Stabilization Control of the Differential Mobile Robot Using Lyapunov Function and Extended Kalman Filter

TL;DR

This paper introduces a control system for differential mobile robots that combines an extended Kalman filter for state estimation with Lyapunov-based stabilization to ensure accurate navigation and robustness.

Contribution

It proposes a novel hybrid control approach integrating Lyapunov functions and an extended Kalman filter for stable robot navigation from arbitrary initial poses.

Findings

The control system achieves asymptotic stability.

Simulations and experiments validate effectiveness.

Robustness of the approach is demonstrated.

Abstract

This paper presents the design of a 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.