Title :
Rate of convergence analysis of simultaneous perturbation stochastic approximation algorithm for time-varying loss function
Author :
Qi Wang ; Ming Ye
Author_Institution :
Dept. of Appl. Math. & Stat., Johns Hopkins Univ., Baltimore, MD, USA
Abstract :
A popular method for continuous stochastic optimization problem is simultaneous perturbation stochastic approximation (SPSA). Spall (1992) introduces SPSA and discusses the rate of convergence of SPSA for fixed loss functions. In this paper, we use different criteria to discuss the rate of convergence of SPSA for time-varying loss functions. The rate of convergence result shows that SPSA is an effective algorithm for time-varying problems, such as the model-free adaptive control of nonlinear stochastic systems with unknown dynamics.
Keywords :
adaptive control; convergence; nonlinear control systems; perturbation techniques; stochastic processes; stochastic systems; SPSA; continuous stochastic optimization problem; convergence analysis; convergence rate; fixed loss function; model-free adaptive control; nonlinear stochastic systems; simultaneous perturbation stochastic approximation algorithm; time-varying loss function; time-varying problem; unknown dynamics; Optimization; Stochastic systems; Time-varying systems;
Conference_Titel :
American Control Conference (ACC), 2014
Conference_Location :
Portland, OR
Print_ISBN :
978-1-4799-3272-6
DOI :
10.1109/ACC.2014.6859379
