model Predictive Control of the dc-dc Boost Converter, IEEE Power Electronics Specialists Conference, PESC 2007, Orlando, Florida, USA, pp.

The suggested approach was to identify a new control algorithm that in essence is a bridge between linear and nonlinear control. This resulted in the development of the MAMPC approach. Through simulation-based comparisons, it is shown that a MAMPC control algorithm is capable of delivering significantly improved control performance in comparison to a conventional NMPC, so that the difficulty of minimizing the performance function for nonlinear predictive control is avoided, which is usually carried by the use of NLP solved at each sampling time that generally is non-convex.

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Advanced Model Predictive Control by T. Zheng


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