期刊
JOURNAL OF SYSTEMS ENGINEERING AND ELECTRONICS
卷 32, 期 5, 页码 1053-1061出版社
SYSTEMS ENGINEERING & ELECTRONICS, EDITORIAL DEPT
DOI: 10.23919/JSEE.2021.000090
关键词
unmanned aerial vehicle (UAV); fault-tolerant control (FTC); prescribed performance control (PPC); proportional-integral-derivative (PID); composite learning; actuator faults
类别
资金
- National Natural Science Foundation of China [62003162, 61833013, 62020106003]
- Natural Science Foundation of Jiangsu Province of China [BK20200416]
- China Postdoctoral Science Foundation [2020TQ0151, 2020M681590]
- State Key Laboratory of Synthetical Automation for Process Industries, Northeastern University [2019-KF-23-05]
- 111 Project [B20007]
- Natural Sciences and Engineering Research Council of Canada
This paper presents a fault-tolerant control design for a faulty UAV, employing PID control concept and a composite learning algorithm. Results show that tracking errors are strictly constrained within specified bounds, confirming the feasibility of the developed FTC scheme.
This paper introduces a fault-tolerant control (FTC) design for a faulty fixed-wing unmanned aerial vehicle (UAV). To constrain tracking errors against actuator faults, error constraint inequalities are first transformed to a new set of variables based on prescribed performance functions. Then, the commonly used and powerful proportional-integral-derivative (PID) control concept is employed to filter the transformed error variables. To handle the fault-induced nonlinear terms, a composite learning algorithm consisting of neural network and disturbance observer is incorporated for increasing flight safety. It is shown by Lyapunov stability analysis that the tracking errors are strictly constrained within the specified error bounds. Experimental results are presented to verify the feasibility of the developed FTC scheme.
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