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Título del libro:
Título del capítulo: Minimizing the Homogeneous Lp-Gain of the Continuous Super-Twisting-Like Algorithm Subject to Noise

Autores UNAM:
JAIME ALBERTO MORENO PEREZ;
Autores externos:

Idioma:

Año de publicación:
2024
Palabras clave:

Invariance; Lyapunov methods; Differentiators; Dissipation inequality; Effect of noise; High gain; Homogeneous system; Input and outputs; Input/output mapping; Lyapunov's functions; Storage function; Super- twisting; Lyapunov functions


Resumen:

We consider homogeneous systems with inputs and outputs, i.e. homogeneous input-output mappings, and observe that the classical Lp -gain is not suitable. Hence, the recently introduced dilation-invariant homogeneous Lp -gain (Lph -gain) is regarded. We focus on the continuous super-twisting-like algorithm (CSTLA) acting as a differentiator and propose a Lyapunov function to prove stability of the free system. This is used as a candidate storage function to estimate the Lph -gain for p = 2 with the homogeneous dissipation inequality. In a high-gain setup, scaled gains are designed that minimize the effect of noise and disturbance on the second state in terms of the Lph -gain estimate. A larger family of Lyapunov functions leads to less conservatism for the stability and Lph -gain analysis. Further, given the frequency response measurements for a periodic input with constant amplitude, the response for any other amplitude is determined using homogeneity. In contrast, the maximum of the scaling-invariant homogeneous frequency response yields a lower bound on the Lph-gain. © 2024 IEEE.


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