scholarly journals Synchronization of an Uncertain Fractional-Order Chaotic System via Backstepping Sliding Mode Control

2013 ◽  
Vol 2013 ◽  
pp. 1-6 ◽  
Author(s):  
Zhen Wang

Backstepping control approach combined with sliding mode control (SMC) technique is utilized to realize synchronization of uncertain fractional-order strict-feedback chaotic system. A backstepping SMC method is presented to compensate the uncertainty which occurs in the slave system. Moreover, the newly proposed control scheme is applied to implement synchronization of fractional-order Duffing-Holmes system. The simulation results demonstrate that the backstepping SMC method is robust against the modeling uncertainties and external disturbances.

2015 ◽  
Vol 2015 ◽  
pp. 1-9 ◽  
Author(s):  
Junbiao Guan ◽  
Kaihua Wang

A new fractional-order chaotic system is addressed in this paper. By applying the continuous frequency distribution theory, the indirect Lyapunov stability of this system is investigated based on sliding mode control technique. The adaptive laws are designed to guarantee the stability of the system with the uncertainty and external disturbance. Moreover, the modified generalized projection synchronization (MGPS) of the fractional-order chaotic systems is discussed based on the stability theory of fractional-order system, which may provide potential applications in secure communication. Finally, some numerical simulations are presented to show the effectiveness of the theoretical results.


Author(s):  
Qingcong Wu ◽  
Xingsong Wang ◽  
Bai Chen ◽  
Hongtao Wu

The novel contribution of this article is to propose a neural network–based sliding-mode control strategy for improving the position-control performance of a tendon sheath–actuated compliant rescue manipulator. Structural design of a rescue robot with slender and compliant mechanical structure is introduced. The developed robot is capable of drilling into the narrow space under debris and accommodating complicated configuration in ruins. Dynamics modeling and parameters identification of a compliant gripper with flexible tendon sheath transmission are researched and discussed. Moreover, the neural network–based sliding-mode control scheme developed based on radial basis function network is proposed to improve the position-control accuracy of the gripper with modeling uncertainties and external disturbances. The stability of the proposed control system is demonstrated using Lyapunov stability theory. Further experimental investigation including trajectory-tracking experiments and step-response experiments are conducted to confirm the effectiveness of the proposed neural network–based sliding-mode control scheme. Experimental results show that the proposed neural network–based sliding-mode control scheme is superior to cascaded proportional–integral–derivative controller and conventional sliding-mode controller in position-control application.


2020 ◽  
Vol 31 (1) ◽  
pp. 68-76

We constitute a control system for overhead crane with simultaneous motion of trolley and payload hoist to destinations and suppression of payload swing. Controller core made by sliding mode control (SMC) assures the robustness. This control structure is inflexible since using fixed gains. For overcoming this weakness, we integrate variable fractional-order derivative into SMC that leads to an adaptive system with adjustable parameters. We use Mittag–Leffler stability, an enhanced version of Lyapunov theory, to analyze the convergence of closed-loop system. Applying the controller to a practical crane shows the efficiency of proposed control approach. The controller works well and keeps the output responses consistent despite the large variation of crane parameters.


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