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ON THE TURNPIKE PROPERTY AND THE RECEDING-HORIZON METHOD FOR LINEAR-QUADRATIC OPTIMAL CONTROL PROBLEMS

机译:关于线性二次最优控制问题的速度特性与后退地平衡方法

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Optimal control problems with a very large time horizon can be tackled with the receding-horizon control (RHC) method, which consists in solving a sequence of optimal control problems with small prediction horizon. The main result of this article is the proof of the exponential convergence (with respect to the prediction horizon) of the control generated by the RHC method toward the exact solution of the problem. The result is established for a class of infinite-dimensional linear-quadratic optimal control problems with time-independent dynamics and integral cost. Such problems satisfy the turnpike property: the optimal trajectory remains most of the time very close to the solution to the associated static optimization problem. Specific terminal cost functions, derived from the Lagrange multiplier associated with the static optimization problem, are employed in the implementation of the RHC method.
机译:可以用倒退的地平控制(RHC)方法来解决具有非常大的时间范围的最佳控制问题,该方法包括求解小预测地平线的一系列最佳控制问题。 本文的主要结果是通过RHC方法对问题的精确解决方案产生的控制的指数收敛(关于预测地平线)的证明。 结果是为一类无限维线性 - 二次最佳控制问题与时间无关的动态和整数成本。 此类问题满足了速度特性:最佳轨迹仍然仍然非常接近对相关静态优化问题的解决方案。 从与静态优化问题相关联的拉格朗日乘数导出的特定终端成本函数在RHC方法的实现中使用。

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