Vehicle longitudinal motion modeling for nonlinear control

Majdoub, Khalid El; Giri, F.; Ouadi, Hamid; Dugard, Luc; Chaoui, F.Z.

doi:10.1016/j.conengprac.2011.09.005

Cited by 53 publications

(21 citation statements)

References 14 publications

Supporting

Mentioning

Contrasting

Unclassified

Order By: Relevance

“…Given that K 1 is always positive and (8), it follows that K 2 also has to be positive. If the resulting force in Equation (7) is greater than zero (positive), then coefficient K 2 is defined by (7) and marked as K 2 +. This leads to a set of equations describing a particular type of motion.…”

Section: Model Solutionmentioning

confidence: 99%

See 1 more Smart Citation

Closed-Form Solution of a Special Case of a Vehicle Longitudinal Motion Model

2019

View full text Add to dashboard Cite

One of the most common approaches in modern engineering research, including vehicle dynamics, is to formulate an accurate, but typically complex, mathematical model of a system or phenomenon and then use a software package to solve it. Typically, the solution is obtained in the form of a large data set, which may be difficult to analyse and interpret. This paper represents a purely theoretical analysis of a special case of vehicle longitudinal motion. Starting from a simplified mathematical model, a set of transcendental equations was derived that represents the exact solution of the model (i.e., in a closed form). The equations are analysed and interpreted in terms of what is their physical meaning. Although the equations derived here have only limited application in studying real world problems, due to the simplicity of the mathematical model, they offer a deeper insight into the nature of vehicle longitudinal motion.

show abstract

Section: Model Solutionmentioning

confidence: 99%

“…One approach to modelling vehicle longitudinal motion is presented in [7], although the focus of the paper is on the control design. Another approach is shown in [8], where air drag and tyre rolling resistance are ignored for simplicity, while focusing on the stability of longitudinal and lateral motion.…”

Section: Introductionmentioning

confidence: 99%

Closed-Form Solution of a Special Case of a Vehicle Longitudinal Motion Model

2019

View full text Add to dashboard Cite

show abstract

“…also applied longitudinal dynamic model in their nonlinear controller. [7] However, practically it is difficult to obtain the accurate vehicle dynamics parameters. System identification of the vehicle dynamics requires extensive experiment tests on the vehicle.…”

Section: Introductionmentioning

confidence: 99%

Longitudinal control of an intelligent vehicle using particle swarm optimization based sliding mode control

Thanok

Parnichkun

2015

Advanced Robotics

View full text Add to dashboard Cite

This paper focuses on the design of longitudinal controller for an intelligent vehicle which was built at Asian Institute of Technology based on sliding mode control. The proposed controller uses particle swarm optimization (PSO) for optimal tuning of sliding surface and controller gain in the sliding mode controller (SMC). The longitudinal control is conducted via controlling of throttle value angle using PSO-based SMC on the simplified first-order linear model of the intelligent vehicle and controlling of brake force using fuzzy logic. In order to achieve the desired headway time, integration of throttle valve angle control and brake force control is required. To obtain the optimal parameters of SMC, two equations velocity updating and position updating are applied. Firstly, the performance of proposed controller is evaluated by using MATLAB simulation to compare with conventional PD controller. Finally, the experimental results show that the proposed PSO-based SMC can perform efficiently in longitudinal control of the intelligent vehicle.

show abstract

“…Dentre as várias técnicas propostas na literatura podem-se destacar as baseadas em inteligência artificial (IA) que utilizam redes neurais artificias (RNA), sistemas fuzzy e algorítimos genéticos [2], [3], [4], [5]. Estas técnicas proporcionam um ganho de performance ao sistema de controle quando comparadas as técnicas tradicionais principalmente nos casos em que modelo longitudinal do veículo considera os efeitos não lineares do atrito aerodinâmico e do atrito de rolamento [6], [7].…”

Section: Introductionunclassified

Rede Neural Auto-Regressiva Com Entradas Exógenas (NARX) Aplicada ao Controle de Velocidade em Veículos Elétricos

Fonseca¹,

Almeida²,

Fernandes³

2015

Anais Do 12. Congresso Brasileiro De Inteligência Computacional

View full text Add to dashboard Cite

Resumo-Este artigo propõe uma estratégia de controle de velocidade para veículos equipados com motores elétricos de corrente contínua e ímã permanente (PMDC-Permanent Magnet DC). Esta estratégia tem como base um controlador nãolinear auto-regressivo com entradas exógenas (NARX-Nonlinear Autoregressive Exogenous) baseado em Redes Neurais Artificiais (RNA) do Tipo Perceptron de Multiplas Camadas (MLP-Multilayer Perceptron) treinado com algoritmo da retropropagação (BP-Backpropagation). O controlador neural atua de forma direta no PMDC, tendo como entrada o erro entre a velocidade atual e a velocidade de referência do veículo, estados passados da saída e finalmente o ângulo de inclinação longitudinal do veículo. Resultados obtidos, a partir de simulações para várias situações de percurso, são apresentados e mostram a eficiência do controlador proposto.

show abstract

Vehicle longitudinal motion modeling for nonlinear control

Cited by 53 publications

References 14 publications

Closed-Form Solution of a Special Case of a Vehicle Longitudinal Motion Model

Closed-Form Solution of a Special Case of a Vehicle Longitudinal Motion Model

Longitudinal control of an intelligent vehicle using particle swarm optimization based sliding mode control

Rede Neural Auto-Regressiva Com Entradas Exógenas (NARX) Aplicada ao Controle de Velocidade em Veículos Elétricos

Contact Info

Product

Resources

About