Fuzzy adaptive back stepping control of wheeled mobile robot

Abstract

Wheeled mobile robots (WMR) are unmanned vehicles and practical robots for industry and human life. The low-cost manufacturing, simple assembling, high-speed, lightweight design, and high observability and controllability of the WMRs have attracted the attention of engineering disciplines such as mechanical and electrical science. This paper focuses on the control of wheeled mobile robots through fuzzy adaptive back stepping (ABS). The mathematical model of WMR is divided into two types, including kinematic and dynamic analyses. Actually, this research analyzes the theoretical math model using hybrid methods such as fuzzy logic and adaptive back stepping (BS) to control WMR in both noisy and noiseless conditions along its path. On the other hand, this hybrid controller, because of its more robust performance, can track WMR on its targets. Because of this, WMR's ability to move around makes it choose fuzzy and adaptive back stepping (FABS) methods, which use model-based and time-dependent features, respectively. As a result, the signal inputs fuzzy membership functions, and then the fuzzy approach outputs a new signal that goes to the back-step adaptive controller to finalize the control effort to navigate WMR with the lowest error during its destinations.