A robust adaptive control scheme with prescribed performance is proposed for attitude maneuver and vibration suppression of flexible spacecraft,in which the parametric uncertainty,external disturbances and unmeasured ...A robust adaptive control scheme with prescribed performance is proposed for attitude maneuver and vibration suppression of flexible spacecraft,in which the parametric uncertainty,external disturbances and unmeasured elastic vibration are taken into account simultaneously.On the basis of the prescribed performance control(PPC)theory,the prescribed steady state and transient performance for the attitude tracking error can be guaranteed through the stabilization of the transformed system.This controller does not need the knowledge of modal variables.The absence of measurements of these variables is compensated by appropriate dynamics of the controller which supplies their estimates.The method of sliding mode differentiator is introduced to overcome the problem of explosion of complexity inherent in traditional backstepping design.In addition,the requirements of knowing the system parameters and the unknown bound of the lumped uncertainty,including external disturbance and the estimate error of sliding mode differentiator,have been eliminated by using adaptive updating technique.Within the framework of Lyapunov theory,the stability of the transformed system is obtained.Finally,numerical simulations are carried out to verify the effectiveness of the proposed control scheme.展开更多
A novel adaptive neural control strategy is exploited for the longitudinal dynamics of a generic flexible air-breathing hypersonic vehicle（FAHV）.By utilizing functional decomposition method, the dynamics of FAHV is ...A novel adaptive neural control strategy is exploited for the longitudinal dynamics of a generic flexible air-breathing hypersonic vehicle（FAHV）.By utilizing functional decomposition method, the dynamics of FAHV is decomposed into the velocity subsystem and the altitude subsystem.For each subsystem, only one neural network is employed for the unknown function approximation.To further reduce the computational burden, minimal-learning parameter（MLP）technology is used to estimate the norm of ideal weight vectors rather than their elements.By introducing sliding mode differentiator（SMD） to estimate the newly defined variables, there is no need for the strict-feedback form and virtual controller.Hence the developed control law is considerably simpler than the ones derived from back-stepping scheme.Finally, simulation studies are made to illustrate the effectiveness of the proposed control approach in spite of the flexible effects, system uncertainties and varying disturbances.展开更多
文摘A robust adaptive control scheme with prescribed performance is proposed for attitude maneuver and vibration suppression of flexible spacecraft,in which the parametric uncertainty,external disturbances and unmeasured elastic vibration are taken into account simultaneously.On the basis of the prescribed performance control(PPC)theory,the prescribed steady state and transient performance for the attitude tracking error can be guaranteed through the stabilization of the transformed system.This controller does not need the knowledge of modal variables.The absence of measurements of these variables is compensated by appropriate dynamics of the controller which supplies their estimates.The method of sliding mode differentiator is introduced to overcome the problem of explosion of complexity inherent in traditional backstepping design.In addition,the requirements of knowing the system parameters and the unknown bound of the lumped uncertainty,including external disturbance and the estimate error of sliding mode differentiator,have been eliminated by using adaptive updating technique.Within the framework of Lyapunov theory,the stability of the transformed system is obtained.Finally,numerical simulations are carried out to verify the effectiveness of the proposed control scheme.
基金supported by the Aeronautical Science Foundation of China (No.20130196004)
文摘A novel adaptive neural control strategy is exploited for the longitudinal dynamics of a generic flexible air-breathing hypersonic vehicle（FAHV）.By utilizing functional decomposition method, the dynamics of FAHV is decomposed into the velocity subsystem and the altitude subsystem.For each subsystem, only one neural network is employed for the unknown function approximation.To further reduce the computational burden, minimal-learning parameter（MLP）technology is used to estimate the norm of ideal weight vectors rather than their elements.By introducing sliding mode differentiator（SMD） to estimate the newly defined variables, there is no need for the strict-feedback form and virtual controller.Hence the developed control law is considerably simpler than the ones derived from back-stepping scheme.Finally, simulation studies are made to illustrate the effectiveness of the proposed control approach in spite of the flexible effects, system uncertainties and varying disturbances.
