scholarly journals GALQR Optimal Control Method and Applying in the Active Suspension System

2007 ◽  
Author(s):  
Guosheng Zhang
Keyword(s):  
Optimal Control ◽  
Control Method ◽  
Active Suspension ◽  
Suspension System ◽  
Optimal Control Method

scholarly journals Online Adaptive Optimal Control of Vehicle Active Suspension Systems Using Single-Network Approximate Dynamic Programming

2017 ◽  
Vol 2017 ◽  
pp. 1-9 ◽  
Author(s):  
Zhi-Jun Fu ◽  
Bin Li ◽  
Xiao-Bin Ning ◽  
Wei-Dong Xie
Keyword(s):  
Optimal Control ◽  
Dynamic Programming ◽  
Approximate Dynamic Programming ◽  
Control Method ◽  
Active Suspension ◽  
Suspension System ◽  
Lyapunov Theory ◽  
Adaptive Optimal Control ◽  
Suspension Systems ◽  
Optimal Control Method

In view of the performance requirements (e.g., ride comfort, road holding, and suspension space limitation) for vehicle suspension systems, this paper proposes an adaptive optimal control method for quarter-car active suspension system by using the approximate dynamic programming approach (ADP). Online optimal control law is obtained by using a single adaptive critic NN to approximate the solution of the Hamilton-Jacobi-Bellman (HJB) equation. Stability of the closed-loop system is proved by Lyapunov theory. Compared with the classic linear quadratic regulator (LQR) approach, the proposed ADP-based adaptive optimal control method demonstrates improved performance in the presence of parametric uncertainties (e.g., sprung mass) and unknown road displacement. Numerical simulation results of a sedan suspension system are presented to verify the effectiveness of the proposed control strategy.

The human-like trajectory planning for autonomous vehicles based on optimal control in a test track environment

2021 ◽  
pp. 095440702110090
Author(s):  
Xing Xu ◽  
Minglei Li ◽  
Feng Wang ◽  
Ju Xie ◽  
Xiaohan Wu ◽  
...  
Keyword(s):  
Optimal Control ◽  
Autonomous Vehicles ◽  
Optimal Trajectory ◽  
Control Method ◽  
Autonomous Vehicle ◽  
Trajectory Data ◽  
Test Track ◽  
Optimal Control Method ◽  
The Future ◽  
On The Road

A human-like trajectory could give a safe and comfortable feeling for the occupants in an autonomous vehicle especially in corners. The research of this paper focuses on planning a human-like trajectory along a section road on a test track using optimal control method that could reflect natural driving behaviour considering the sense of natural and comfortable for the passengers, which could improve the acceptability of driverless vehicles in the future. A mass point vehicle dynamic model is modelled in the curvilinear coordinate system, then an optimal trajectory is generated by using an optimal control method. The optimal control problem is formulated and then solved by using the Matlab tool GPOPS-II. Trials are carried out on a test track, and the tested data are collected and processed, then the trajectory data in different corners are obtained. Different TLCs calculations are derived and applied to different track sections. After that, the human driver’s trajectories and the optimal line are compared to see the correlation using TLC methods. The results show that the optimal trajectory shows a similar trend with human’s trajectories to some extent when driving through a corner although it is not so perfectly aligned with the tested trajectories, which could conform with people’s driving intuition and improve the occupants’ comfort when driving in a corner. This could improve the acceptability of AVs in the automotive market in the future. The driver tends to move to the outside of the lane gradually after passing the apex when driving in corners on the road with hard-lines on both sides.

The Simulation Analysis of Semi-Active Suspension System in Vehicle Based on Sliding Mode Control with Varying Structure

2011 ◽  
Vol 216 ◽  
pp. 96-100
Author(s):  
Jing Jun Zhang ◽  
Wei Sha Han ◽  
Li Ya Cao ◽  
Rui Zhen Gao
Keyword(s):  
Control Method ◽  
Simulation Analysis ◽  
Reference Model ◽  
Sliding Mode ◽  
Tracking Error ◽  
Active Suspension ◽  
Suspension System ◽  
Sliding Mode Controller ◽  
Error Dynamics ◽  
Dynamic Quality

A sliding mode controller for semi-active suspension system of a quarter car is designed with sliding model varying structure control method. This controller chooses Skyhook as a reference model, and to force the tracking error dynamics between the reference model and the plant in an asymptotically stable sliding mode. An equal near rate is used to improve the dynamic quality of sliding mode motion. Simulation result shows that the stability of performance of the sliding-mode controller can effectively improve the driving smoothness and safety.

