Local recurrence based performance prediction and prognostics in the nonlinear and nonstationary systems Academic Article uri icon

abstract

  • This paper presents a local recurrence modeling approach for state and performance predictions in complex nonlinear and nonstationary systems. Nonstationarity is treated as the switching force between different stationary systems, which is shown as a series of finite time detours of system dynamics from the vicinity of a nonlinear attractor. Recurrence patterns are used to partition the system trajectory into multiple near-stationary segments. Consequently, piecewise eigen analysis of ensembles in each near-stationary segment can capture both nonlinear stochastic dynamics and nonstationarity. The experimental studies using simulated and real-world datasets demonstrate significant prediction performance improvements in comparison with other alternative methods. © 2011 Elsevier Ltd. All rights reserved.

author list (cited authors)

  • Yang, H., Bukkapatnam, S., & Barajas, L. G.

citation count

  • 25

publication date

  • August 2011