Implementation of model predictive control for tracking in embedded systems using a sparse extended ADMM algorithm
Pablo Krupa,
Ignacio Alvarado,
Daniel Limon
et al.
Abstract:This article presents an implementation of a sparse, low-memory footprint optimization algorithm for the implementation of the model predictive control for tracking formulation in embedded systems. The algorithm is based on an extension of the alternating direction method of multipliers to problems with three separable functions in the objective function. One of the main advantages of the proposed algorithm is that its memory requirements grow linearly with the prediction horizon of the controller. Its sparse … Show more
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