Robust Constrained Stabilization Control Using Control Lyapunov and Control Barrier Function in the Presence of Measurement Noises

Abstract

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.