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Fast predictive control of linear systems combining Nesterov's gradient method and the method of multipliers

机译:结合Nesterov梯度法和乘数法的线性系统快速预测控制

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The fast, tailored solution of linear, predictive control problems is important, yet challenging. We present an algorithm based on the fast gradient method and the method of multipliers for model predictive control of linear, discrete-time, time-invariant, systems with box constraints. The algorithm uses the augmented Lagrangian method to handle equality constraints, so it can takes advantage of the sparsity of the problem. We present different schemes to update the multipliers. An example illustrates the performance of the algorithm, which is competitive with other tailored solution methods.
机译:线性,预测性控制问题的快速,量身定制的解决方案很重要,但也充满挑战。我们提出了一种基于快速梯度法和乘数法的算法,用于具有箱约束的线性,离散时间,时不变系统的模型预测控制。该算法使用增强的拉格朗日方法来处理等式约束,因此可以利用问题的稀疏性。我们提出了不同的方案来更新乘数。一个示例说明了该算法的性能,与其他定制解决方案方法相比具有竞争力。

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