Application of Vehicle Dynamics' Active Control to a Realistic Vehicle Model

Dinçmen, Erkin; Acarman, Tankut

doi:10.1109/acc.2007.4282862

Cited by 7 publications

(4 citation statements)

References 4 publications

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“…As a result, q is assumed to vary in the range of q=[0.01,100]normalm2normals5 to compensate for not modelling the derivative of acceleration in the white noise jerk model of subsection III-C (see also [1, 9, 30, 11]).…”

Section: Environment Modelmentioning

confidence: 99%

State-of-the-art Versus Time-triggered Object Tracking in Advanced Driver Assistance Systems

Koplin

Elmenreich

2013

International Journal of Advanced Robotic Systems

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Most state-of-the-art driver assistance systems cannot guarantee that real-time images of object states are updated within a given time interval, because the object state observations are typically sampled by uncontrolled sensors and transmitted via an indeterministic bus system such as CAN. To overcome this shortcoming, a paradigm shift toward time-triggered advanced driver assistance systems based on a deterministic bus system, such as FlexRay, is under discussion.In order to prove the feasibility of this paradigm shift, this paper develops different models of a state-of-the-art and a time-triggered advanced driver assistance system based on multi-sensor object tracking and compares them with regard to their mean performance. The results show that while the state-of-the-art model is advantageous in scenarios with low process noise, it is outmatched by the time-triggered model in the case of high process noise, i.e., in complex situations with high dynamic.

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Section: Environment Modelmentioning

confidence: 99%

State-of-the-art Versus Time-triggered Object Tracking in Advanced Driver Assistance Systems

Koplin

Elmenreich

2013

International Journal of Advanced Robotic Systems

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“…If controller is designed in this situation, it will rely heavily on subjective factors, so the effect is not on the performance well. To analyze and improve the performance of the control system, determine the parameters of controller and design special control laws , a mathematical robot model should be established so that the robot can manipulate in a special environment (Feng et al, 2010;Dincmen and Acarman, 2007). In addition, it also can implement the motion simulation, analysis and development of control strategies.…”

Section: Introductionmentioning

confidence: 99%

Wind-driven land-yacht robot mathematical modeling and verification

Chen

Xie

Luo

et al. 2016

Industrial Robot: An International Journal

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Purpose – The purpose of this paper was to solve the shortage of carrying energy in probing robot and make full use of wind resources in the Antarctic expedition by designing a four-wheel land-yacht. Land-yacht is a new kind of mobile robot powered by the wind using a sail. The mathematical model and trajectory of the land-yacht are presented in this paper. Design/methodology/approach – The mechanism analysis method and experimental modeling method are used to establish a dual-input and dual-output mathematical model for the motion of land-yacht. First, the land-yacht’s model structure is obtained by using mechanism analysis. Then, the models of steering gear, servomotors and force of wing sail are analyzed and validated. Finally, the motion of land-yacht is simulated according to the mathematical model. Findings – The mathematical model is used to analyze linear motion and steering motion. Compared with the simulation results and the actual experimental tests, the feasibility and reliability of the proposed land-yacht modeling are verified. It can travel according to the given signal. Practical implications – This land-yacht can be used in the Antarctic, outer planet or for harsh environment exploration. Originality/value – A land-yacht is designed, and the contribution of this research is the development of a mathematical model for land-yacht robot. It provides a theoretical basis for analysis of the land-yacht’s motion.

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“…[15] The system under consideration is described by Equatons (2)-(4). It is assumed that both states can be measured.…”

Section: Lqr Controlmentioning

confidence: 99%

“…A combination of steer-by-wire and longitudinal control is presented in [15], where an extremum seeking controller is introduced to control the longitudinal tyre forces. For steer-by-wire an linear quadratic regulator (LQR) controller based on yaw-rate and vehicle slip angle is designed.…”

Section: Introductionmentioning

confidence: 99%

A robust control analysis for a steer-by-wire vehicle with uncertainty on the tyre forces

Sande

Zegelaar

Besselink

et al. 2016

Vehicle System Dynamics

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This paper proposes guidelines for controller design for steer-by-wire vehicles. The proposed controller removes the velocity dependency of the vehicle dynamics and accounts for the nonlinear characteristics of the lateral tyre force. Using an H ∞ approach, bounds on the closed loop sensitivity are presented, which results in guidelines for the controller design. Using the designed controller, simulations using a multi-body model show that the yaw dynamics of the vehicle are stabilised for extreme manoeuvres. ARTICLE HISTORY

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Application of Vehicle Dynamics' Active Control to a Realistic Vehicle Model

Cited by 7 publications

References 4 publications

State-of-the-art Versus Time-triggered Object Tracking in Advanced Driver Assistance Systems

State-of-the-art Versus Time-triggered Object Tracking in Advanced Driver Assistance Systems

Wind-driven land-yacht robot mathematical modeling and verification

A robust control analysis for a steer-by-wire vehicle with uncertainty on the tyre forces

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