Title :
On asynchronous stochastic learning control method
Author :
Sun Zengqi ; Deng Zhidong
Author_Institution :
Dept. of Comput. Sci. & Technol., Tsinghua Univ., Beijing, China
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;
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
DOI :
10.1109/TENCON.1993.320499
