@article{oai:kanazawa-u.repo.nii.ac.jp:00009453,
 author = {山本, 茂 and Yamamoto, Shigeru},
 journal = {Proc. of the 10th Asian Control Conference 2015 (ASCC 2015)},
 month = {Sep},
 note = {We propose a new predictive control method utilizing a sparse solution of a minimization problem defined by both online and stored input/output data of the controlled system. The conventional predictive control methods generally require a mathematical model of the controlled system to predict an optimal future input to control the system. The mathematical model is usually obtained by applying a standard system identification method to the measured input/output data. The proposed method in this paper requires no mathematical model to predict future control input to achieve the desired output. This model-free control method, also called just-in-time predictive control, was originally proposed by Inoue and Yamamoto in 2004 and simplified by Yamamoto in 2014. In this paper, to develop another simplified method, we formulate an ℓ1-minimization problem. © 2015 IEEE., 10th Asian Control Conference, ASCC 2015; Sutera Harbour ResortKota Kinabalu; Malaysia; 31 May 2015 through 3 June 2015; Category numberCFP15832-ART; Code 117644, Article number 7244446, 金沢大学融合研究域融合科学系},
 title = {A model-free predictive control method by ℓ1-minimization},
 year = {2015}
}