DocumentCode :
2839931
Title :
Synchronization of Ghostburster neurons using high order sliding mode control
Author :
Han, Chun-Xiao ; Wang, Jiang ; Che, Yan-Qiu ; Zhou, Si-Si
Author_Institution :
Sch. of Electr. Eng. & Autom., Tianjin Univ., Tianjin, China
fYear :
2010
fDate :
26-28 May 2010
Firstpage :
4371
Lastpage :
4376
Abstract :
In this paper, high order sliding mode control is proposed to realize the synchronization of two Ghostburster neurons under external electrical stimulation. Being a motion on a discontinuity set of a dynamic system, the sliding mode is used to keep accurately a given constraint and features theoretically-infinite-frequency switching. As the high order sliding mode technique employed in this paper, it considers a fractional power of the absolute value of the tracking error coupled with the sign function. This structure provides several advantages such as the simplification of the control law, higher accuracy and chattering prevention. Firstly we analyze the periodic and chaotic dynamics of individual Ghostburster neuron under different external electrical stimulus, then high order sliding mode controller is designed to synchronize two Ghostburster neurons and drive the slave neuron to act as the master one. Asymptotic synchronization of the system can be obtained by proper choice of the control parameters. Simulation results demonstrate the effectiveness of the proposed control method.
Keywords :
medical control systems; neural nets; neurophysiology; variable structure systems; Ghostburster neuron synchronization; asymptotic synchronization; chaotic dynamics; electrical stimulation; fractional power; high order sliding mode control; periodic dynamics; theoretically-infinite-frequency switching; Biological systems; Brain modeling; Chaos; Control systems; Mathematical model; Neural networks; Neurons; Nonlinear control systems; Nonlinear dynamical systems; Sliding mode control; Ghostburster; High order sliding mode control; Synchronization;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Control and Decision Conference (CCDC), 2010 Chinese
Conference_Location :
Xuzhou
Print_ISBN :
978-1-4244-5181-4
Electronic_ISBN :
978-1-4244-5182-1
Type :
conf
DOI :
10.1109/CCDC.2010.5498358
Filename :
5498358
Link To Document :
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