{"title":"Neuroadaptive high-order fully-actuated system approach for roll autopilot with unknown uncertainties","authors":"","doi":"10.1016/j.ast.2024.109567","DOIUrl":null,"url":null,"abstract":"<div><p>In this paper, a neuroadaptive high-order fully-actuated system approach control scheme incorporating the disturbance observer technique is proposed for the missile roll autopilot, subject to model uncertainties generated by the induced roll moment, along with actuator control efficiency deterioration and external disturbance. To address model uncertainties, the radial basis function neural network is implemented. The external disturbance and approximation error are treated as compound disturbances and estimated by a nonlinear disturbance. To avoid the “differential explosion” inherent in the backstepping technique, the high-order fully-actuated system approach is invoked to track the desired roll angle command. The semi-globally uniformly bounded of the closed-loop system is demonstrated via the Lyapunov method. Numerous simulations under various conditions have been conducted to verify the effectiveness of the proposed roll autopilot.</p></div>","PeriodicalId":50955,"journal":{"name":"Aerospace Science and Technology","volume":null,"pages":null},"PeriodicalIF":5.0000,"publicationDate":"2024-09-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Aerospace Science and Technology","FirstCategoryId":"5","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S1270963824006977","RegionNum":1,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"ENGINEERING, AEROSPACE","Score":null,"Total":0}
引用次数: 0
Abstract
In this paper, a neuroadaptive high-order fully-actuated system approach control scheme incorporating the disturbance observer technique is proposed for the missile roll autopilot, subject to model uncertainties generated by the induced roll moment, along with actuator control efficiency deterioration and external disturbance. To address model uncertainties, the radial basis function neural network is implemented. The external disturbance and approximation error are treated as compound disturbances and estimated by a nonlinear disturbance. To avoid the “differential explosion” inherent in the backstepping technique, the high-order fully-actuated system approach is invoked to track the desired roll angle command. The semi-globally uniformly bounded of the closed-loop system is demonstrated via the Lyapunov method. Numerous simulations under various conditions have been conducted to verify the effectiveness of the proposed roll autopilot.
期刊介绍:
Aerospace Science and Technology publishes articles of outstanding scientific quality. Each article is reviewed by two referees. The journal welcomes papers from a wide range of countries. This journal publishes original papers, review articles and short communications related to all fields of aerospace research, fundamental and applied, potential applications of which are clearly related to:
• The design and the manufacture of aircraft, helicopters, missiles, launchers and satellites
• The control of their environment
• The study of various systems they are involved in, as supports or as targets.
Authors are invited to submit papers on new advances in the following topics to aerospace applications:
• Fluid dynamics
• Energetics and propulsion
• Materials and structures
• Flight mechanics
• Navigation, guidance and control
• Acoustics
• Optics
• Electromagnetism and radar
• Signal and image processing
• Information processing
• Data fusion
• Decision aid
• Human behaviour
• Robotics and intelligent systems
• Complex system engineering.
Etc.