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The problem of fault estimation and accommodation of nonlinear systems with disturbances is studied in this paperusing adaptive observer and neural network techniques. A robust adaptive learning algorithm based on switchings? ? modification is developed to realize the accurate and fast estimation of unknown actuator faults or component faults. Thena fault tolerant controller is designed to restore system performance. Dynamic error convergence and system stability can beguaranteed by Lyapunov stability theory. Finally, simulation results of quadrotor helicopter attitude systems are presented toillustrate the efficiency of the proposed techniques.
The problem of fault estimation and accommodation of nonlinear systems with disturbances is studied in this paper using adaptive observer and neural network techniques. A modification of developed learning algorithm based on switchings?? Modification is developed to realize the accurate and fast estimation of unknown actuator faults or component faults. Thena 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 toillustrate the efficiency of the proposed technique.