scholarly journals MPC Based Semi-active Suspension Control for Overtaking Maneuvers

Author(s):  
Tamás Hegedűs ◽  
Balázs Németh ◽  
Péter Gáspár

In this paper, the lateral and vertical control design is presented for autonomous vehicles. The vertical control of the vehicle is based on a semi-active suspension system. In the first step, a decision-making process is made. Based on the results of this algorithm an optimal trajectory is planned. Since the trajectory is known, the lateral accelerations can be computed for the given control horizon. In the second step, the vertical control is achieved, which uses the results of the trajectory planning algorithms. The control design is made by a Model Predictive Control (MPC), in which the sign and the maximum value of the additional force can be taken into account. The main goal in the vertical control process is vehicle roll angle minimization. The results of the algorithm are validated using a high fidelity vehicle dynamics simulation software, CarMaker.

2010 ◽  
Vol 118-120 ◽  
pp. 728-732
Author(s):  
Shu Wen Zhou ◽  
Si Qi Zhang ◽  
Guang Yao Zhao

Tractor semitrailers on high speed obstacle avoidance under emergency are likely to arise rollover or jack-knifing, which are serious risks for motorists. A dynamic stability analysis model of a three-axle tractor semitrailer vehicle is developed using the application tool. The linearized vehicle model is utilized to predict the dynamics state of the tractor semitrailer built in multibody dynamics simulation software. The lateral stability simulation for yaw rate following and anti-rollover has been performed on the dynamic model based on virtual prototyping. The results show that the lateral stability control based on tractor semitrailer proposed in this paper can stabilize the tractor semitrailer, rollover and jack-knifing can be prevented to a large extent.


Energies ◽  
2021 ◽  
Vol 14 (2) ◽  
pp. 517
Author(s):  
Dániel Fényes ◽  
Balázs Németh ◽  
Péter Gáspár

This paper presents a novel modeling method for the control design of autonomous vehicle systems. The goal of the method is to provide a control-oriented model in a predefined Linear Parameter Varying (LPV) structure. The scheduling variables of the LPV model through machine-learning-based methods using a big dataset are selected. Moreover, the LPV model parameters through an optimization algorithm are computed, with which accurate fitting on the dataset is achieved. The proposed method is illustrated on the nonlinear modeling of the lateral vehicle dynamics. The resulting LPV-based vehicle model is used for the control design of path following functionality of autonomous vehicles. The effectiveness of the modeling and control design methods through comprehensive simulation examples based on a high-fidelity simulation software are illustrated.


2011 ◽  
Vol 143-144 ◽  
pp. 69-73
Author(s):  
Xiao Bin Fan ◽  
Bing Xu Fan ◽  
Hui Gang Wang

An active suspension system has been proposed to improve the ride comfort. A quarter-car 2 degree-of-freedom system is designed and constructed on the basis of the concept of a four-wheel independent suspension. The aim of the work described in the paper was to illustrate the application of fuzzy Proportional Integration Derivative (PID) technique and Linear Quadratic Guass (LQG) control to the active suspension control system. The paper describes also the model and controller used in the study and discusses the vehicle response results obtained from a range of road input simulations. This work describes some comparison of active suspension fuzzy PID control and LQG control design method by MATLAB simulations. Simulation results show that the LQG controller achieved better performances in all carried-out investigations.


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