结合灵敏度更新的NMPC的性能界限
Performance bounds for NMPC combined with Sensitivity Updates
摘要：
本文提出了一种无稳定化终端成本约束的模型预测控制的稳定性证明，该控制系统受到未知但可测的干扰。为此，放松的李雅普诺夫参数的名义系统和利普希茨条件的开环变化的最优值函数和阶段的成本。基于特殊情况下的灵敏度分析，我们证明了Lipschitz假设是满足的，如果灵敏度更新可以沿着闭环解决方案。为了说明我们的方法，我们提出了一个半车的例子，并显示更新后的解决方案的舒适性和处理性能的性能改进。
英文摘要：
In this paper we present a stability proof of model predictive control without stabilizing terminal constraints of cost which are subject to unknown but measurable disturbances. To this end, a relaxed Lyapunov argument on the nominal system and Lipschitz conditions on the open loop change of the optimal value function and the stage costs are employed. Based on the special case of sensitivity analysis, we show that Lipschitz assumptions are satisfied if a sensitivity update can be performed along the closed loop solution. To illustrate our approach we present a halfcar example and show performance improvement of the updated solution with respect to comfort and handling properties.
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