caa a22 4500 606205330 CHVBK 20210128101006.0 cr unu---uuuuu 210128e20150701xx s 000 0 eng 10.1007/s00034-014-9939-6 doi (NATIONALLICENCE)springer-10.1007/s00034-014-9939-6 Fault Tolerant Control for Near Space Vehicles with Input Saturation Using Disturbance Observer and Neural Networks [Elektronische Daten] [Jing Yu, Mou Chen] In this paper, a fault tolerant sliding mode control scheme is derived for near space vehicles with actuator faults, unknown external disturbance, system uncertainty and input saturation based on disturbance observer and neural networks (NNs). To deal with actuator faults, the radial basis function NNs are employed. The nonlinear disturbance observer is designed to eliminate the effect of external disturbance and system uncertainty. To tackle input saturation, the known bound of saturation is used to design the control law such that the control input is within the bounded range. Lyapunov stability analysis shows that the closed-loop system is stable and all closed-loop signals are uniformly ultimately bounded. Simulation results demonstrate the effectiveness of the developed fault tolerant control scheme, when actuator faults, unknown external disturbance, system uncertainty and input saturation appear simultaneously. Springer Science+Business Media New York, 2014 Near space vehicle nationallicence Fault tolerant control nationallicence Sliding mode control nationallicence Input saturation nationallicence Disturbance observer nationallicence Neural networks nationallicence Yu Jing College of Automation Engineering, Nanjing University of Aeronautics and Astronautics, 210016, Nanjing, China aut Chen Mou College of Automation Engineering, Nanjing University of Aeronautics and Astronautics, 210016, Nanjing, China aut Circuits, Systems, and Signal Processing Springer US; http://www.springer-ny.com 34/7(2015-07-01), 2091-2107 0278-081X 34:7<2091 2015 34 34 https://doi.org/10.1007/s00034-014-9939-6 text/html Onlinezugriff via DOI BK010053 XK010053 XK010000 Metadata rights reserved Springer special CC-BY-NC licence nationallicence 1 research-article jats NATIONALLICENCE NATIONALLICENCE NL-springer NATIONALLICENCE 856 40 https://doi.org/10.1007/s00034-014-9939-6 text/html Onlinezugriff via DOI NATIONALLICENCE 700 1- Yu Jing College of Automation Engineering, Nanjing University of Aeronautics and Astronautics, 210016, Nanjing, China aut NATIONALLICENCE 700 1- Chen Mou College of Automation Engineering, Nanjing University of Aeronautics and Astronautics, 210016, Nanjing, China aut NATIONALLICENCE 773 0- Circuits, Systems, and Signal Processing Springer US; http://www.springer-ny.com 34/7(2015-07-01), 2091-2107 0278-081X 34:7<2091 2015 34 34