Power system stabilizers have been widely used and successfully implemented for the improvement of power system damping. However, a fixed parameter power system stabilizer tends to be sensitive to variations in generator dynamics so that, for operating conditions away from those used for design, the effectiveness of the stabilizer can be greatly impaired. With the advent of microprocessor techn...

This paper presents a novel HDMR-Bayesian technique for dynamic system identification in a Bayesian framework. This technique is based on Bayesian Inference. Direct application of Bayesian inference in estimation and identification involves evaluation of multi-dimensional integrals in multidimensional systems. This is computationally complex and tedious. The proposed technique addresses this ch...

Dynamic mode decomposition has emerged as a leading technique to identify spatiotemporal coherent structures from high-dimensional data, benefiting from a strong connection to nonlinear dynamical systems via the Koopman operator. In this work, we integrate and unify two recent innovations that extend DMD to systems with actuation [56] and systems with heavily subsampled measurements [17]. When ...

Field of system identification have become important discipline. Identification is basically the process of developing or improving a mathematical representation of a physical system using experimental data. The artificial neural network is a newly developed technique among the identification methods. Dynamic function mapping, including the structural dynamic model is still a challenging topic ...

A solution to the problem of identification and control of smart structures is presented in this paper. Smart structures with build-in sensors and actuators can actively and adaptively change their physical geometry and properties. As a particular example, a representative dynamic model of a typical fighter vertical tail, identified as the smart fin, is considered. Piezoelectric patches, which ...

Many high-dimensional time-varying signals can be modeled as a sequence of noisy nonlinear observations of a low-dimensional dynamical process. Given high-dimensional observations and a distribution describing the dynamical process, we present a computationally inexpensive approximate algorithm for estimating the inverse of this mapping. Once this mapping is learned, we can invert it to constru...

a solution to the problem of identification and control of smart structures is presented in this paper. smart structures with build-in sensors and actuators can actively and adaptively change their physical geometry and properties. as a particular example, a representative dynamic model of a typical fighter vertical tail, identified as the smart fin, is considered. piezoelectric patches, which ...