Self-Tuning Optimal Control of an Active Suspension

1989 ◽  
Author(s):  
Hung-Hsu Fred Chen ◽  
Dennis A. Guenther
Keyword(s):  
Optimal Control ◽  
Active Suspension ◽  
Self Tuning

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 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.

Simultaneous dynamic system estimation and optimal control of vehicle active suspension

2018 ◽  
Vol 57 (10) ◽  
pp. 1467-1493 ◽  
Author(s):  
Tamer Attia ◽  
Kyriakos G. Vamvoudakis ◽  
Kevin Kochersberger ◽  
John Bird ◽  
Tomonari Furukawa
Keyword(s):  
Optimal Control ◽  
Dynamic System ◽  
Active Suspension

scholarly journals Applications of Approximate Optimal Control to Nonlinear Systems of Tracked Vehicle Suspensions

2021 ◽  
Vol 14 (1) ◽  
Author(s):  
Yan-Jun Liang ◽  
You-Jun Lu ◽  
De-Xin Gao ◽  
Zhong-Sheng Wang
Keyword(s):  
Optimal Control ◽  
Vibration Control ◽  
Ride Comfort ◽  
Nonlinear Dynamic System ◽  
Active Suspension ◽  
Nonlinear Damping ◽  
Tracked Vehicle ◽  
Control Approach ◽  
Vehicle Suspensions ◽  
Suspension Systems

AbstractTechnique of approximate optimal vibration control and simulation for vehicle active suspension systems are developed. Considered the nonlinear damping of springs, mechanical model and a nonlinear dynamic system for a class of tracked vehicle suspension vibration control are established and the corresponding system of state space form is described. To prolong the working life of suspension system and improve ride comfort, based on the active suspension vibration control devices and using optimal control approach, an approximate optimal vibration controller is designed, and an algorithm is presented for the vibration controller. Numerical simulation results illustrate the effectiveness of the proposed technique.

Sign in / Sign up

Export Citation Format

Share Document