首页|Findings from Yanshan University in Robotics Reported (Modeling and Robust Adaptive Practical Predefined Time and Precision Tracking Control of Unmanned Fire Fighting Robot)
Findings from Yanshan University in Robotics Reported (Modeling and Robust Adaptive Practical Predefined Time and Precision Tracking Control of Unmanned Fire Fighting Robot)
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By a News Reporter-Staff News Editor at Robotics & Machine Learning DailyNews Daily News - Investigators discuss new findings in Robotics. According to news reporting fromQinhuangdao, People’s Republic of Chi na, by NewsRx journalists, research stated, “This article studiesthe modeling a nd tracking control problems for a class of towed unmanned fire fighting robots. Consideringthat no similar modeling results exist, we take the lead in buildin g a novel system model that takes intoconsideration both system uncertainties a nd external disturbances, including unknown friction factors anddrag force.”Financial support for this research came from National Natural Science Foundatio n of China (NSFC).The news correspondents obtained a quote from the research from Yanshan Universi ty, “Then, tocompensate for the adverse effects of system uncertainties and ext ernal disturbances, a novel robustcontrol algorithm is proposed, which utilizes adaptive control and scaling techniques. Moreover, innovativepredefined perfor mance functions are designed to ensure that tracking processes meet predefined t ransientand steady-state requirements. Unlike most of the existing works, our p redefined time performance functionhas the advantage that the convergence time and convergence accuracy can be arbitrarily changed. In theend, a novel robust adaptive control scheme with predefined time and precision tracking is designed usingthe backstepping recursive method. Based on Lyapunov stability theory, it is demonstrated that all signalsin the closed-loop system are ultimately bounde d, and both predefined transient and steady-state processes are never violated. To validate the effectiveness of this proposed control scheme, numerical simulat ionsand practical platform experiments have been conducted.”
QinhuangdaoPeople’s Republic of ChinaAsiaEmerging TechnologiesMachine LearningRobotRoboticsYanshan University
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