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Robust control via concave minimization local and global algorithms

机译:通过凹面最小化局部和全局算法进行鲁棒控制

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This paper deals with the robust control problem of linear fractional representation uncertain systems depending on a time-varying parameter uncertainty. Our main result exploits a linear matrix inequality (LMI) characterization involving scalings and Lyapunov variables subject to an additional essentially non-convex algebraic constraint. The non-convexity enters the problem in the form of a rank deficiency condition or matrix inverse relation on the scalings only. It is shown that such problems and many others can be formulated as the concave minimization of a nonlinear functional subject to LMI constraints. The local Frank and Wolfe feasible direction algorithm is introduced. Several efficient global concave minimization programming methods are also introduced and combined with the local feasible direction method to secure and certify global optimality of the solutions. The implementation details of the algorithms are covered.
机译:本文研究了基于时变参数不确定性的线性分数表示不确定系统的鲁棒控制问题。我们的主要结果是利用线性矩阵不等式(LMI)表征,其中涉及缩放和Lyapunov变量,这些变量受其他基本非凸代数约束的约束。非凸性仅以等级不足条件或矩阵逆关系的形式出现在问题上。结果表明,此类问题和许多其他问题可以表述为受LMI约束的非线性泛函的凹面最小化。介绍了局部Frank和Wolfe可行方向算法。还介绍了几种有效的全局凹面最小化编程方法,并将其与局部可行方向方法相结合,以确保和证明解的全局最优性。涵盖了算法的实现细节。

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