Adaptive Sliding Mode Trajectory Tracking Control for WMR Considering Skidding and Slipping via Extended State Observer

Gang Wang,Xiaoping Liu,Chenghui Zhou,Yu Yu

doi:10.3390/en12173305

Abstract

When the wheeled mobile robot (WMR) is required to perform specific tasks in complex environment, i.e., on the forestry, wet, icy ground or on the sharp corner, wheel skidding and slipping inevitably occur during trajectory tracking. To improve the trajectory tracking performance of WMR under unknown skidding and slipping condition, an adaptive sliding mode controller (ASMC) design approach based on the extended state observer (ESO) is presented. The skidding and slipping is regarded as external disturbance. In this paper, the ESO is introduced to estimate the lumped disturbance containing the unknown skidding and slipping, parameter variation, parameter uncertainties, etc. By designing a sliding surface based on the disturbance estimation, an adaptive sliding mode tracking control strategy is developed to attenuate the lumped disturbance. Simulation results show that higher precision tracking and better disturbance rejection of ESO-ASMC is realized for linear and circular trajectory than the ASMC scheme. Besides, experimental results indicate the ESO-ASMC scheme is feasible and effective. Therefore, ESO-ASMC scheme can enhance the energy efficiency for the differentially driven WMR under unknown skidding and slipping condition.

Highlights

With the increasingly widespread application of robotics, wheeled mobile robot (WMR) is required to perform many tasks, i.e., rescue operation [1], transportation products [2], social interaction [3], planetary exploration [4] and so on
A combined kinematic/torque controller was presented with the adaptive backstepping in [5], a finite-time tracking controller with output feedback was developed in [6], a data-based path tracking control algorithm was realized in [7,8], sliding-mode based algorithms [9,10,11] were presented to allow two different types of WMRs to track the reference path. [12,13,14,15] presented several other effective algorithms, such as the neural networks method [12], robust control scheme [13,14], and backstepping approach for path tracking control in [15]
The experimental results present a similar tendency for the Group A, B, and C, the position tracking precision of the extended state observer (ESO)-adaptive sliding mode controller (ASMC) scheme is all superior to the ASMC scheme in Figure 7 and

Summary

Introduction

With the increasingly widespread application of robotics, wheeled mobile robot (WMR) is required to perform many tasks, i.e., rescue operation [1], transportation products [2], social interaction [3], planetary exploration [4] and so on. High-performance control strategy is the prerequisites to implement the different practical tasks efficiently. Due to the WMR is a typical nonholonomic system, most present researches on the tracking control schemes were base on assuming that the wheel rolling without considering slipping and skidding. [12,13,14,15] presented several other effective algorithms, such as the neural networks method [12], robust control scheme [13,14], and backstepping approach for path tracking control in [15]. The controller in [5,6,7,8,9,10,11,12,13,14,15] had achieved certain performance on trajectory tracking based on nonslipping and nonskidding assumptions

Methods

Results

Conclusion