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Application of Robust Control Barrier Function with Stochastic Disturbance Model for Discrete Time Systems

机译：鲁棒控制屏障功能在离散时间系统中随机扰动模型的应用

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For engine control systems, there are several constraints to prevent damages of engines due to bad phenomena, eg. knocking. When the dynamics of the systems are modeled as state space representations, the constraints can be represented as state constraints. Therefore, many researchers have studied controllers to achieve good control performances without violating given state constraints. Recently, a new method to solve such constraint control problems has been proposed, which is called CLF-CBF-QP. The control method was proposed first for continuous time systems and was extended to discrete time systems. It can achieve good control performances in the nominal case, however it is impossible to achieve good results in the presence of disturbances. This paper proposes a robust constrained stabilization control using control barrier function and Gaussian process regression for discrete time systems affected by stochastic disturbances, and show an application to the engine control systems.
机译：对于发动机控制系统，由于不良现象，有几个限制以防止引擎的损坏，例如。敲门。当系统的动态被建模为状态空间表示时，约束可以表示为状态约束。因此，许多研究人员已经研究了控制器，以实现良好的控制性能而不违反给定的状态约束。最近，已经提出了一种解决这些约束控制问题的新方法，称为CLF-CBF-QP。首先提出控制方法，用于连续时间系统，并扩展到离散时间系统。它可以在标称案件中实现良好的控制性能，但是在存在干扰的情况下无法达到良好的结果。本文提出了一种利用随机扰动影响的离散时间系统的控制屏障功能和高斯过程回归的稳健限制稳定控制，并显示了发动机控制系统的应用。

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