A Study of Control Strategy for Vehicle Semi-Active Suspension System

1991 ◽  
Author(s):  
Yiming Zhang ◽  
Ye Lin
Keyword(s):  
Optimal Control ◽  
Control Strategy ◽  
Active Suspension ◽  
Suspension System ◽  
Statistical Characteristics ◽  
Active System ◽  
Optimal Control Strategy ◽  
Performance Limit ◽  
Passive Suspension ◽  
Isolation Performance

Abstract This paper investigates a reference control strategy for Vehicle semi-active suspension. The control is conducted by following the idea optimal active controller. The passive actuator is set to optimal whenever the active and passive actuators have the same signs; and set to zero output whenever the two signs are opposite. The simulation results of a 2DoF vehicle show that the semi -active suspension system can follow the ideal active system very well, both are superior to conventional passive systems. In this paper, a 2DoF vehicle model was also used to study a statistical optimal control strategy of the semi-active suspension system. The statistical optimal concept is the result of the combination of the nonlinear programming and controllable damper. A way of estimating statistical characteristics of road irregularities was also proposed. Vehicle active, suspension, due to its perfect v i bra t i on isolation performance, gets moreand more attention. Active suspension can be generally divided into two categories, totally active suspension system and semi-active suspension system. From the published results it is known that active suspension can surpass the performance limit of conventional passive suspension and greatly improve the vehicle riding comfort and steering ability. But active suspension has a critical disadvantage of less applicability, due to its high cost and low reliability. Also it consumes large amount of energy as it works. The idea of semi-active suspension was put forward to overcome the shortcoming of active suspension. It is a compromise between active suspension and passive suspension. Semi-active suspension has approximately the same behavior as active suspension, and almost consumes no energy as it works. So semi-active suspension possesses a great potential in application. At. present, in the field of suspension research over the world, a great deal of attention is paied to semi-active suspension. At present, for the cotrol of semi-active suspension the widely studied strategy is “on off” control [1] [2], which is first put forward by Karnopp. “On-off” control can eliminate the phenomenon of vibration amplification for passive suspension, thus it can improve the suspension performance to certain extent. At present, no substantive result has been obtained yet in the field of optimal control of semi-active suspension. This paper will investigate a reference control strategy on the basis of linear optimal control. The control is conducted by following the optimal ctive controller. The referrence control result is optimal when the outputs of the active and semi-active force generators have the same signs.

scholarly journals Reconfiguring Smart Structures Using Approximate Heteroclinic Connections in a Spring-Mass Model

2015 ◽  
Author(s):  
Jiaying Zhang ◽  
Colin R. McInnes
Keyword(s):  
Optimal Control ◽  
Control Method ◽  
Smart Structures ◽  
Polynomial Method ◽  
Reference Trajectory ◽  
Sensors And Actuators ◽  
Embedded Computing ◽  
Equal Energy ◽  
Optimal Control Method ◽  
Heteroclinic Connection

Several new methods are proposed to reconfigure smart structures with embedded computing, sensors and actuators. These methods are based on heteroclinic connections between equal-energy unstable equilibria in an idealised spring-mass smart structure model. Transitions between equal-energy unstable (but actively controlled) equilibria are considered since in an ideal model zero net energy input is required, compared to transitions between stable equilibria across a potential barrier. Dynamical system theory is used firstly to identify sets of equal-energy unstable configurations in the model, and then to connect them through heteroclinic connection in the phase space numerically. However, it is difficult to obtain such heteroclinic connections numerically in complex dynamical systems, so an optimal control method is investigated to seek transitions between unstable equilibria, which approximate the ideal heteroclinic connection. The optimal control method is verified to be effective through comparison with the results of the exact heteroclinic connection. In addition, we explore the use of polynomials of varying order to approximate the heteroclinic connection, and then develop an inverse method to control the dynamics of the system to track the polynomial reference trajectory. It is found that high order polynomials can provide a good approximation to true heteroclinic connections and provide an efficient means of generating such trajectories. The polynomial method is envisaged as being computationally efficient to form the basis for real-time reconfiguration of real, complex smart structures with embedded computing, sensors and actuators.

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