Intelligent complementary sliding-mode control with dead-zone parameter modification

2014 ◽  
Vol 23 ◽  
pp. 355-365 ◽  
Author(s):  
Chun-Fei Hsu ◽  
Tzu-Chun Kuo
Keyword(s):  
Sliding Mode Control ◽  
Sliding Mode ◽  
Dead Zone ◽  
Mode Control ◽  
Zone Parameter ◽  
Parameter Modification

Chaotic Gyros Synchronization

2011 ◽  
pp. 183-209
Author(s):  
M. Roopaei ◽  
M. J. Zolghadri ◽  
B. S. Ranjbar ◽  
S. H. Mousavi ◽  
H. Adloo ◽  
...  
Keyword(s):  
Sliding Mode Control ◽  
Control Method ◽  
Fuzzy Controller ◽  
Sliding Mode ◽  
Dead Zone ◽  
Control Input ◽  
Mode Control ◽  
Fuzzy Sliding Mode ◽  
Robust Adaptive ◽  
Fuzzy Parameter

In this chapter, three methods for synchronizing of two chaotic gyros in the presence of uncertainties, external disturbances and dead-zone nonlinearity are studied. In the first method, there is dead-zone nonlinearity in the control input, which limits the performance of accurate control methods. The effects of this nonlinearity will be attenuated using a fuzzy parameter approximator integrated with sliding mode control method. In order to overcome the synchronization problem for a class of unknown nonlinear chaotic gyros a robust adaptive fuzzy sliding mode control scheme is proposed in the second method. In the last method, two different gyro systems have been considered and a fuzzy controller is proposed to eliminate chattering phenomena during the reaching phase of sliding mode control. Simulation results are also provided to illustrate the effectiveness of the proposed methods.

SLIDING MODE CONTROL OF LORENZ SYSTEM WITH MULTIPLE INPUTS CONTAINING SECTOR NONLINEARITIES AND DEAD ZONE

2008 ◽  
Vol 22 (13) ◽  
pp. 2187-2196 ◽  
Author(s):  
XINGYUAN WANG ◽  
MING LIU ◽  
MINGJUN WANG ◽  
YIJIE HE
Keyword(s):  
Sliding Mode Control ◽  
Lorenz System ◽  
Sliding Mode ◽  
Dead Zone ◽  
Mode Control ◽  
Strong Robustness ◽  
Sector Nonlinearities

This paper designs the controller for uncertain Lorenz system with multiple inputs containing sector nonlinearities and dead zone, and theoretically demonstrates the effectiveness of this controller. By this controller, the controlled Lorenz system can asymptotically drive the system orbits to arbitrarily objective trajectories even with uncertainties and sector nonlinearities and dead zone in the inputs, and thus has strong robustness. Finally, through the emulation studies of controlled Lorenz systems, it demonstrates the effectiveness of this controller.

Adaptive Sliding Mode Control for Depth Trajectory Tracking of Remotely Operated Vehicle with Thruster Nonlinearity

2016 ◽  
Vol 70 (1) ◽  
pp. 149-164 ◽  
Author(s):  
Zhenzhong Chu ◽  
Daqi Zhu ◽  
Simon X. Yang ◽  
Gene Eu Jan
Keyword(s):  
Sliding Mode Control ◽  
Trajectory Tracking ◽  
Sliding Mode ◽  
Dead Zone ◽  
Adaptive Sliding Mode Control ◽  
Remotely Operated Vehicle ◽  
Trajectory Tracking Control ◽  
Adaptive Sliding Mode ◽  
Saturation Nonlinearity ◽  
Mode Control

This paper focuses on depth trajectory tracking control for a Remotely Operated Vehicle (ROV) with dead-zone nonlinearity and saturation nonlinearity of thruster; an adaptive sliding mode control method based on neural network is proposed. Through the analysis of dead-zone nonlinearity and saturation nonlinearity of thruster, the depth trajectory tracking control system model of a ROV which uses thruster control signals as system input has been established. According to the principle of sliding mode control, an adaptive sliding mode depth trajectory tracking controller is built by using three-layer feed-forward neural network for online identification of unknown items. The selection method and update laws of the control parameters are also given. The uniform ultimate boundedness of trajectory tracking error is analysed by Lyapunov theorem. Finally, the effectiveness of the proposed method is illustrated by simulations.

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