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Neurodynamics-Based Robust Pole Assignment for High-Order Descriptor Systems

机译:基于神经动力学的高阶描述符系统的鲁棒极点分配

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In this paper, a neurodynamic optimization approach is proposed for synthesizing high-order descriptor linear systems with state feedback control via robust pole assignment. With a new robustness measure serving as the objective function, the robust eigenstructure assignment problem is formulated as a pseudoconvex optimization problem. A neurodynamic optimization approach is applied and shown to be capable of maximizing the robust stability margin for high-order singular systems with guaranteed optimality and exact pole assignment. Two numerical examples and vehicle vibration control application are discussed to substantiate the efficacy of the proposed approach.
机译:本文提出了一种神经动力学优化方法,用于通过鲁棒极点分配来合成具有状态反馈控制的高阶描述符线性系统。以新的鲁棒性度量作为目标函数,将鲁棒本征结构分配问题表述为伪凸优化问题。应用了神经动力学优化方法,并证明该方法能够最大程度地保证具有保证的最优性和精确的极点分配的高阶奇异系统的鲁棒稳定性裕度。讨论了两个数值示例和车辆振动控制应用,以证实所提出方法的有效性。

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