A LQR-Based Controller with Estimation of Road Bank for Improving Vehicle Lateral and Rollover Stability via Active Suspension

Riofrio, Andres; Boada, María Jesús López

doi:10.3390/s17102318

Cited by 28 publications

(19 citation statements)

References 26 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Andres Riofrio [2] improved the vehicle rollover stability of active suspension through an LQR (linear quadratic regulator)-based controller with estimation of the road. Shuai Wang [3] discussed the active control of hydro-pneumatic suspension parameters of wheel loaders based on a fuzzy controller, which reduces the vertical vibration of the wheel loader. Sarel F [4] presented the possibility of using slow active suspension control to reduce the body roll and The rest of this paper is organized as follows.…”

Section: Introductionmentioning

confidence: 99%

Sliding Mode Switch Control of Adjustable Hydro-Pneumatic Suspension based on Parallel Adaptive Clonal Selection Algorithm

Zhou

Liu

et al. 2020

Applied Sciences

View full text Add to dashboard Cite

The hydro-pneumatic suspension, as a widely used suspension for heavy vehicles, has been taken seriously by researchers for a long time because it is crucial in terms of handling stability, riding comfort, and driving safety of these vehicles. Most previous studies only discussed the control of ride comfort or vehicle handling stability of the suspension system separately. This article proposes a dynamic switch control strategy which can switch between ride comfort and handling stability controllers under different road surfaces and driving conditions. The load transfer ratio (LTR) is selected as the switch performance index, and it is calculated through a six-degrees-of-freedom (6-DOF) model. The ride comfort and handling stability controller of the hydro-pneumatic suspension are designed based on the sliding mode control theory. The objective functions of parameters optimization of the sliding mode controller (SMC) are obtained by means of analytic hierarchy process (AHP), and then the controller's parameters are optimized by the parallel adaptive clonal selection algorithm (PACSA). The simulation results based on MATLAB/Simulink show that: (1) the PACSA performs better than a genetic algorithm in terms of the parameters optimization of the SMC; (2) the proposed switch control strategy can simultaneously improve the ride comfort and handling stability under several typical steering maneuvers and various road profiles compared with the conventional SMC-controlled suspension. thus reduce the rollover propensity. Awad, Magdy Naeem [5] designed a hydro-pneumatic energy harvesting suspension system based on a PID-PSO (particle swarm optimization) controller, which achieved the maximum riding comfort as the peak values of the acceleration.However, past research on adjustable hydro-pneumatic suspension mainly focused on the analysis of vehicles' ride comfort or handling stability under different operating conditions separately, because it is difficult to achieve optimality in both aspects of ride comfort and handling stability due to the conflicting relationship between them. Hence, it is urgent to concentrate on the dynamic switch control strategy between the vehicle's ride comfort and handling stability to meet different requirements of working conditions.As a powerful controller, the sliding mode controller (SMC) has a great use in control systems because of its good robustness to external disturbance and fast dynamic response. Pradhan, Subarni [6] applied a composite SMC for wind power extraction in a remotely located solar PV-wind hybrid system. Biricik, Samet [7] used an SMC three-phase dynamic voltage restorer with adaptive notch filter to protect sensitive loads. Farahmandrad, Maryam [8] designed a fuzzy SMC for a cooperative robotic system with uncertainty for handling an object. Abtahi, S. Mahdi [9] suppressed chaotic vibrations in a suspension system of vehicle dynamics based on the optimal SMC. Inspired by the previous studies mentioned above, an SMC is used to control the hydro-pneumatic suspension system...

show abstract

Section: Introductionmentioning

confidence: 99%

Sliding Mode Switch Control of Adjustable Hydro-Pneumatic Suspension based on Parallel Adaptive Clonal Selection Algorithm

Zhou

Liu

et al. 2020

Applied Sciences

View full text Add to dashboard Cite

show abstract

“…According to the National Highway Traffic Safety Administration (NHTSA), vehicle rollover occurred in about 3% of all passenger-vehicle crashes in 2002, and 33% of all fatalities had vehicle rollover as a contributor in 2014 [1]- [4]. Hence, advanced control algorithms for rollover prevention, such as Roll Stability Control (RSC) systems, are highly desired for vehicle systems [5], [6]. However, since closed-loop realizations are based on the knowledge of many roll angle and roll rate sensors, such systems are commercially unattractive due to the high cost of sensors for measuring these states.…”

