scholarly journals Mathematical Modeling of Sliding Mode Reaching Laws for Buck Converter

In this paper, the load and line variations are analyzed for Sliding Mode reaching laws. Mathematical modeling has been done for all proposed sliding mode reaching laws, they are Exponential reaching law, Sigmoid reaching law, Tan hyperbolic, Robust reaching law, Improved tan hyperbolic reaching law and Double power reaching law. SMC has less sensitive for load and line disturbances. SMC (Sliding Mode Control) gives sensitive for load and line mutations due to chattering phenomenon. The comparative analyses for these reaching laws have been tested in buck converter. Chattering of all reaching laws are depicted. Among these reaching laws, tan hyperbolic reaching law gives efficient and insensitive for line and load mutations, even for parametric uncertainties and simulation results are validated through MATLAB/Simulink

Energies ◽  
2017 ◽  
Vol 10 (11) ◽  
pp. 1788 ◽  
Author(s):  
Linyun Xiong ◽  
Penghan Li ◽  
Hao Li ◽  
Jie Wang

2015 ◽  
Vol 741 ◽  
pp. 655-658 ◽  
Author(s):  
Cai Yun Dong ◽  
Hai Jun Wang ◽  
Wen Yong Cui

The sliding mode control approach based on double power exponential reaching law is proposed for the hydraulic servo system. With the example of the hydraulic servo system in the lab, the mathematic model is established and the new controller is presented and simulated. Simulation results show that: the proposed approach has high track precision, fast response, small chattering and ensures dynamic quality of the system.


2013 ◽  
Vol 2013 ◽  
pp. 1-9 ◽  
Author(s):  
Yu-Xin Zhao ◽  
Tian Wu ◽  
Yan Ma

For discrete system, the reaching law election and controller design are two crucial and important problems. In this paper, an improved double power reaching law of SMC and a controller combined with neural network have been investigated. Theory proves that this method can eliminate the chattering and increase the reaching rate. Furthermore, when there is a certain external interference, the regulating function of neural network can ensure strong robustness of the system. Simulation results show that compared with exponential reaching law, single power reaching law, and traditional double power reaching law, the proposed reaching law has faster convergence speed and better dynamic performance.


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