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Vibration suppression in multi-body systems by means of disturbance filter design methods

机译:通过干扰过滤器设计方法振动抑制多体系

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This paper addresses the problem of interaction in mechanical multi-body systems and shows that subsystem interaction can be considerably minimized while increasing performance if an efficient disturbance model is used. In order to illustrate the advantage of the proposed intelligent disturbance filter, two linear model based techniques are considered: IMC and the model based predictive (MPC) approach. As an illustrative example, multivariable mass-spring-damper and quarter car systems are presented. An adaptation mechanism is introduced to account for linear parameter varying LPV conditions. In this paper we show that, even if the IMC control strategy was not designed for MIMO systems, if a proper filter is used, IMC can successfully deal with disturbance rejection in a multivariable system, and the results obtained are comparable with those obtained by a MIMO predictive control approach. The results suggest that both methods perform equally well, with similar numerical complexity and implementation effort.
机译:本文解决了机械多体系中的交互问题,并且表明如果使用有效的干扰模型,则可以显着最小化子系统交互,同时增加性能。为了说明所提出的智能扰动滤波器的优点,考虑了两个基于线性模型的技术:IMC和基于模型的预测(MPC)方法。作为说明性示例,提出了多变量质量弹簧阻尼器和四分之一的汽车系统。引入适应机制以解释线性参数变化的LPV条件。在本文中,我们表明,即使没有为MIMO系统设计IMC控制策略,如果使用了适当的过滤器,IMC可以成功地处理多变量系统中的干扰抑制,并且获得的结果与A由A获得的结果相当。 MIMO预测控制方法。结果表明,两种方法同样好,具有相似的数值复杂性和实施努力。

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