Nonlinear Vehicle Dynamics Control - A Flatness Based Approach

Fuchshumer, Stefan; Schlacher, Kurt; Rittenschober, Thomas

doi:10.1109/cdc.2005.1583203

Cited by 49 publications

(38 citation statements)

References 6 publications

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“…In general, the problem common to both differential geometric and flatness-based approaches is the generation of reasonable and sufficiently differentiable reference trajectories. In recent publications [12][13][14][15], this question has not been explicitly treated.…”

Section: Introductionmentioning

confidence: 99%

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A new flatness-based control of lateral vehicle dynamics

Antonov

Fehn

Kugi

2008

Vehicle System Dynamics

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This paper presents a new concept for vehicle dynamics control (VDC). The control of the longitudinal vehicle dynamics is not discussed, since we are assuming that it is much slower and weakly coupled to the lateral and yawing dynamics. The actuators are considered to be the traction and the braking torques of the individual wheels and only the standard sensors of the common VDC system are used. A modular interface to the subordinate wheel control system is provided by choosing the yaw torque as a fictitious control input. The VDC system is designed by means of a two degrees-of-freedom control scheme. It comprises a flatness-based feedforward part and a stabilising feedback part. The reference trajectory generation is introduced for the flat output which is given by the lateral velocity of the vehicle. Thus an advantageous kind of body side-slip angle control is provided with the standard VDC system hardware. Extensive simulation studies show excellent performance of the designed control concept.

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Section: Introductionmentioning

confidence: 99%

“…Solutions by means of exact input-output linearisation are proposed in [12,13]. The differential flatness technique is adopted for vehicle dynamics control in [14,15]. Therein the centralised longitudinal tyre forces and the steer angle of the front wheels are chosen as control inputs.…”

Section: Introductionmentioning

confidence: 99%

A new flatness-based control of lateral vehicle dynamics

Antonov

Fehn

Kugi

2008

Vehicle System Dynamics

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“…For example, the acceleration of the front CO is independent of the rear lateral tire force [9]. The coordinates in a body-fixed frame of the velocity of the rear CO have been identified as flat outputs of a half-car model that incorporates wheel slip but does not consider load transfer [10]. More pertinent to the context of motion planning, the coordinates in an inertial frame of the position of the front CO have been identified as "pseudo-flat" outputs for the half-car model [11].…”

Section: Introductionmentioning

confidence: 99%

“…Firstly, we drop the simplifications to the half-car model adopted in [10], [11]: specifically, we allow normal load transfer between the front and rear tires -a technique used commonly by rally racing drivers to control the yaw dynamics [15] -and we consider as inputs the longitudinal slips of the front and rear tires instead of the longitudinal tire forces (as considered in [10], [11]). Manipulating the longitudinal tire slips (with thrust/brakes) is more realistic than manipulating longitudinal forces because these forces depend on the total tire slips, not the longitudinal slips alone.…”

Section: Introductionmentioning

confidence: 99%

“…Manipulating the longitudinal tire slips (with thrust/brakes) is more realistic than manipulating longitudinal forces because these forces depend on the total tire slips, not the longitudinal slips alone. Secondly, we map analytically the constraints on tire friction forces to equivalent constraints on the flat output trajectory: friction force constraints are ignored in similar earlier works [10], [11]. Thirdly, we provide a computationally efficient local steering algorithm for the half-car dynamical model, which may be applied independently in conjunction with motion planners different from that considered in this paper (RRT * ).…”

Section: Introductionmentioning

confidence: 99%

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Optimal motion planning with the half-car dynamical model for autonomous high-speed driving

Jeon

Cowlagi

Peters

et al. 2013

2013 American Control Conference

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Abstract-We investigate the application of the RRT * optimal motion planning algorithm to autonomous high-speed driving. Specifically, we discuss the implementation of RRT * for the halfcar dynamical model. To enable fast solutions of the associated local steering problem, we observe that the motion of a special point (viz., the front center of oscillation) can be modeled as a double integrator augmented with fictitious inputs. We first map the constraints on tire friction forces to constraints on these augmented inputs, which provides instantaneous, statedependent bounds on the curvature of geometric paths feasibly traversable by the front center of oscillation. Next, we map the vehicle's actual inputs to the augmented inputs. The local steering problem for the half-car dynamical model can then be transformed to a simpler steering problem for the front center of oscillation, which we solve efficiently by first constructing a curvature-bounded geometric path and then imposing a suitable speed profile on this geometric path. Finally, we demonstrate the efficacy of the proposed motion planner via numerical simulation results.

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Trajectory planning and tracking for four‐wheel steering vehicle based on differential flatness and active disturbance rejection controller

Xia

Lin

Zhang

et al. 2021

Adaptive Control & Signal

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To address the difficulties of under-actuation, nonlinearity, strong coupling, disturbances and measurement noise in four-wheel steering (4WS) vehicle tracking control, this paper presents an innovative control strategy based on differential flatness and linear active disturbance rejection controller (LADRC). The flatness property of 4WS vehicle is derived from a simplified dynamic model that ignores some complicated dynamics and external disturbances. The impact of these neglected components on the system is treated as part of the total-disturbance, which is estimated by the observer and compensated by LADRC. Three flatness-based control schemes, including feedback linearization controller with PID corrective term, traditional LADRC and LADRC with robust generalized proportional integral observer (RGPIO), are designed and investigated in this paper. Moreover, an overtaking scenario is selected as an application example for the tracking controllers, and the corresponding trajectory planner is designed.The tracking performances of these schemes for the overtaking trajectory are simulated on a three-degree-of-freedom dynamic model and a more complete dynamic model of the 4WS vehicle, respectively. Results show the effectiveness of these schemes, especially the excellent tracking performance of LADRC with RGPIO in the presence of strong external disturbances and measurement noise.

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Nonlinear Vehicle Dynamics Control - A Flatness Based Approach

Cited by 49 publications

References 6 publications

A new flatness-based control of lateral vehicle dynamics

A new flatness-based control of lateral vehicle dynamics

Optimal motion planning with the half-car dynamical model for autonomous high-speed driving

Trajectory planning and tracking for four‐wheel steering vehicle based on differential flatness and active disturbance rejection controller

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