Shakouri, P., Ordys, A. and Askari, M.R. (2012) Adaptive cruise control with stop&go function using the state-dependent nonlinear model predictive control approach. ISA Transactions, 51(5), pp. 622-631. ISSN (print) 0019-0578Full text not available from this archive.
In the design of adaptive cruise control (ACC) system two separate control loops - an outer loop to maintain the safe distance from the vehicle traveling in front and an inner loop to control the brake pedal and throttle opening position - are commonly used. In this paper a different approach is proposed in which a single control loop is utilized. The objective of the distance tracking is incorporated into the single nonlinear model predictive control (NMPC) by extending the original linear time invariant (LTI) models obtained by linearizing the nonlinear dynamic model of the vehicle. This is achieved by introducing the additional states corresponding to the relative distance between leading and following vehicles, and also the velocity of the leading vehicle. Control of the brake and throttle position is implemented by taking the state-dependent approach. The model demonstrates to be more effective in tracking the speed and distance by eliminating the necessity of switching between the two controllers. It also offers smooth variation in brake and throttle controlling signal which subsequently results in a more uniform acceleration of the vehicle. The results of proposed method are compared with other ACC systems using two separate control loops. Furthermore, an ACC simulation results using a stop&go scenario are shown, demonstrating a better fulfilment of the design requirements.
|Uncontrolled Keywords:||vehicle dynamic, adaptive cruise control, non-linear model predictive control, state-dependent linear model|
|Research Area:||General engineering and mineral and mining engineering|
|Faculty, School or Research Centre:||Faculty of Science, Engineering and Computing > School of Mechanical and Automotive Engineering|
|Depositing User:||Automatic Import Agent|
|Date Deposited:||18 Oct 2012 17:32|
|Last Modified:||15 Nov 2012 14:01|
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