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Online Optimizing Positioning Control With Model Error Compensator for LEGRV System

机译:在线优化LEGRV系统模型误差补偿器定位控制

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摘要

In this article, a precision positioning control approach of a linear exhaust gas recirculation valve (LEGRV) system using online optimization technique is proposed. As both dynamics and nonlinear factors, including hysteretic features, are inherent in LEGRV systems, the modeling of system is not an easy process. In order to avoid the complex obstacle of modeling, in this method, a simplified model, for e.g., linear or linearized dynamic model, is developed to approximate the essential motion feature of pintle position of the linear valve. For compensating the effect of model uncertainty caused by unmodeled nonlinear and dynamic factors, a model error compensator (MEC) is introduced. Then, an online optimizing positioning control (OPC) scheme is applied to the control of pintle position of valve. In this control scheme, the estimated gradient of MEC with respect to control variable is also included in the control strategy to suppress the influence of model uncertainty. Considering the effect of nonsmoothness of hysteresis inherent in the system, a nonsmooth optimization-search method based on the technique of generalized gradient is proposed. Afterward, the stability analysis of the OPC+MEC system is presented. Finally, the experimental results to evaluate the performance of proposed control method are presented.
机译:在本文中,提出了使用在线优化技术的线性废气再循环阀(LEGRV)系统的精确定位控制方法。作为动态和非线性因素,包括滞后特征,是leglv系统中固有的,系统的建模不是一个简单的过程。为了避免建模的复杂障碍,在该方法中,为例如线性或线性化动态模型的简化模型是开发的,以近似线性阀的针线位置的基本运动特征。为了补偿由未拼接的非线性和动态因素引起的模型不确定性的影响,介绍了模型误差补偿器(MEC)。然后,将在线优化定位控制(OPC)方案应用于阀的叉子位置的控制。在该控制方案中,MEC关于控制变量的估计梯度也包括在控制策略中,以抑制模型不确定性的影响。考虑到系统中固有的滞像的影响,提出了一种基于广义梯度技术的非光学优化搜索方法。之后,提出了OPC + MEC系统的稳定性分析。最后,提出了评价所提出的控制方法性能的实验结果。

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