A Real-Time Model Predictive Control Approach for Autonomous Active Steering
Paper i proceeding, 2006

The problem of controlling the front steering to stabilize a vehicle along a desired path is tackled in this paper. Although a Non-LinearModel Predictive Control (NLMPC) approach can achieve good performance and constraints fulfillment, its computational burden does not allow a real-time implementation. In order to decrease the complexity of the controller, in this paper we propose a suboptimal MPC scheme based on successive on-line linearizations of the non-linear vehicle model. The method stems from an accurate analysis of the vehicle nonlinearities, the constraints and the performance index in the optimal control problem. The simulation results show a significant reduction of the controller complexity, with a small loss of performances respect to a NLMPC controller. The suboptimal MPC control policy is compared to the control policy of a robot driver from Ford Motor Company.We show that better performance can be achieved with a smaller control effort, without violating vehicle physical constraints, by using a systematic control design procedure.

Författare

Paolo Falcone

Chalmers, Signaler och system, System- och reglerteknik, Mekatronik

Francesco Borrelli

Jahan Asgari

H. Eric Tseng

Davor Hrovat

First IFAC International workshop on NMPC for Fast Systems, Grenoble, France, October 2006

Ämneskategorier

Reglerteknik

Mer information

Skapat

2017-10-08