摘要
研究了车辆主动悬架这个多变量不确定系统的自适应控制问题。提出了一种新型的单神经元多变量控制器。给出一种综合误差的概念,将综合误差与传统的单神经元控制器相结合,得到一种基于综合误差理论的单神经元控制器,它可以同时直接调控被控对象的多输出变量。将该控制方法应用于1/4主动悬架系统,采用二次型性能指标对控制器参数进行了优化设计。研究了在不同的悬架参数及随机路面输入情况下控制器的自适应性能,并与被动悬架及传统神经元控制的主动悬架进行了性能对比。仿真结果表明,所提出的控制器可使车辆获得更为优良的综合减振性能,可显著改善平顺性,是一种简单有效且鲁棒性较好的自适应控制器。该控制方法为主动悬架及类似的多变量不确定系统的控制提供了一种可能的简捷有效的新途径。
This paper investigated the adaptive control of vehicle active suspension, in which multivariable and uncertainty problems were involved. A novel multivariable neuron controller was proposed. An integrated error concept was firstly given, then a new neuron controller combining integrated error with traditional neuron controller was formed. It can directly control the multi--output variables of controlled plant simultaneously. The control scheme was applied for controlling a quarter --car active suspension, and the optimum parameters of the corresponding controller were obtained by means of minimization of the quadratic performance index. The self--adaptability of the controller was investigated in various vehicle parameters and random road conditions. Extension comparisons with an equivalent passive suspension and an active suspension using traditional neuron control were also performed. Simulation results demonstrate the proposed controller is a simple, effective and robust adaptive controller which can achieve better vehicle overall performance, especially in ride comfort. In addition, the newly--proposed neuron scheme provides a concise yet efficient new possibility to the control of a class of uncertain multivariable systems similar to vehicle active suspension.
出处
《中国机械工程》
EI
CAS
CSCD
北大核心
2007年第21期2641-2645,共5页
China Mechanical Engineering
关键词
主动悬架
自适应控制
神经元
综合误差
多变量
active suspension
adaptive control
neuron
integrated error
multivariable
