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Model parameter on-line identification with nonlinear parametrization – manipulator model

Cedro Leszek

Technical Transactions

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2022

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Vol. 119, iss. 1

art. no. e2022007

EN

This paper presents an example of solving the parameter identification problem in the case of a robot with two degrees of freedom. In this study, a weighted recursive least squares algorithm was generalised to a case of nonlinear parameterisation in which the identified parameters did not satisfy the linear model. The generalisation involved linearising the model in the neighbourhood of current values of the parameter estimates. It was assumed that the estimates were updated every N steps of signal sampling. This method of identification can be applied whenever the parameters concerning a model need to be determined at the time of measurement. This is particularly useful in adaptive control when the plant parameters vary over time.

2

A Comparative study of user Identification for COVID-19 vaccination online registration

Kato Sota, Sirapaisan Soontorn, Vorakulpipat Chalee

Annals of Computer Science and Information Systems

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2022

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Vol. 31

89-93

EN

Due to the COVID-19 pandemic, individuals have been encouraged to obtain COVID-19 vaccinations. As part of the vaccination process, it is necessary to verify the identity before obtaining the vaccines. Incorrectly identifying the individuals could lead to serious consequences. For example, an incorrect vaccination schedule ( e.g., incorrect timing between doses and incompatible brands) may cause undesired side effects to an individual, so it should be more accurate and convenient to identify themselves whenever and wherever people are required. One of the most effective and commonly used identification methods is face-to-face (or offline) identification. However, the method is typically time-consuming and is not suitable for the current situation where individuals should avoid direct contact. Hence, there is a growing trend for an online identification method where individuals use digital credentials to identify themselves. This paper suggests an online authentication system for improvements by investigating how different people authenticate themselves online in each country for COVID-19 vaccination. Comparing the online authentication systems between a country that have their national identification cards or not makes the Pros and Cons of both systems clear, particularly, in Japan and Thailand.

3

Online parameter identification of SPMSM based on improved artificial bee colony algorithm

Wu Chunli, Jiang Shuai, Bian Chunyuan

Archives of Electrical Engineering

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2021

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Vol. 70, nr 4

777--790

EN

The artificial bee colony (ABC) intelligence algorithm is widely applied to solve multi-variable function optimization problems. In order to accurately identify the parameters of the surface-mounted permanent magnet synchronous motor (SPMSM), this paper proposes an improved ABC optimization method based on vector control to solve the multi-parameter identification problem of the PMSM. Because of the shortcomings of the existing parameter identification algorithms, such as high computational complexity and data saturation, the ABC algorithm is applied for the multi-parameter identification of the PMSM for the first time. In order to further improve the search speed of the ABC algorithm and avoid falling into the local optimum, Euclidean distance is introduced into the ABC algorithm to search more efficiently in the feasible region. Applying the improved algorithm to multi-parameter identification of the PMSM, this method only needs to sample the stator current and voltage signals of the motor. Combined with the fitness function, the online identification of the PMSM can be achieved. The simulation and experimental results show that the ABC algorithm can quickly identify the motor stator resistance, inductance and flux linkage. In addition, the ABC algorithm improved by Euclidean distance has faster convergence speed and smaller steady-state error for the identification results of stator resistance, inductance and flux linkage.

4

Self-tuning control with regularized RLS algorithm for vibration cancellation of a circular plate

Leniowska L., Kos P.

Archives of Acoustics

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2009

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Vol. 34, No. 4

613-624

EN

The self-tuning control assumes that the vibrating system is unknown and the controller procedure has the ability to identify the process and to update the necessary control law. Such an algorithm provides the relevant regulator parameters according to the obtained parametric object model. The algorithm can be described as a combination of the following two procedures: the online identification and the computation of the controller parameters. Nearly all of the identification procedures are related to the Least Squares (LS) estimate of a model output. Classified as an ill-posed problem, it implies that the obtained solution is potentially very sensitive to the data perturbations. In order to avoid such problems, the regularized version of the RLS method has been considered in this paper. By solving the linear system of equations with a non-singular Sylvester matrix, the formulas for the unknown coefficients of the considered PID-type controller structure have been obtained. The results of the tests and simulations for the circular plate vibration cancellation have been also included.