Machine Learning-Based Model Predictive Control of Two-Time-Scale Systems
Aisha Alnajdi,
Fahim Abdullah,
Atharva Suryavanshi
et al.
Abstract:In this study, we present a general form of nonlinear two-time-scale systems, where singular perturbation analysis is used to separate the dynamics of the slow and fast subsystems. Machine learning techniques are utilized to approximate the dynamics of both subsystems. Specifically, a recurrent neural network (RNN) and a feedforward neural network (FNN) are used to predict the slow and fast state vectors, respectively. Moreover, we investigate the generalization error bounds for these machine learning models a… Show more
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