Transactions of Nanjing University of Aeronautics & Astronautics
Non-Destructive Testing and Structural Health Monitoring in Aerospace 2018
Fault Estimation and Accommodation for a Class of Nonlinear System Based on Neural Network Observer
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Abstract:
The problem of fault estimation and accommodation of nonlinear systems with disturbances is studied using adaptive observer and neural network techniques. A robust adaptive learning algorithm based on switching βs-modification is developed to realize the accurate and fast estimation of unknown actuator faults or component faults. Then a fault tolerant controller is designed to restore system performance. Dynamic error convergence and system stability can be guaranteed by Lyapunov stability theory. Finally, simulation results of quadrotor helicopter attitude systems are presented to illustrate the efficiency of the proposed techniques.
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This work was supported by the National Natural Science Foundation of China (No.61533008), the Fund of National Engineering and Research Center for Commercial Aircraft Manufacturing (No.SAMC14-JS-15-053), and the Fundamental Research Funds for the Central Universities (No.NJ20150011).
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