论文标题
通过平行蒙特卡洛模拟对非线性模型预测控制器的性能量化闭环系统
Performance Quantification of a Nonlinear Model Predictive Controller by Parallel Monte Carlo Simulations of a Closed-loop System
论文作者
论文摘要
本文为闭环中的非线性模型预测控制（NMPC）提供了基于平行的蒙特卡洛模拟量化方法。该方法为随机系统中的控制器性能提供了分布，从而实现了性能量化。我们在C启用的C中执行了高性能的Monte Carlo模拟，该元素由新的线程安全NMPC实现与现有的高性能Monte Carlo Simulation Toolbox结合使用。我们将NMPC调节器作为最佳控制问题（OCP），我们将其与新的线程Safe-Safe-Safe-Safe-Safe-Safe-Safen-Safen-Safen-Secient-Safen-Sequential-Sequential-Sequential-Sequential-quadratic quadratic quadratic quadratic Sonvationming Nlpseming Nlpsqp。我们的结果表明，在32核CPU上，NMPC闭环几乎是线性缩放。特别是，我们在32个内核上加速了大约27倍。我们在简单的连续搅拌坦克反应器（CSTR）上演示了性能定量方法，在该反应器（CSTR）中，我们使用NMPC和参考比例积分（PI）控制器进行了30,000个闭环模拟。随机闭环系统的性能量化表明，NMPC在平均值和方差上都优于PI控制器。
This paper presents a parallel Monte Carlo simulation based performance quantification method for nonlinear model predictive control (NMPC) in closed-loop. The method provides distributions for the controller performance in stochastic systems enabling performance quantification. We perform high-performance Monte Carlo simulations in C enabled by a new thread-safe NMPC implementation in combination with an existing high-performance Monte Carlo simulation toolbox in C. We express the NMPC regulator as an optimal control problem (OCP), which we solve with the new thread-safe sequential quadratic programming software NLPSQP. Our results show almost linear scale-up for the NMPC closed-loop on a 32 core CPU. In particular, we get approximately 27 times speed-up on 32 cores. We demonstrate the performance quantification method on a simple continuous stirred tank reactor (CSTR), where we perform 30,000 closed-loop simulations with both an NMPC and a reference proportional-integral (PI) controller. Performance quantification of the stochastic closed-loop system shows that the NMPC outperforms the PI controller in both mean and variance.
