Robust control for automated lane keeping against lateral disturbance

Vehicle Axles Disturbing Forces Estimation Based on Ant Colony Optimization Unscented Kalman Filter Algorithm

“…Thus it can be see that acquiring lateral disturbance accurately and timely is the most basic and important for vehicle automatic lane keeping control, this disturbance is mainly caused by the external environment such as lateral wind or road surface roughness and so on. When a vehicle drives in high speed, the continuous cumulative effects of this disturbance can make the vehicle steering wheel deflect tinyly and out of the reserved lane [2].…”

Estimation of Equivalent Input Disturbance Improves Vehicular Steering Control

“…A UTOMATIC steering control is a key element of intelligent transportation systems (see, for example, [1]- [8]). It involves two techniques: lane keeping, in which the steering control system tracks the center of the current lane, and lane changing, in which it steers in order to track a reference input for a given lateral motion.…”

“…For example, Lin et al [6] used a steady-state Kalman filter to estimate the lateral velocity of a vehicle and the magnitudes of external disturbances acting on it, Güvenç et al [7] used a disturbance observer to suppress external disturbances, and Yamamoto et al [8] devised a disturbance-estimation algorithm. However, each method has drawbacks: Lin et al [6] only considered step-type disturbances, it is difficult to tune the filter parameters in [7] because the filter design must guarantee both the causality of the estimator and the stability of the whole control system, and [8] requires the differentiation of measured outputs.…”

Vehicle Steering Control Based on Estimation of Equivalent Input Disturbance

“…Automatic steering control is a key element of intelligent transportation systems, and has been intensively investigated, e.g., (O'Brien et al, 1996;Byrne et al, 1998;Hatipoglu et al, 2003;Kim et al, 2001;Peng and Tomizuka, 1993;Lin et al, 2000;Güvenç et al, 2001;Yamamoto et al, 1999). It involves two techniques: lane keeping, for which the steering control system must track the center of the current lane; and lane changing, for which it must steer so as to track a reference input for a given lateral motion.…”

“…For example, (Lin et al, 2000) used a steady-state Kalman filter to estimate the lateral velocity of the vehicle and the magnitudes of external disturbances acting on the vehicle; (Güvenç et al, 2001) applied the disturbance observer approach to suppress external disturbances; and (Yamamoto et al, 1999) proposed a disturbance estimation algorithm. However, each method has drawbacks: (Lin et al, 2000) con- sidered only step-type disturbances; in (Güvenç et al, 2001), it is difficult to tune the filter parameters because the filter has to be designed to guarantee both the causality of the estimator and the stability of the whole control system; and (Yamamoto et al, 1999) requires the differentiation of measured outputs. This paper addresses the steering control problem for a straight road.…”