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A segment based sequential least squares algorithm with optimum energy control for tracking the dynamic shapes of smart structures

机译:具有最佳能量控制的基于分段的顺序最小二乘算法,用于跟踪智能结构的动态形状

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This paper presents a segment based sequential least squares algorithm with optimum energy control for tracking the dynamic shapes of piezoelectric smart structures. In this algorithm, integration of the square difference between the desired and achieved dynamic shapes over a time period is employed as an error function. The total electrical energy consumption of all actuators is used as the other control target. Two control schemes are studied: (a) minimization of the square error over a time period with energy constraint and (b) minimization of control energy with specified square error constraint. The Lagrange multiplier technique is used to consider the constraint, in which the properties of the characteristic matrix and polynomials of the Lagrange multiplier are analysed. Based on the present analysis, a simple and efficient algorithm is proposed; the relationship between permissible energy constraint and achievable minimum square error is investigated. Numerical results are presented for tracking twisting shape variations of a smart plate. Optimum energy control for reducing conflicting effects of the applied actuation voltages is also discussed.
机译:本文提出了一种基于分段的顺序最小二乘算法,该算法具有最佳能量控制,可用于跟踪压电智能结构的动态形状。在该算法中,将期望的和获得的动态形状之间的平方差在某个时间段内的积分用作误差函数。所有执行器的总电能消耗用作另一个控制目标。研究了两种控制方案:(a)在具有能量约束的时间段内最小化平方误差,以及(b)在具有指定平方误差约束的情况下最小化控制能量。拉格朗日乘数技术用于考虑约束条件,其中分析了拉格朗日乘数的特征矩阵和多项式的性质。在此基础上,提出了一种简单有效的算法。研究了允许的能量约束与可达到的最小平方误差之间的关系。给出了用于跟踪智能板扭曲形状变化的数值结果。还讨论了用于减少施加的激励电压的冲突影响的最佳能量控制。

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