DocumentCode
2044398
Title
On asynchronous stochastic learning control method
Author
Sun Zengqi ; Deng Zhidong
Author_Institution
Dept. of Comput. Sci. & Technol., Tsinghua Univ., Beijing, China
Volume
4
fYear
1993
fDate
19-21 Oct. 1993
Firstpage
329
Abstract
In view of the limitation that a general asynchronous learning control method is unable to cope with systems with measurement noise, an asynchronous stochastic learning control system (ASLC) using stochastic approximation algorithm, is proposed. The corresponding convergence proof is given. To improve the convergence rate of stochastic approximation, ASLC with acceleration factor is further presented. A simulation example is given.<>
Keywords
approximation theory; closed loop systems; convergence of numerical methods; learning systems; self-adjusting systems; acceleration factor; asynchronous stochastic learning control; closed loop systems; convergence rate; iterative control; repetitive control; stochastic approximation algorithm; Automatic logic units; Costs; Error correction; Low pass filters; Noise measurement; Radio access networks; Stability; Stochastic processes; Stochastic resonance; Sun;
fLanguage
English
Publisher
ieee
Conference_Titel
TENCON '93. Proceedings. Computer, Communication, Control and Power Engineering.1993 IEEE Region 10 Conference on
Conference_Location
Beijing, China
Print_ISBN
0-7803-1233-3
Type
conf
DOI
10.1109/TENCON.1993.320499
Filename
320499
Link To Document