论文标题
模型预测控制中的时间适应性
Time adaptivity in model predictive control
论文作者
论文摘要
在算法的每个步骤中，模型预测控制（MPC）方法的核心在于在MPC算法的预测范围内求解时间依赖性优化问题，然后在应用范围上应用一部分对应用程序范围的最佳控制以获得新状态。为了有效地解决此问题，我们提出了基于此最佳控制问题的最佳系统的时间自适应残差A-posteriori错误控制概念。这种方法不仅提供了预测范围的量身定制时间离散化，而且还建议针对当前MPC步骤定制的应用范围。我们将此概念应用于由线性抛物线PDE管辖的系统，并提供了几个数值示例，这些示例证明了我们自适应MPC控制概念的性能和鲁棒性。
The core of the Model Predictive Control (MPC) method in every step of the algorithm consists in solving a time-dependent optimization problem on the prediction horizon of the MPC algorithm, and then to apply a portion of the optimal control over the application horizon to obtain the new state. To solve this problem efficiently, we propose a time-adaptive residual a-posteriori error control concept based on the optimality system of this optimal control problem. This approach not only delivers a tailored time discretization of the the prediction horizon, but also suggests a tailored length of the application horizon for the current MPC step. We apply this concept for systems governed by linear parabolic PDEs and present several numerical examples which demonstrate the performance and the robustness of our adaptive MPC control concept.
