基于灵敏度的NMPC更新在汽车应用中的性能
Performance of Sensitivity based NMPC Updates in Automotive Applications
摘要：
在这项工作中，我们考虑了半车模型，这是未知的，但可测量的干扰。为了控制这个系统，我们施加模型预测控制的组合，而不稳定终端约束或成本，以产生一个标称的解决方案和灵敏度更新，以处理干扰。对于这种方法，所得到的闭环的稳定性可以保证使用放松的李雅普诺夫参数的标称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。对于所考虑的例子中，所提出的方法是实时适用的，相应的结果表明，更新后的解决方案的舒适性和处理性能显着的性能改善。
英文摘要：
In this work we consider a half car model which is subject to unknown but measurable disturbances. To control this system, we impose a combination of model predictive control without stabilizing terminal constraints or cost to generate a nominal solution and sensitivity updates to handle the disturbances. For this approach, stability of the resulting closed loop can be guaranteed using 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. For the considered example, the proposed approach is realtime applicable and corresponding results show significant performance improvements of the updated solution with respect to comfort and handling properties.
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