An Auxiliary-Model-Based Stochastic Gradient Algorithm for Dual-Rate Sampled-Data Box-Jenkins Systems

作者：Chen, Jing; Ding, Rui^*

来源：Circuits, Systems, and Signal Processing, 2013, 32(5): 2475-2485.

DOI：10.1007/s00034-013-9563-x

• Parameter estimation
• Auxiliary model
• Dual-rate system
• Stochastic gradient
• Box-Jenkins system

This paper presents an identification algorithm for Box-Jenkins systems by combining the auxiliary model identification idea and the gradient search principle. The proposed algorithm can estimate all unknown parameters of the Box-Jenkins systems. Furthermore, to improve the convergence rate of the stochastic gradient algorithm, a modified stochastic gradient algorithm is given. The simulation results indicate that the proposed algorithm can work well.

• 单位
  江南大学