Journal of Systems Engineering and Electronics ›› 2021, Vol. 32 ›› Issue (5): 1053-1061.doi: 10.23919/JSEE.2021.000090

• New Developments on FDD and FTC Techniques • Previous Articles     Next Articles

PID-type fault-tolerant prescribed performance control of fixed-wing UAV

Ziquan YU1(), Youmin ZHANG2,*(), Bin JIANG1()   

  1. 1 College of Automation Engineering, Nanjing University of Aeronautics and Astronautics, Nanjing 211106, China
    2 Department of Mechanical, Industrial and Aerospace Engineering, Concordia University, Montreal H3G 1M8, Canada
  • Received:2021-05-02 Online:2021-10-18 Published:2021-11-04
  • Contact: Youmin ZHANG E-mail:yuziquan@nuaa.edu.cn;ymzhang@encs.concordia.ca;binjiang@nuaa.edu.cn
  • About author:|YU Ziquan received his Ph.D. degree in control science and engineering from Northwestern Polytechnical University, Xi’an, China, in 2019. From 2017 to 2019, he was a joint Ph.D. student supported by the China Scholarship Council with the Department of Mechanical, Industrial and Aerospace Engineering, Concordia University, Montreal, QC, Canada. He is currently with the College of Automation Engineering, Nanjing University of Aeronautics and Astronautics, Nanjing, China. His current research interests include fault-tolerant cooperative control of safety-critical systems, and guidance, navigation, and control of unmanned aerial vehicles. E-mail: yuziquan@nuaa.edu.cn||ZHANG Youmin received his B.S., M.S., and Ph.D. degrees in automatic control from Northwestern Polytechnical University, Xi’an, China, in 1983, 1986, and 1995, respectively. He is currently a professor with the Department of Mechanical, Industrial and Aerospace Engineering and the Concordia Institute of Aerospace Design and Innovation, Concordia University, Montreal, QC, Canada. He has authored seven books, more than 550 journal and conference papers, and book chapters. His current research interests include guidance, navigation, and control (GNC), fault detection and diagnosis (FDD), fault-tolerant control (FTC), and remote sensing with applications to unmanned aerial/space/ground/ marine vehicles, smart grids, and smart cities. Dr. Zhang is a fellow of CSME, a senior member of AIAA and IEEE, and a member of Technical Committee for several scientific societies. He is an editorial board member, deputy editor-in-chief, editor/associate editor of several international journals, including Journal of Intelligent & Robotic Systems, IEEE Trans. on Neural Networks and Learning Systems, and Guidance, Navigation and Control. He has served as the general chair, program chair, and IPC Member of several unmanned systems and renewable energies relevant international conferences, including as general chair and honorary general chair of the 2020, 2021, and 2022 International Conference on Unmanned Aircraft Systems (ICUAS), respectively. E-mail: ymzhang@encs.concordia.ca||JIANG Bin received his Ph.D. degree in automatic control from Northeastern University, Shenyang, China, in 1995. He has been a postdoctoral fellow or a research fellow in Singapore, France, and the USA, and a visiting professor in Canada. He is currently a chair professor of Cheung Kong Scholar Program in Ministry of Education, and vice president in Nanjing University of Aeronautics and Astronautics, Nanjing, China. His current research interests include fault diagnosis and fault-tolerant control and their applications. Dr. Jiang serves as an editor, an associate editor or an editorial board member for the IEEE Trans. on Cybernetics, IEEE Trans. on Neural Networks and Learning Systems, International Journal of Control, Automation Systems, Neurocomputing, Acta Automatica Sinica, and Journal of Astronautics. He is IEEE fellow and the chair of the Control Systems Chapter of the IEEE Nanjing Section and a member of the International Federation of Automatic Control Technical Committee on Fault Detection, Supervision, and Safety of Technical Processes. E-mail: binjiang@nuaa.edu.cn
  • Supported by:
    This work was supported by the National Natural Science Foundation of China (62003162, 61833013, 62020106003), the Natural Science Foundation of Jiangsu Province of China (BK20200416), the China Postdoctoral Science Foundation (2020TQ0151; 2020M681590), the State Key Laboratory of Synthetical Automation for Process Industries, Northeastern University (2019-KF-23-05), the 111 Project (B20007), and the Natural Sciences and Engineering Research Council of Canada

Abstract:

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.

Key words: unmanned aerial vehicle (UAV), fault-tolerant control (FTC), prescribed performance control (PPC), proportional-integral-derivative (PID), composite learning, actuator faults