Systematic Modeling for Free Stators of Rotary Piezoelectric Ultrasonic Motors

This paper presents an equivalent circuit model with complex numbers that describes the free stator model of traveling-wave ultrasonic motors. The mechanical, dielectric, and piezoelectric losses associated with the vibrator are considered by introducing the imaginary part to the equivalent circuit elements. The determination of the complex circuit elements is performed by using a new, simple iterative method. The presented method uses information about five points of the stator admittance measurements. The accuracy of the model in fitting to the experimental data is verified by using the measurements of a recently developed piezoelectric motor and a well-known USR60     

Chaotic invasive weed optimization algorithm with application to parameter estimation of chaotic systems

This paper introduces a novel hybrid optimization algorithm by taking advantage of the stochastic properties of chaotic search and the invasive weed optimization (IWO) method. In order to deal with the weaknesses associated with the conventional method, the proposed chaotic invasive weed optimization (CIWO) algorithm is presented which incorporates the capabilities of chaotic search methods. The functionality of the proposed optimization algorithm is investigated through several benchmark multi-dimensional functions. Furthermore, an identification technique for chaotic systems based on the CIWO algorithm is outlined and validated by several examples. The results established upon the proposed scheme are also supplemented which demonstrate superior performance with respect to other conventional methods.     

Identification of multiple-input single-output Hammerstein models using Bezier curves and Bernstein polynomials

This paper considers the implementation of Bezier–Bernstein polynomials and the Levenberg–Marquart algorithm for identifying multiple-input single-output (MISO) Hammerstein models consisting of nonlinear static functions followed by a linear dynamical subsystem. The nonlinear static functions are approximated by the means of Bezier curves and Bernstein basis functions. The identification method is based on a hybrid scheme including the inverse de Casteljau algorithm, the least squares method, and the Levenberg–Marquart (LM) algorithm. Furthermore, results based on the proposed scheme are given which demonstrate substantial identification performance.