Section: Introductionmentioning

confidence: 99%

Fuzzy Observer-Based Prescribed Performance Control of Vehicle Roll Behavior via Controllable Damper

Wang

Qin

et al. 2019

IEEE Access

View full text Add to dashboard Cite

This paper presents a novel observer-based control strategy to improve the vehicle roll behavior performance through magneto-rheological (MR) dampers under steering wheel input and various road excitation conditions. Since the vehicle roll with sudden steering input is an essential part of driving safety and possesses inherent nonlinearities, the full-car nonlinear Takagi-Sugeno (T-S) fuzzy model is first established to describe the vehicle roll dynamics considering nonlinear coupling dynamics of tire lateral force and MR damper force under road excitation input. Furthermore, a T-S model-based fuzzy observer is adapted to estimate the vehicle roll angle and roll rate. The stability conditions for the used T-S observer are calculated using linear matrix inequalities (LMIs), and the proposed observer is induced by solving the proposed LMI. Based on the Lyapunov function, sliding mode theory and prescribed performance function, a novel state observer-based prescribed performance control strategy is developed to constrain the controlled vehicle roll angle and roll rate state within the prescribed performance boundaries. Finally, the proposed techniques are validated through the J-turn and Fishhook tests conducted via a high-fidelity CarSim software platform. INDEX TERMS Vehicle roll dynamics, prescribed performance control, Takagi-Sugeno fuzzy observer, state estimation, vehicle system.

show abstract

“…Given the high number of vehicle-crash victims, it has been established as a priority to reduce this figure in the transportation sector. For this reason, many of the recent research works are focused on including different control systems in commercial vehicles in order to improve their stability, comfort and handling [ 1 , 2 , 3 ]. These systems need to know in every moment the dynamics of the vehicle through variables such as longitudinal and lateral accelerations, yaw rate, roll rate, roll angle and sideslip angle, among others, when different maneuvers are performed, in order to actuate by means of the systems in the vehicle (brakes, steering, suspension) and, in this way, achieving a good behavior.…”

Section: Introductionmentioning

confidence: 99%

VEHIOT: Design and Evaluation of an IoT Architecture Based on Low-Cost Devices to Be Embedded in Production Vehicles

Redondo

Prieto-González

Guzmán

et al. 2018

Sensors

Self Cite

View full text Add to dashboard Cite

Nowadays, the current vehicles are incorporating control systems in order to improve their stability and handling. These control systems need to know the vehicle dynamics through the variables (lateral acceleration, roll rate, roll angle, sideslip angle, etc.) that are obtained or estimated from sensors. For this goal, it is necessary to mount on vehicles not only low-cost sensors, but also low-cost embedded systems, which allow acquiring data from sensors and executing the developed algorithms to estimate and to control with novel higher speed computing. All these devices have to be integrated in an adequate architecture with enough performance in terms of accuracy, reliability and processing time. In this article, an architecture to carry out the estimation and control of vehicle dynamics has been developed. This architecture was designed considering the basic principles of IoT and integrates low-cost sensors and embedded hardware for orchestrating the experiments. A comparison of two different low-cost systems in terms of accuracy, acquisition time and reliability has been done. Both devices have been compared with the VBOX device from Racelogic, which has been used as the ground truth. The comparison has been made from tests carried out in a real vehicle. The lateral acceleration and roll rate have been analyzed in order to quantify the error of these devices.

show abstract

A LQR-Based Controller with Estimation of Road Bank for Improving Vehicle Lateral and Rollover Stability via Active Suspension

Cited by 28 publications

References 26 publications

Sliding Mode Switch Control of Adjustable Hydro-Pneumatic Suspension based on Parallel Adaptive Clonal Selection Algorithm

Sliding Mode Switch Control of Adjustable Hydro-Pneumatic Suspension based on Parallel Adaptive Clonal Selection Algorithm

Fuzzy Observer-Based Prescribed Performance Control of Vehicle Roll Behavior via Controllable Damper

VEHIOT: Design and Evaluation of an IoT Architecture Based on Low-Cost Devices to Be Embedded in Production Vehicles

Contact Info

Product

Resources

About