Robust Constrained Stabilization Control Using Control Lyapunov and Control Barrier Function in the Presence of Measurement Noises
Robust Constrained Stabilization Control Using Control Lyapunov and Control Barrier Function in the Presence of Measurement Noises
复制标题
存在测量噪声时使用控制李雅普诺夫和控制势垒函数的鲁棒约束稳定控制
DOI：
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发表时间：
2018
期刊：
影响因子：
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通讯作者：
M. Yamakita
中科院分区：
文献类型：
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作者：
Rin Takano;M. Yamakita
为了控制实际系统，必须考虑多种约束条件。特别是，状态约束与系统的安全性和稳定性密切相关。因此，许多研究人员提出了在不违反给定状态约束的情况下获得良好控制性能的控制器。最近，人们提出了一种新的方法来解决这类约束控制问题，即基于控制Lyapunov函数和控制Barrier函数的二次规划（CLF-CBF-QP）。该方法通过求解输出归零控制和满足给定约束的两种约束条件下的二次问题来计算最优控制输入。它在标称情况下可以获得良好的控制性能，但在存在干扰的情况下不可能获得良好的控制效果。本文提出了一种鲁棒的无气味卡尔曼滤波CLF-CBF -QP控制器，该控制器具有衰减状态干扰和测量噪声的能力。
A lot of kinds of constraints must be considered to control real systems. In particular, state constraints are closely related to safety and stability of systems. Therefore, many researchers have proposed 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 Control Lyapunov Function and Control Barrier Function based Quadratic Programs (CLF-CBF-QP). This method calculates an optimal control input by solving a quadratic problem under two kinds of constraints for output zeroing control and satisfying given constraints. 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 CLF-CBF -QP controller with Unscented Kalman Filter (UKF) which has an ability to attenuate effects of state disturbances and measurement noises.