Fault-Tolerant Active Disturbance Rejection Control of Plant Protection of Unmanned Aerial Vehicles Based on a Spatio-Temporal RBF Neural Network

Lianghao Hua,Jianfeng Zhang,Dejie Li,Xiaobo Xi

doi:10.3390/app11094084

Abstract

This paper presents a fault-tolerant flight control method for a multi-rotor UAV under actuator failure and external wind disturbances. The control method is based on an active disturbance rejection controller (ADRC) and spatio-temporal radial basis function neural networks, which can be used to achieve the stable control of the system when the parameters of the UAV mathematical model change. Firstly, an active disturbance rejection controller with an optimized parameter design is designed for rthe obust control of a multi-rotor vehicle. Secondly, a spatio-temporal radial basis function neural network with a new adaptive kernel is designed. In addition, the output of the novel radial basis function neural network is used to estimate fusion parameters containing actuator faults and model uncertainties and, consequently, to design an active fault-tolerant controller for a multi-rotor vehicle. Finally, fault injection experiments are carried out with the Qball-X4 quadrotor UAV as a specific research object, and the experimental results show the effectiveness of the proposed self-tolerant, fault-tolerant control method.

Highlights

With the advent of the Internet, multi-rotor unmanned aerial vehicles (UAVs) have rapidly developed in the consumption field and in the sectors of logistics and transportation, warehouse inspection, and agricultural spraying [1]
The flight stability of an aircraft may be adversely influenced by external disturbances and actuator faults
To address the above problems, we integrated an active disturbance rejection control (ADRC) controller with a spatio-temporal radial basis function (RBF) neural network to construct an fault-tolerant aircraft control (FTAC) scheme. This RBF neural network was capable of the online estimation of uncertain terms in the system model

Summary

Introduction

With the advent of the Internet, multi-rotor unmanned aerial vehicles (UAVs) have rapidly developed in the consumption field and in the sectors of logistics and transportation, warehouse inspection, and agricultural spraying [1]. With the increase in the number of the airborne equipment and tasks to be performed, multi-rotor UAVs are no longer a simple nonlinear systems [2]. They have begun to evolve toward a more complex system [3,4,5,6]. Adaptive technology is combined with a sliding-mode controller to achieve stability in finite time [10]. Along with the development of fault-tolerant control (FTC) theory [14,15,16,17], several researchers have attempted to use the robust adaptive approach to solve the FTC problem of a nonlinear system with actuator faults [18,19]

Methods

Results

Conclusion