A design method of model error compensator for systems with polytopic-type uncertainty and disturbances

Ryuichiro Yoshida, Yuki Tanigawa, Hiroshi Okajima, N. Matsunaga
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引用次数: 5

Abstract

Control systems achieve the desired performance with the model-based controller if the dynamical model of the actual plant is given with sufficient accuracy. However, if there exists a difference between the actual plant and its model dynamics, the model-based controller does not work well and does not achieve the intended desired performance. A model error compensator (MEC) is proposed for overcoming the model error in our previous study. Attaching the compensator for the model error to the actual plant, the output trajectory of the actual plant is made close to that of its model. Then, from the controller, the apparent difference in the dynamics can be smaller, and performance degradation is drastically reduced. MEC is useful for various control systems such as non-linear systems and the control systems with delay, and so on. In this paper, we propose an original design method of the filter parameters in MEC for systems with polytopic-type uncertainty and disturbances. First, we show an analysis method about the robust performance of MEC for the system with the polytopic type uncertainty based on an linear matrix inequality problem. The gain parameters in MEC is designed using particle swarm optimization and the presented analysis method. The effectiveness of the design method for the system with polytopic-type uncertainty and disturbance is evaluated using numerical examples.
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具有多向不确定性和扰动的系统模型误差补偿器的设计方法
如果给定了具有足够精度的实际对象的动态模型,那么基于模型的控制器控制系统就能达到预期的性能。但是,如果实际对象与其模型动力学之间存在差异,则基于模型的控制器不能很好地工作并且不能达到预期的性能。在之前的研究中,我们提出了一种模型误差补偿器(MEC)来克服模型误差。将模型误差补偿器附加到实际对象上,使实际对象的输出轨迹接近其模型的输出轨迹。然后,从控制器来看,动力学上的明显差异可以更小,并且性能下降大大减少。MEC可用于各种控制系统,如非线性系统和具有延迟的控制系统等。本文提出了一种具有多向不确定性和干扰的MEC系统滤波器参数的设计方法。首先,提出了一种基于线性矩阵不等式问题的多面体不确定性系统的MEC鲁棒性分析方法。采用粒子群算法设计了MEC的增益参数,并给出了分析方法。通过数值算例,评价了该设计方法对具有多向不确定性和扰动的系统的有效性。
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