Multi objective H active anti-roll bar control for heavy vehicles

Tấn, Vũ Văn; Sename, Olivier; Dugard, Luc; Gáspár, Péter

doi:10.1016/j.ifacol.2017.08.2071

Cited by 9 publications

(7 citation statements)

References 15 publications

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“…During normal movement, the pitch and roll angles both reach small values, so the displacement of the sprung mass at each wheel z i is determined as follows: Equations from (1) to (8) are the dynamics equations of the full car model in the vertical direction, and they are converted to the state-space representation as follows [25]:…”

Section: Full Vertical Car Modelmentioning

confidence: 99%

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Designing a Kalman–Bucy State Estimator for a Full Vertical Car Model

Hung

Tấn

2023

Mathematical Problems in Engineering

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Currently, mechatronic systems are commonly used in automotive control systems to improve ride comfort and road safety characteristics. In these control systems, the sensors used to determine the input signals of controllers are very important to help the calculation process and give the correct control output signals for actuators. However, not all input signals can be easily measured directly by sensors or their cost is too high. This paper proposes one using the Kalman–Bucy estimator to estimate the state variables of a two-axle car to study the automotive suspension system. The disturbance input is the road profile at the four tires, while the car speed is considered from 40 km/h to 120 km/h. This research only uses four signals, namely, the vertical displacement of the four unsprung masses, through the estimator it can determine 14 variables of the vector state of the general vertical model of the car. The advantage of this research is that it is possible to reduce the number of the sensors but still ensure that the necessary input signals are obtained for studying the full car model. The signal estimation through some sensors available on the car is necessary for practice. Survey results show that the signal quantification through the Kalman–Bucy estimator unit has an accuracy of over 96% compared to the original car’s signals.

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Section: Full Vertical Car Modelmentioning

confidence: 99%

“…. [25,27]. Te Kalman estimator is a discrete-time flter, using a predictive-correction estimation algorithm, used as a kinematic system model to predict state values and a measurement model for correction this prediction.…”

Section: Kalman-bucy Estimator Design For General Vibration Model Of ...mentioning

confidence: 99%

Designing a Kalman–Bucy State Estimator for a Full Vertical Car Model

Hung

Tấn

2023

Mathematical Problems in Engineering

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“…Besides the traditional method, which is selected based on the experience of the designer, the genetic algorithm can be used to determine the weighting functions. 26,27 The weighting functions matrix for the performance output is chosen as W z = diag½W z1 W z2 . We emphasise here that the purpose of the weighting functions is to keep the control input, normalised load transfer, lateral acceleration and suspension roll angle as small as possible over the desired frequency range up to 4 rad/s, which represents the limited bandwidth of the driver.…”

Section: Performance Specifications For the Hn Control Designmentioning

confidence: 99%

Improving roll stability of tractor semi-trailer vehicles by using H∞ active anti-roll bar control system

Tấn

Sename

Gáspár

2021

Proceedings of the Institution of Mechanical Engineers, Part D:

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Tractor semi-trailers are increasingly playing an important role in freight transportation worldwide. Although most tractor semi-trailers are equipped with a passive anti-roll bar system, however accidents involving this type of vehicle are still frequent and have serious consequences. This paper presents an H∞ controller design for an active anti-roll bar system in order to enhance the roll stability of a tractor semi-trailer with the torque control generated at all axles. The considered performance outputs include the lateral acceleration, the normalised load transfer for both tractor and semi-trailer, as well as the magnitude of the torque control to avoid the actuator’s saturation. The effectiveness of the proposed method is evaluated in the frequency domain via the transfer function magnitude from the steering angle to the survey signals, and in the time domain through the nonlinear vehicle model of TruckSim® software. The evaluation results show that the roll stability of the tractor semi-trailer using the H∞ active anti-roll bar system has improved by more than 20% compared to a passive vehicle.

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“…When we impose such optimal desired performance presented by the weighting functions, the H∞ controller design process maybe failed to find a suitable controller for such performance, the solution is that we have to demean the performance specification. Nature-inspired stochastic optimization tools have been used in many works to get the weighting functions' optimal parameters with the existing H∞ controller, for the LTI system (Alfaro-Cid et al, 2008), for a polytopic-LPV system (Do et al, 2011;Vu et al, 2017), and for an LFT-LPV system (Hasseni and Abdou, 2020). These tools are more required in the multi-objective problem, which is very common in the controller designing process.…”

Section: Challenges and Contributionsmentioning

confidence: 99%

Robust LFT-LPV H∞ Control of an Underactuated Inverted Pendulum on a Cart with Optimal Weighting Functions Selection by GA and ES

Hasseni

Abdou

2020

Acta Mechanica Et Automatica

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This article investigates the robust stabilization and control of the inverted pendulum on a cart against disturbances, measurement noises, and parametric uncertainties by the LFT-based LPV technique (Linear-Fractional-Transformation based Linear-Parameter-Varying). To make the applying of the LPV technique possible, the LPV representation of the inverted pendulum on a cart model is developed. Besides, the underactuated constraint of this vehicle is overcome by considering both degrees of freedom (the rotational one and the translational one) in the structure. Moreover, the selection of the weighting functions that represent the desired performance is solved by two approaches of evolutionary algorithms; Genetic Algorithms (GA) and Evolutionary Strategies (ES) to find the weighting functions’ optimal parameters. To validate the proposed approach, simulations are performed and they show the effectiveness of the proposed approach to obtain robust controllers against external signals, as well as the parametric uncertainties.

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Multi objective H active anti-roll bar control for heavy vehicles

Cited by 9 publications

References 15 publications

Designing a Kalman–Bucy State Estimator for a Full Vertical Car Model

Designing a Kalman–Bucy State Estimator for a Full Vertical Car Model

Improving roll stability of tractor semi-trailer vehicles by using H∞ active anti-roll bar control system

Robust LFT-LPV H∞ Control of an Underactuated Inverted Pendulum on a Cart with Optimal Weighting Functions Selection by GA and ES

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