In this paper we present a comparison between two different vehicle lateral dynamic control approaches: a novel Model Predictive Control (MPC) and a Linear Quadratic Regulator (LQR). Both strategies are aimed at controlling yaw rate and side slip of the vehicle through differential braking and are designed on the basis of a two-degrees of freedom planar model. On the basis of the estimate of tire longitudinal forces we estimate the range of lateral forces which the tire can exert; these bounds, together with the rate limiter of the braking system, represent the hard constraints of MPC controller and the saturations of LQR controller. The results show the benefits to use MPC controller; in particular, when drives in conditions near the physical constraints borders, the MPC controller can produce a better distribution of braking forces because of information is formalized in optimization problem.
A comparison between LTV-MPC and LQR yaw rate-side slip controller / Meola, D.; Gambino, G.; Palmieri, G.; Glielmo, L.. - (2009). (Intervento presentato al convegno E-COSM'09, the 2009 IFAC Workshop on Engine and Powertrain Control, Simulation and Modeling tenutosi a RUEIL-MALMAISON, FRANCE nel NOVEMBER 30-DECEMBER 2) [10.3182/20091130-3-FR-4008.0045].
A comparison between LTV-MPC and LQR yaw rate-side slip controller
Glielmo L.
2009
Abstract
In this paper we present a comparison between two different vehicle lateral dynamic control approaches: a novel Model Predictive Control (MPC) and a Linear Quadratic Regulator (LQR). Both strategies are aimed at controlling yaw rate and side slip of the vehicle through differential braking and are designed on the basis of a two-degrees of freedom planar model. On the basis of the estimate of tire longitudinal forces we estimate the range of lateral forces which the tire can exert; these bounds, together with the rate limiter of the braking system, represent the hard constraints of MPC controller and the saturations of LQR controller. The results show the benefits to use MPC controller; in particular, when drives in conditions near the physical constraints borders, the MPC controller can produce a better distribution of braking forces because of information is formalized in optimization problem.I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.
