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Robust maximum principle for multi-model LQ-problem

机译:多模型LQ问题的鲁棒最大原理

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This paper presents the version of the robust maximum principle in the context of multi-model control formulated as the minimax Bolza problem. The cost function contains a terminal term as well as an integral one. A fixed horizon and terminal set are considered. The necessary conditions of the optimality are derived for the class of uncertain systems given by an ordinary differential equation with parameters from a given finite set. This problem consists in the control design providing a good behaviour for a given class of multi-model system. It is shown that the design of the minimax optimal controller is reduced to a finite-dimensional optimization problem given at the corresponding simplex set containing the weight parameters to be found. The robust optimal control may be interpreted as a mixture (with the optimal weights) of the controls which are optimal for each fixed parameter value. The proof is based on the recent results obtained for minimax Mayer problem (Boltyanski and Poznyak 1999a). The minimax linear quadratic control problem is considered in detail and the illustrative examples dealing with finite as well as infinite horizons conclude this paper. [References: 20]
机译:本文介绍了在拟定为minimax Bolza问题的多模型控制的情况下鲁棒极大原理的版本。成本函数包含一个终项以及一个整数。考虑固定水平仪和终端机。对于由具有给定有限集合的参数的常微分方程给出的一类不确定系统,得出了最优性的必要条件。这个问题在于控制设计为给定类别的多模型系统提供了良好的行为。结果表明,最小极大最优控制器的设计被简化为一个有限维的优化问题,该问题是在对应的单纯形集合中给出的,该单纯形集合包含要找到的权重参数。鲁棒的最优控制可以解释为对于每个固定参数值而言最优的控制的混合(具有最优权重)。该证明是基于最近对极小极大迈耶问题获得的结果(Boltyanski和Poznyak 1999a)。本文详细讨论了极大极小线性二次控制问题,并给出了关于有限和无限地平线的说明性示例。 [参考:20]

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