Gradient Estimate for Continuous-Time Linear Dynamical Systems

https://doi.org/10.58571/CNCA.AMCA.2024.074

Resumen: In this paper we compare two different methodologies for computing the gradient of a linear, continuous-time dynamical system with no parametric uncertainties nor unknown inputs. Such a gradient is computed by performing the partial derivative of a performance function w.r.t. the input of the system. The first of the methodologies uses the model of the dynamical system to construct the gradient; whereas the second one avails of the differentiation of the performance function and the system’s input. We compare both approaches via a numerical simulation.

¿Cómo citar?

Lopez Caamal, F. & Torres, I.(2024). Gradient Estimate for Continuous-Time Linear Dynamical Systems. Memorias del Congreso Nacional de Control Automático 2024, pp. 434-438. https://doi.org/10.58571/CNCA.AMCA.2024.074

Palabras clave

Model-based gradient, Continuous-time estimation, Linear systems

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