Tao Zhang

Sun Yat-Sen University | SYSU · Aerospace Engineering

The complexity inherent in defining and computing fractional derivatives renders the development of a data-driven modeling framework for fractional-order systems more formidable than for their integer-order counterparts. This study introduces a methodology for sparsely identifying fractional chaotic systems by leveraging time-domain data to ascerta...

This paper proposes an adaptive integral alternating minimization method (AIAMM) for learning nonlinear dynamical systems using highly corrupted measured data. This approach selects and identifies the system directly from noisy data using the integral model, encompassing unknown sparse coefficients, initial values, and outlier noisy data within the...

This paper presents a new parameter estimation approach for fractional chaotic systems based on stepwise integration and response sensitivity analysis. This paper mainly consists of three parts. First, a numerical discretization scheme is introduced to obtain the numerical solution of the Grünwald-Letnikov fractional-order equations. Then, we propo...

A novel parameter estimation method based on the Laplace transform and the response sensitivity method has been presented to recognize the parameters of linear fractional-order systems (FOS) rapidly. The proposed method consumes two orders of magnitude computational resources lower than the traditional time-domain method. Fractional-order operators...

The present paper develops an enhanced response sensitivity approach for parameter identification of nonlinear time-delay systems from the time-domain data. Accurate and rapid identification of the time-delay system's parameters is the key to achieve effective control and synchronization, especially for the delay parameters. The work of this paper...