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Min-max control of constrained uncertain discrete-time linear systems

机译:约束不确定不确定离散线性系统的最小-最大控制

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For discrete-time uncertain linear systems with constraints on inputs and states, we develop an approach to determine state feedback controllers based on a min-max control formulation. Robustness is achieved against additive norm-bounded input disturbances and/or polyhedral parametric uncertainties in the state-space matrices. We show that the finite-horizon robust optimal control law is a continuous piecewise affine function of the state vector and can be calculated by solving a sequence of multiparametric linear programs. When the optimal control law is implemented in a receding horizon scheme, only a piecewise affine function needs to be evaluated on line at each time step. The technique computes the robust optimal feedback controller for a rather general class of systems with modest computational effort without needing to resort to gridding of the state-space.
机译:对于具有输入和状态约束的离散时间不确定线性系统,我们开发了一种基于最小-最大控制公式确定状态反馈控制器的方法。针对状态空间矩阵中加性范数有界的输入扰动和/或多面体参数不确定性,实现了鲁棒性。我们表明,有限水平鲁棒最优控制律是状态向量的连续分段仿射函数,可以通过求解一系列多参数线性程序来计算。当在后退的水平方案中实现最佳控制律时,在每个时间步仅需要在线评估分段仿射函数。该技术以适度的计算量为相当普通的一类系统计算了鲁棒的最优反馈控制器,而无需求助于状态空间的网格化。

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