An adaptive backstepping multi-sliding mode approximation variable structure control scheme is proposed for a class of uncertain nonlinear systems.An actuator model with compound nonlinear characteristics is establish...An adaptive backstepping multi-sliding mode approximation variable structure control scheme is proposed for a class of uncertain nonlinear systems.An actuator model with compound nonlinear characteristics is established based on the model decomposition method.The unmodeled dynamic term of the radial basis function neural network approximation system is presented.The Nussbaum gain design technique is utilized to overcome the problem that the control gain is unknown.The adaptive law estimation is used to estimate the upper boundary of neural network approximation and uncertain interference.The adaptive approximate variable structure control effectively weakens the control signal chattering while enhancing the robustness of the controller.Based on the Lyapunov stability theory,the stability of the entire control system is proved.The main advantage of the designed controller is that the compound nonlinear characteristics are considered and solved.Finally,simulation results are given to show the validity of the control scheme.展开更多
The objective of this research is to realize a composite nonlinear feedback control approach for a class of linear and nonlinear systems with parallel-distributed compensation along with sliding mode control technique...The objective of this research is to realize a composite nonlinear feedback control approach for a class of linear and nonlinear systems with parallel-distributed compensation along with sliding mode control technique.The proposed composite nonlinear feedback control approach consists of two parts.In a word,the first part provides the stability of the closed-loop system and the fast convergence response,as long as the second one improves transient response.In this research,the genetic algorithm in line with the fuzzy logic is designed to calculate constant controller coefficients and optimize the control effort.The effectiveness of the proposed design is demonstrated by servo position control system and inverted pendulum system with DC motor simulation results.展开更多
基金This work was supported by the National Social Science Foundation of China(No.17BGL270).
文摘An adaptive backstepping multi-sliding mode approximation variable structure control scheme is proposed for a class of uncertain nonlinear systems.An actuator model with compound nonlinear characteristics is established based on the model decomposition method.The unmodeled dynamic term of the radial basis function neural network approximation system is presented.The Nussbaum gain design technique is utilized to overcome the problem that the control gain is unknown.The adaptive law estimation is used to estimate the upper boundary of neural network approximation and uncertain interference.The adaptive approximate variable structure control effectively weakens the control signal chattering while enhancing the robustness of the controller.Based on the Lyapunov stability theory,the stability of the entire control system is proved.The main advantage of the designed controller is that the compound nonlinear characteristics are considered and solved.Finally,simulation results are given to show the validity of the control scheme.
文摘The objective of this research is to realize a composite nonlinear feedback control approach for a class of linear and nonlinear systems with parallel-distributed compensation along with sliding mode control technique.The proposed composite nonlinear feedback control approach consists of two parts.In a word,the first part provides the stability of the closed-loop system and the fast convergence response,as long as the second one improves transient response.In this research,the genetic algorithm in line with the fuzzy logic is designed to calculate constant controller coefficients and optimize the control effort.The effectiveness of the proposed design is demonstrated by servo position control system and inverted pendulum system with DC motor simulation results.
