Optimal Control of Vehicle Active Suspension Systems with Actuator Delay

Author(s):  
Bao-Lin Zhang ◽  
Ming-Qu Fan ◽  
Fu-Sheng Miao
Author(s):  
Rooholah Abdollahpour ◽  
Reza Sharifi Sedeh ◽  
Mohamad Taghi Ahmadian ◽  
Nasser Sadati

Advent of passenger cars has caused people to use them for more efficiency in their performance and wasting less time. Problems, however, still exist in them. For instance, since people travel with cars, their human bodies undergo in fatigue, restlessness, and sometimes health problems. Human body reaction under external vibration depends on the amplitude, frequency, and acceleration of the applied external excitation. These limitations which are usually announced by the bureau of standards imply the necessity of control of amplitude, vibration, frequency, and acceleration received by human body due to cars passing humps and bumps. In this paper, a quarter car model with active suspension system is considered and three control approaches namely optimal control, fuzzy control, and adaptive fuzzy optimal control (AFOC) are applied. Moreover, the performance of different controllers is compared. Application of three different methods indicate that adaptive fuzzy optimal control results in a higher performance in time, acceleration, amplitude, and consequently lower hazards to human body.


1992 ◽  
Vol 114 (4) ◽  
pp. 592-598 ◽  
Author(s):  
L. R. Ray

The stability robustness of linear-optimal control laws for quarter-car active suspension systems is evaluated using stochastic robustness analysis. Simultaneous parameters variations and neglected actuator and sensor dynamics are considered for LQ active suspension systems and for a single-measurement LQG system to determine the effects of uncertainty on system stability. The results indicate that neglected actuator and sensor dynamics have a small effect on stability robustness, while parameter uncertainty, particularly that of the “sprung mass” is of great concern. The effectiveness of Loop Transfer Recovery on active suspension systems with both parameter uncertainty and higher-order uncertainty is discerned. The analysis shows that when Loop Transfer Recovery is applied arbitrarily to uncertain systems, both estimator performance and system robustness can decrease. Nevertheless, it is concluded that the impact of the robustness recovery method is determined by stochastic stability robustness analysis, and the recovery design parameter that provides sufficient robustness with minimal performance degradation is readily identified. The effect of LQ design parameters on robustness also is considered. The paper presents robustness analysis and synthesis methods for a quarter-car model that can be applied to higher-order active suspension systems.


2013 ◽  
Vol 340 ◽  
pp. 631-635
Author(s):  
Yong Fa Qin ◽  
Jie Hua ◽  
Long Wei Geng

Vehicles with active suspension systems become more ride comfort and maneuverable stability, many types of active suspensions have been applied to passenger vehicles, but one of the shortcomings of an active susupension system is that the additional control power consumption is needed. The core issues of designing an active suspension system are to minimiaze vibration magnitute and control energy comsuption of the active suspension system. A new mathematic model for an active suspension system is established based on vehicle dynamics and modern control theory. An optimal control law is constructed through solving the Riccati equation, and then the transfer function is deduced to describe the relationship between the vetical velosity of the road roughness and the output of suspension system. Three typical parameters of vehicle ride comfort are researched, such as vertical acceleration of vehicle body, dynamic deflection of suspension system and dynamic deformation of tires. A case of a quarter vehicle model is studied by simulation to show that the proposed method of modeling and designing optimal controller are suitable to develop active suspension systems.


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