Work

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

Year: 2024

Type: article

Abstract: 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.

Source: IEEE/CAA Journal of Automatica Sinica

DOI: 10.1109/jas.2023.124158

Authors: Tao Chen, Ruiyuan Zhao, Jian Chen, Zichao Zhang

Institutions: China Agricultural University, Ministry of Agriculture and Rural Affairs

Language: English

Topic: Iterative Learning Control Systems

Subfield: Control and Systems Engineering

Field: Engineering

Domain: Physical Sciences

Open Access status: bronze

Funders: National Natural Science Foundation of China, China Agricultural University, National Key Research and Development Program of China

Awards: G1804204912, G1848906230, G6006264290