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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.

4. Evolution of the set point, the output and the control (NMPC): constrained case Fig. 5. Evolution of the set point, the output and the control (MAMPC): constrained case Fast Nonlinear Model Predictive Control using Second Order Volterra Models Based Multi-agent Approach 41 It is clear from this figures that the new strategy of control leads to satisfactory results with respect to set-point changes. Indeed, the tracking error is reduced and with a smooth control action. It is shown that NMPC also gives consistently a good performance for the range examined.

Of the International Conference on Engineering Optimization, EngOpt 2008, Rio de Janeiro, Brazil, June 2008. A. A. (2002). Fuzzy logic control for parallel hybrid vehicles, IEEE Trans. on Control Systems Technology 10(3): 460-468. Sciarretta, A. & Guzzella, L. (2007). Control of hybrid electric vehicles, IEEE Control Systems Magazine pp. 60-70. Sontag, E. (1981). Nonlinear regulation: The piecewise linear approach, IEEE Trans. on Automatic Control 26(2): 346-358. 28 26 Advanced Model Predictive Control Will-be-set-by-IN-TECH Steinmaurer, G.

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