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A Real-Time Model Predictive Control Approach for Autonomous Active Steering

Paolo Falcone (Institutionen för signaler och system, Mekatronik) ; Francesco Borrelli ; Jahan Asgari ; H. Eric Tseng ; Davor Hrovat
First IFAC International workshop on NMPC for Fast Systems, Grenoble, France, October 2006 (2006)
[Konferensbidrag, refereegranskat]

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.

Denna post skapades 2008-04-13. Senast ändrad 2017-06-28.
CPL Pubid: 70076


Institutioner (Chalmers)

Institutionen för signaler och system, Mekatronik (2005-2017)



Chalmers infrastruktur