The Design of Self-Adaptive Controller Based on Hopfield Neural Network

Author

Wen-Shang, Xu ; Shao-hua, Chen

Author_Institution

Coll. of Inf. & Electr. Eng., Shan Dong Univ. of Sci. & Technol., Qingdao, China

Volume

1

fYear

2009

fDate

10-11 Oct. 2009

Firstpage

112

Lastpage

116

Abstract

Hopfield network is a typical feedback network, All of its neurons are connected to each other and it has rich dynamic characteristics. Hopfield network solve the Tsp Traveling Salesman Problem well, it has been applied to optimal computation and associative memory and proved to be very effective. However, in the control system is also in an initial stage. This paper studied the problem of controller design in Hopfield network,combine equation of Lyapunov, discuss the stability of the system, advance the design of controller. Finally, simulate the control system by Matlab,the effect is very well.

Keywords

Hopfield neural nets; Lyapunov methods; adaptive control; control system synthesis; neurocontrollers; self-adjusting systems; Hopfield neural network; Lyapunov equation; Matlab; controller design; feedback network; self-adaptive controller; system stability; Associative memory; Computational modeling; Computer networks; Control systems; Equations; Hopfield neural networks; Neurofeedback; Neurons; Stability; Traveling salesman problems; Hopfield network; Tsp; equation of Lyapunov;

fLanguage

English

Publisher

ieee

Conference_Titel

Intelligent Computation Technology and Automation, 2009. ICICTA '09. Second International Conference on

Conference_Location

Changsha, Hunan

Print_ISBN

978-0-7695-3804-4

Type

conf

DOI

10.1109/ICICTA.2009.36

Filename

5287694