Centralized nonlinear fusion filter design problem is to construct an asymptotically stable observer that leads to a stable estimation error process whose L2 gain with respect to disturbance signal is less than a prescribed level for state estimation of the multi-sensor fusion system. This paper tries to resolve the problem in using of H∞ filtering theory and LMI methods under certain condition...

Recently, particle filters have attracted attentions for nonlinear state estimation. In this approaches, a posterior probability distribution of the state variable is evaluated based on observations in simulation using so-called importance sampling. We proposed a new filter, Evolution Strategies based particle (ESP) filter to circumvent degeneracy phenomena in the importance weights, which dete...

This paper compares the target displacement estimate from four current nonlinear static procedures—FEMA-356 CM, ASCE­ 41 CM, ATC-40 CSM, and FEMA-440 CSM—with the value derived from recorded motions of five strongly shaken reinforced concrete buildings.This comparison provides useful insight into two important questions: (1) how much does the target displacement vary among the four nonlinear st...

System identification is the theory and methods of establishing mathematical models of the systems. As one of the key issues of system and control science, system identification has been widely applied to the design and analysis of the control system. Accordingly, system identification becomes one of the current active subjects. Currently, parameter estimation of the nonlinear system models is ...

The problem of estimating unmeasured state and disturbance variables for nonlinear process control applications is considered. We assume that the process model is affine with respect to the unmeasured disturbances and any unmeasured state variables. The disturbances are considered as additional state variables, and a nonlinear observer is designed for the augmented state-space system. The obser...