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An effective projection-based nonlinear adaptive control strategy for heavy vehicle suspension with hysteretic leaf spring
Nonlinear Dynamics ( IF 5.2 ) Pub Date : 2020-02-24 , DOI: 10.1007/s11071-020-05527-4
Jie Zhang , Fei Ding , Bangji Zhang , Chao Jiang , Haiping Du , Boyuan Li

Abstract

A new nonlinear adaptive control strategy for electrohydraulic active suspensions with the hysteretic leaf spring is proposed to improve suspension performances of heavy vehicle. The nonlinear hysteresis property of leaf spring, described and experimentally validated with the Bouc–Wen model, is transformed into linear system by Takagi–Sugeno (T–S) fuzzy approach. Based on the derived T–S fuzzy model, a robust \({H}\infty \) dynamic feedback control with adaptive gain is employed to generate the desired target forces for hydraulic actuators. A new projection-based adaptive control (PAC) law is further proposed for actuators to track the target forces under parametric uncertainties. The PAC law is derived based on the global asymptotic stability conditions of Lyapunov function for the obtained T–S fuzzy model with parametric uncertainties under inputs from both outputs of robust \({H}\infty \) controller and errors of force tracking. The benefits of vehicle systems with PAC active suspension are compared to both sliding mode control (SMC) active suspension and passive suspension. The obtained results indicate that the PAC method can be able to cope with uncertainties and has better robustness than SMC method. Furthermore, the obtained results also indicate that the proposed nonlinear adaptive control strategy effectively improves the suspension performances of heavy vehicle with the hysteretic leaf spring.



中文翻译:

具有滞后板簧的基于有效投影的非线性车辆悬架非线性自适应控制策略

摘要

提出了一种具有滞后片簧的电液主动悬架非线性自适应控制策略,以提高重型车辆的悬架性能。用Bouc–Wen模型描述和实验验证的钢板弹簧的非线性磁滞特性通过Takagi–Sugeno(TS)模糊方法转化为线性系统。基于派生的TS模糊模型,稳健的\({H} \ infty \)具有自适应增益的动态反馈控制用于为液压执行器生成所需的目标力。进一步提出了一种新的基于投影的自适应控制(PAC)定律,用于执行器在参数不确定性下跟踪目标力。基于Lyapunov函数的全局渐近稳定性条件,针对鲁棒\({H} \ infty \)的两个输出,在参数不确定性下获得的含参数不确定性T–S模糊模型,得出PAC律控制器和力跟踪错误。带有PAC主动悬架的车辆系统的优势与滑模控制(SMC)主动悬架和被动悬架相比都有所提高。所得结果表明,PAC方法能够应对不确定性,并且比SMC方法具有更好的鲁棒性。此外,所得结果还表明,所提出的非线性自适应控制策略有效地改善了带有滞后片簧的重型车辆的悬架性能。

更新日期:2020-02-25
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