An Accelerated Parameter Identification Algorithm for Linear Regression Systems

https://doi.org/10.58571/CNCA.AMCA.2024.075

Resumen: In this paper, a parameter identification algorithm is proposed for linear regression systems with constant unknown parameters. Such an algorithm is composed of an accelerated version of the heavy–ball method and a modified extension of Kreisselmeier’s filters and can identify constant parameters in a finite time under a persistent excitation condition. The workability of the proposed algorithm is depicted by simulation results.

¿Cómo citar?

Ríos, H., Efimov, D. & Ushirobira, R. (2024). An Accelerated Parameter Identification Algorithm for Linear Regression Systems. Memorias del Congreso Nacional de Control Automático 2024, pp. 439-444. https://doi.org/10.58571/CNCA.AMCA.2024.075

Palabras clave

Parameter Identification, Heavy–Ball Method, Finite–Time

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