Observer-Based Predefined-Time Adaptive Fuzzy Prescribed Performance Tracking Control for a QUAV

Abstract

This article focuses on the problem of predefined-time adaptive output-feedback tracking control with prescribed performance for a quadrotor unmanned aerial vehicle (QUAV). Fuzzy logic systems (FLSs) are utilized to identify the unknown nonlinear dynamics of QUAV, and a fuzzy state observer is devised to estimate immeasurable states. By using the command filter, the problem of “explosion of complexity” is successfully averted, meanwhile the influence of filtered error is eliminated by way of the fractional power error compensation mechanism. The issue of singularity is effectively tackled by the hyperbolic tangent function's property and L'Hospital's rule. A predefined-time performance function is inserted into the control scheme to ensure that the tracking errors are restricted to the preassigned performance bounds. It is strictly proven that the closed-loop system is practically predefined-time stable, and the position and attitude tracking errors are driven into a small region around zero in a predefined time. Finally, a comparative simulation example is provided to show the validity and superiority of the proposed predefined-time adaptive control algorithm.