In this paper a novel approach to autonomous steering systems is presented. A model predictive control (MPC) scheme is designed in order to stabilize a vehicle along a desired path while fulfilling its physical constraints. Simulation results show the benefits of the systematic control methodology used. In particular we show how very effective steering maneuvers are obtained as a result of the MPC feedback policy. Moreover, we highlight the trade off between the vehicle speed and the required preview on the desired path in order to stabilize the vehicle. The paper concludes with highlights on future research and on the necessary steps for experimental validation of the approach.
SUMMARYA model predictive control (MPC) approach for controlling an active front steering (AFS) system in an autonomous vehicle is presented. At each time step a trajectory is assumed to be known over a finite horizon, and an MPC controller computes the front steering angle in order to best follow the desired trajectory on slippery roads at the highest possible entry speed. We start from the results presented in (Int. (3)) and formulate the MPC problem based on successive online linearization of the nonlinear vehicle model (linear timevarying (LTV) MPC). We present a sufficient stability condition for such LTV MPC scheme. The condition is derived for a general class of nonlinear discrete time systems and results into an additional convex constraint to be included in the LTV MPC design.For the AFS control problem, we compare the proposed LTV MPC scheme with the LTV MPC scheme in (IEEE Trans. Contr. Syst. Technol. 2007; 15(3)) where stability has been enforced with an ad hoc constraint. Simulation and experimental tests up to 17 m=s on icy roads show the effectiveness of the LTV MPC formulation.
The practical feasibility of a WiFi transmissions based passive bistatic radar (PBR) is analyzed here. The required data processing steps are described including the adopted techniques for 1) the control of the signal autocorrelation function (ACF) usually yielding a high sidelobe level, and 2) the removal of the undesired signal contributions which strongly limit the useful dynamic range. The performance of the proposed techniques is firstly evaluated against simulated data generated according to the IEEE 802.11 Standards. Moreover the results are presented against a real data set collected by an experimental setup when using the conventional dual (reference and surveillance) channels PBR receiving scheme. This allows us to demonstrate the potentialities of a WiFi-based PBR for local area surveillance applications, where vehicles and people can be detected and tracked. Based on the digital nature of the exploited signals of opportunity, the attractive possibility is also investigated of avoiding the use of a dedicated receiving channel for the reference signal, by synthesizing it from the surveillance channel. This approach is shown to yield comparable performance with respect to the conventional PBR approach while yielding a remarkable saving in terms of system complexity
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