Modeling and Robust Adaptive Practical Predefined Time and Precision Tracking Control of Unmanned Fire Fighting Robot
Jiannan Chen, Xi Luo, Changchun Hua, Dianrui Mu, Fuchun Sun
Abstract
This article studies the modeling and tracking control problems for a class of towed unmanned fire fighting robots. Considering that no similar modeling results exist, we take the lead in building a novel system model that takes into consideration both system uncertainties and external disturbances, including unknown friction factors and drag force. Then, to compensate for the adverse effects of system uncertainties and external disturbances, a novel robust control algorithm is proposed, which utilizes adaptive control and scaling techniques. Moreover, innovative predefined performance functions are designed to ensure that tracking processes meet predefined transient and steady-state requirements. Unlike most of the existing works, our predefined time performance function has the advantage that the convergence time and convergence accuracy can be arbitrarily changed. In the end, a novel robust adaptive control scheme with predefined time and precision tracking is designed using the backstepping recursive method. Based on Lyapunov stability theory, it is demonstrated that all signals in the closed-loop system are ultimately bounded, and both predefined transient and steady-state processes are never violated. To validate the effectiveness of this proposed control scheme, numerical simulations and practical platform experiments have been conducted. To ensure repeatability, our codes are open sourced on Github: https://github.com/JiannanChen/Modeling-and-Robust-Control-UFFR.git.