Abstract
In order to synthesize controllers for wheeled mobile robots (WMRs), some design techniques are usually based on the assumption that the center of mass is at the center of the robot itself. Nevertheless, the exact position of the center of mass is not easy to measure, thus WMRs is a typical uncertain nonlinear system with unknown control direction. Based on the fast terminal sliding mode control, an adaptive fuzzy path tracking control scheme is proposed for mobile robots with unknown control direction. In this scheme, the fuzzy system is used to approximate unknown functions, and a robust controller is constructed to compensate for the approximation error. The Nussbaum-type functions are integrated into the robust controller to estimate the unknown control direction. It is proved that all the signals in the closed-loop system are bounded, and the tracking error converges to a small neighborhood of the origin in a limited time. The effectiveness of the proposed scheme is illustrated by a simulation example.
Highlights
Design of Tracking ControllerIn order to realize the tracking error convergence in a finite time, the sliding mode surface is designed as s z_ + α · z + β · z(q/p) 0,
According to whether the tracking trajectory is a function of time, tracking control is divided into trajectory tracking and path tracking
For the path tracking, when the center of mass of the robot is exactly at the geometric center of the wheel axis, the path tracking problem was studied in [5], while the center of mass of the robot is located on the central axis of the two driving wheels, the path tracking problem was developed in [6]. e assumption in [5, 6] that the center of mass is located on the geometric center of the wheel axis or the central axis of the two driving wheels is a good idea for an actual operating robot system; the exact position of the center of mass is not easy to measure when it is running; the mobile robot system is a typical uncertain nonlinear system
Summary
In order to realize the tracking error convergence in a finite time, the sliding mode surface is designed as s z_ + α · z + β · z(q/p) 0,. ΜFli so (xi)), the control law (10) may have singularity problems, the fuzzy system (11) g(x|θ) θTψ(x) is adopted to approximate the unknown function g(x), and the equivalent control law is designed as follows:. To compensate the approximation error of the fuzzy system, the control law is designed as follows:. Substituting (12) into (6), we obtain z_ − αz − βzc − g(x|θ)ueq + g(x)ueq + g(x)ur (14). Nussbaum-type function technique is a feasible method to solve such unknown problems; Nussbaumtype function N(ζ) exp(ζ2)cos((π/2)ζ) is introduced into the design of a robust controller ur. E robust controller ur is designed as follows: ur. Rameter adaptive law is designed as θ_ ηψ(x)ueqz, δ_ g μueq‖ z, e following pa(17) (18). E adaptive fuzzy controller (13) and the adaptive law of unknown parameters (17)–(19) are adopted to the robot system (7); ,. + (g(τ)N(ζ) + 1)ζ_dτ ≤ V(0) + (g(τ)N(ζ) + 1)ζ_dτ
Sign-in/Register to view highlights & summary Sign-in/Register to access full text options 
Free) 
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a call
