Intelligent optimal control for the crawler vehicle with semi-active suspension using modified staged continuous tabu search algorithm

2017 ◽  
Vol 40 (13) ◽  
pp. 3617-3624
Author(s):  
Fengchen Wang ◽  
Decheng Wang ◽  
Jia Sun ◽  
Jianzhu Zhao

This paper proposes a novel intelligent optimal control strategy for crawler vehicles with semi-active suspension. The proposed control strategy aims at improving vehicle ride comfort by addressing contradictory suspension properties requirements of ride comfort and handling stability simultaneously. After establishing seven degrees of freedom dynamic model of the crawler vehicle, a comprehensive evaluation index is developed to trade off among various vehicle performances, which include ride comfort, damper thermal reliability, elastic element fatigue and handling stability. Then, using modified staged continuous tabu search (MSCTS) algorithm, the optimal control efforts of semi-active suspension, damping ratios, are determined by minimizing the cost function defined by the comprehensive evaluation index. Demonstrated by simulations with triangle convex block and random ground roughness excitations, MSCTS control strategy can successfully improve ride comfort performance and achieve the optimal comprehensive performance as well.

Author(s):  
Yiming Zhang ◽  
Ye Lin

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.


2012 ◽  
Vol 38 (6) ◽  
pp. 1017 ◽  
Author(s):  
Jia-Yan ZHANG ◽  
Zhong-Hai MA ◽  
Xiao-Bin QIAN ◽  
Shao-Ming LI ◽  
Jia-Hong LANG

2021 ◽  
Vol 145 ◽  
pp. 110789
Author(s):  
Parthasakha Das ◽  
Samhita Das ◽  
Pritha Das ◽  
Fathalla A. Rihan ◽  
Muhammet Uzuntarla ◽  
...  

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