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The skin effect in modeling an induction motor can be described by fractional differential equations. The existing methods for identifying the parameters of an induction motor with a rotor skin effect suggest the presence of errors only in the output. The presence of errors in measuring currents and voltages leads to errors in both input and output signals. Applying standard methods, such as the ordinary least squares method, leads to biased estimates in these types of problems. The study proposes a new method for identifying the parameters of an induction motor in the presence of a skin effect. Estimates of parameters were determined based on generalized total least squares. The simulation results obtained showed the high accuracy of the obtained estimates. The results of this research can be applied in the development of predictive diagnostic systems. This study shows that ordinary least squares parameter estimates can lead to incorrect operation of the fault diagnosis system. [ABSTRACT FROM AUTHOR]

This paper presents an overview of the main methods used to identify autoregressive models with additive noises. The classification of identification methods is given. For each group of methods, advantages and disadvantages are indicated. The article presents the simulation results of a large number of the described methods and gives recommendations on choosing the best methods. [ABSTRACT FROM AUTHOR]

In the field of engineering, time-delay is a typical occurrence. In reality, the inner dynamics of many industrial processes are impacted by delay or after-effect events. This paper discusses the identification of continuous-time fractional order system with unknown time-delay using the bias compensated least squares algorithm. The basic concept is to remove the imposed bias by including a correction term into the least squares estimations. The suggested approach makes a significant contribution by the estimation, iteratively, of fractional order system coefficients as well as the orders and the time-delay using a nonlinear optimization algorithm. The main advantage of this method is to provide a simple and powerful algorithm with good accuracy. The suggest method performances are assessed through two numerical examples. [ABSTRACT FROM AUTHOR]

In this paper, the stochastic gradient algorithm for learning fractional-order dynamical systems with noisy input and output is proposed. The proposed algorithm allows estimating the parameters of fractional dynamic systems if the input and output noises are color. The proposed algorithm does not require knowledge of the noise distribution laws. The simulation results demonstrate the high accuracy of the proposed learning algorithm in comparison with the least squares learning algorithm. [ABSTRACT FROM AUTHOR]

Models based on equations with derivatives and differences of fractional order are increasingly used for simulation of different processes. The paper presents a method of structural parametric identification of Gegenbauer autoregressive with noise on output signal. The search of the parameter of Gegenbauer difference is carried out with the help of a genetic algorithm. The propose algorithm was realized in Matlab. The simulation results show the high efficiency of the propose algorithm. [ABSTRACT FROM AUTHOR]

This paper is devoted to the identification of the parameters of discrete fractional systems with errors in variables. Estimates of the parameters of such systems can be obtained using generalized total least squares (GTLS). A GTLS problem can be reduced to a total least squares (TLS) problem. A total least squares problem is often ill-conditioned. To solve a TLS problem, a classical algorithm based on finding the right singular vector or an algorithm based on an augmented system of equations with complex coefficients can be applied. In this paper, a new augmented system of equations with real coefficients is proposed to solve TLS problems. A symmetrical augmented system of equations was applied to the parameter identification of discrete fractional systems. The simulation results showed that the use of the proposed symmetrical augmented system of equations can shorten the time for solving such problems. It was also shown that the proposed system can have a smaller condition number. [ABSTRACT FROM AUTHOR]