Data-Driven Active Disturbance Rejection Control of Plant-Protection Unmanned Ground Vehicle Prototype: A Fuzzy Indirect Iterative Learning Approach  

作　　者：Tao Chen Ruiyuan Zhao Jian Chen Zichao Zhang 

机构地区：[1]College of Engineering,China Agricultural University,Beijing 100083,China [2]Key Laboratory of Smart Agricultural Technology in Tropical South China,Ministry of Agriculture and Rural Affairs,Guangzhou 510642,China

出　　处：《IEEE/CAA Journal of Automatica Sinica》2024年第8期1892-1894,共3页自动化学报（英文版）

基　　金：supported by the National Key R&D Program of China(2022YFD2001405);the National Natural Science Foundation of China(51979275);the Open Project Program of Key Laboratory of Smart Agricultural Technology in Tropical South China,Ministry of Agriculture and Rural Affairs,China(HNZHNY-KFKT-202202);the 2115 Talent Development Program of China Agricultural University.

摘　　要：Dear Editor,This letter proposes a fuzzy indirect iterative learning(FIIL)active disturbance rejection control(ADRC)scheme to address the impact of uncertain factors of plant-protection unmanned ground vehicle(UGV),in which ADRC is a data-driven model-free control algorithm that only relies on the input and output data of the system.Based on the established nonlinear time-varying dynamic model including dynamic load(medicine box),the FIIL technology is adopted to turn the bandwidth and control channel gain online,in which the fuzzy logic system is used to update the gain parameters of iterative learning in real time.Simulation and experiment show the FIIL-ADRC scheme has better control performance.

关 键 词：Active scheme ITERATIVE 

分 类 号：S24[农业科学—农业电气化与自动化] TP273[农业科学—农业工程]