2012 American Control Conference (ACC) 2012
DOI: 10.1109/acc.2012.6315171
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&#x2113;<inf>asso</inf> MPC: Smart regulation of over-actuated systems

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Cited by 40 publications
(45 citation statements)
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“…Remark: Although not used, the cost function (5a) can include a l 1 -norm regularization term ||D 2 κ|| 1 to induce sparsity in the obtained curvature commands, see [57], [58].…”
Section: B Control Designmentioning
confidence: 99%
“…Remark: Although not used, the cost function (5a) can include a l 1 -norm regularization term ||D 2 κ|| 1 to induce sparsity in the obtained curvature commands, see [57], [58].…”
Section: B Control Designmentioning
confidence: 99%
“…The use of regularizing terms for inducing sparsity or other special structures on solutions of optimization problems has been previously used in other areas such as signal processing, system identification, etc, [1], [5], [16]- [19], and has also recently found interest in control, [8], [20], [21]. In this paper we also employ a similar strategy for inducing special structure or sparsity on the generated control signals.…”
Section: Regularized Model Predictive Controlmentioning
confidence: 99%
“…This formulation was first proposed in [8] and later discussed under the name ℓ asso MPC in [20]. The most common choices of regularization term are with p = 1, 2, which are the so-called ℓ 1 -norm and sum-of-norms regularization respectively.…”
Section: Regularized Model Predictive Controlmentioning
confidence: 99%
“…An 1 -regularised quadratic ( asso ) cost function [13]- [16] is used to engender sparsity in the input trajectory, thus avoiding lengthy periods of continuous low-level thrust. At each time step k, the MPC minimises the cost function…”
Section: A Control Scenariomentioning
confidence: 99%