To address the low accuracy and stability when applying classical control theory in distribution networks with distributed generation,a control method involving flexible multistate switches(FMSs)is proposed in this st...To address the low accuracy and stability when applying classical control theory in distribution networks with distributed generation,a control method involving flexible multistate switches(FMSs)is proposed in this study.This approach is based on an improved double-loop recursive fuzzy neural network(DRFNN)sliding mode,which is intended to stably achieve multiterminal power interaction and adaptive arc suppression for single-phase ground faults.First,an improved DRFNN sliding mode control(SMC)method is proposed to overcome the chattering and transient overshoot inherent in the classical SMC and reduce the reliance on a precise mathematical model of the control system.To improve the robustness of the system,an adaptive parameter-adjustment strategy for the DRFNN is designed,where its dynamic mapping capabilities are leveraged to improve the transient compensation control.Additionally,a quasi-continuous second-order sliding mode controller with a calculus-driven sliding mode surface is developed to improve the current monitoring accuracy and enhance the system stability.The stability of the proposed method and the convergence of the network parameters are verified using the Lyapunov theorem.A simulation model of the three-port FMS with its control system is constructed in MATLAB/Simulink.The simulation result confirms the feasibility and effectiveness of the proposed control strategy based on a comparative analysis.展开更多
We studied carrier landing robust control based on longitudinal decoupling.Firstly,due to the relative strong coupling between the tangential and the normal directions,the height and the velocity channels were decoupl...We studied carrier landing robust control based on longitudinal decoupling.Firstly,due to the relative strong coupling between the tangential and the normal directions,the height and the velocity channels were decoupled by using the exact linearization method,so that controllers for the two channels could be designed seperately.In the height control,recursive dynamic surface was used to accelerate the convergence of the height control and eliminate″the explosion of complexity″.The radial basis function(RBF)neural network was designed by using the minimum learning parameter method to compensate the uncertainty.A kind of surface with nonsingular fast terminal sliding mode and its reaching law were developed to ensure finite time convergence and to avoid singularity.The controller for the velocity was designed by using super-twisting second-order sliding mode control.The stability of the proposed system was validated by Lyapunov method.The results showed that the Levant′s robust differential observer was improved and used for the observation of the required higher order differential of signals in the controller.The response of aircraft carrier landing under the complex disturbance is simulated and the results verified the approach.展开更多
基金the Natural Science Foundation of Fujian,China(No.2021J01633).
文摘To address the low accuracy and stability when applying classical control theory in distribution networks with distributed generation,a control method involving flexible multistate switches(FMSs)is proposed in this study.This approach is based on an improved double-loop recursive fuzzy neural network(DRFNN)sliding mode,which is intended to stably achieve multiterminal power interaction and adaptive arc suppression for single-phase ground faults.First,an improved DRFNN sliding mode control(SMC)method is proposed to overcome the chattering and transient overshoot inherent in the classical SMC and reduce the reliance on a precise mathematical model of the control system.To improve the robustness of the system,an adaptive parameter-adjustment strategy for the DRFNN is designed,where its dynamic mapping capabilities are leveraged to improve the transient compensation control.Additionally,a quasi-continuous second-order sliding mode controller with a calculus-driven sliding mode surface is developed to improve the current monitoring accuracy and enhance the system stability.The stability of the proposed method and the convergence of the network parameters are verified using the Lyapunov theorem.A simulation model of the three-port FMS with its control system is constructed in MATLAB/Simulink.The simulation result confirms the feasibility and effectiveness of the proposed control strategy based on a comparative analysis.
基金supported in part by the National Natural Science Foundation of China(No.51505491)
文摘We studied carrier landing robust control based on longitudinal decoupling.Firstly,due to the relative strong coupling between the tangential and the normal directions,the height and the velocity channels were decoupled by using the exact linearization method,so that controllers for the two channels could be designed seperately.In the height control,recursive dynamic surface was used to accelerate the convergence of the height control and eliminate″the explosion of complexity″.The radial basis function(RBF)neural network was designed by using the minimum learning parameter method to compensate the uncertainty.A kind of surface with nonsingular fast terminal sliding mode and its reaching law were developed to ensure finite time convergence and to avoid singularity.The controller for the velocity was designed by using super-twisting second-order sliding mode control.The stability of the proposed system was validated by Lyapunov method.The results showed that the Levant′s robust differential observer was improved and used for the observation of the required higher order differential of signals in the controller.The response of aircraft carrier landing under the complex disturbance is simulated and the results verified the approach.
