Global Sliding Mode Control for Brushless DC Motors by Neural Networks

Author(s):  
Zhiqiang Cheng ◽  
Chongsheng Hou ◽  
Xiaojin Wu
2014 ◽  
Vol 596 ◽  
pp. 584-589
Author(s):  
Xi Jie Yin ◽  
Jian Guo Xu

The sliding mode variable structure control method for brushless DC motors with uncertain external disturbances and unknown loads is studied. A neural sliding mode control scheme is proposed for reducing chattering of sliding mode control. A global sliding mode manifold is designed in this approach, which guarantees that the system states can be on the sliding mode manifold at initial time and the system robustness is increased. A radial basis function neural network (RBFNN) is applied to learn the maximum of unknown loads and external disturbances. Based on the neural networks, the switching control parameters of sliding mode control can be adaptively adjusted with uncertain external disturbances and unknown loads. Therefore, the chattering of the sliding mode controller is reduced. Simulation results proved that this control scheme is valid.


2008 ◽  
Vol 56 (1-2) ◽  
pp. 193-198 ◽  
Author(s):  
Leipo Liu ◽  
Zhengzhi Han ◽  
Wenlin Li

2013 ◽  
Vol 846-847 ◽  
pp. 134-138
Author(s):  
Jue Wang ◽  
Fei Li ◽  
Ye Huang ◽  
Jian Hao Wang ◽  
Hong Lin Zhang

The paper studies the problem of tracking control for flight simulator servo systems, one typical CPS, with parameter uncertainties and nonlinear friction compensation. Methods of adaptive global sliding mode control and backstepping control are respectively proposed to realize the control of virtual rotational speed and position tracking. Adaptive backstepping global sliding mode control strategy for flight simulator servo systems is proposed and its stability is analyzed. Simulation results show the effectiveness of the proposed method, which could achieve the precision position tracking performance and eliminate the chattering.


2018 ◽  
Vol 2018 ◽  
pp. 1-8 ◽  
Author(s):  
Dan-xu Zhang ◽  
Yang-wang Fang ◽  
Peng-fei Yang ◽  
You-li Wu ◽  
Tong-xin Liu

This paper proposed a finite time convergence global sliding mode control scheme for the second-order multiple models control system. Firstly, the global sliding surface without reaching law for a single model control system is designed and the tracking error finite time convergence and global stability are proved. Secondly, we generalize the above scheme to the second-order multimodel control system and obtain the global sliding mode control law. Then, the convergent and stable performances of the closed-loop control system with multimodel controllers are proved. Finally, a simulation example shows that the proposed control scheme is more effective and useful compared with the traditional sliding mode control scheme.


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