Stabilization control of the differential mobile robot using Lyapunov function and extended kalman filter

Abstract

This paper presents the design of a novel control model to navigate the differential mobile robot  to  reach  the  desired  destination  from  an  arbitrary  initial  pose.  The  designed  model  is divided into two stages: the state estimation and the stabilization control. In the state estimation, an extended Kalman  filter  is employed  to optimally combine  the  information  from  the  system dynamics  and  measurements.  Two  Lyapunov  functions  are  constructed  that  allow  a  hybrid feedback control law to execute the robot movements. The asymptotical stability and robustness of  the closed  loop  system are assured. Simulations and experiments are carried out  to validate the effectiveness and applicability of the proposed approach.