@article{oai:kanazawa-u.repo.nii.ac.jp:00009557,
 author = {山本, 茂 and Li, Hongran and Yamamoto, Shigeru},
 journal = {Proceedings of 2016 SICE International Symposium on Control Systems, ISCS 2016},
 month = {May},
 note = {This paper proposes a model-free predictive control method for nonlinear systems on the basis of polynomial regression. In contrast to conventional model predictive control, model-free predictive control does not require mathematical models. Instead, it uses the previous recorded input/output datasets of the controlled system to predict an optimal control input so as to achieve the desired output. The novel point in this paper is the improvement of existing model-free predictive control by adopting polynomial regression, which is a generalization of the so-called Volterra series expansion of nonlinear functions. © 2016 The Society of Instrument and Control Engineers-SICE., 2nd SICE International Symposium on Control Systems, ISCS 2016; Nagoya Campus, Nanzan UniversityNagoya; Japan; 7 March 2016 through 10 March 2016; Category numberCFP16TPH-ART; Code 121644, 金沢大学融合研究域融合科学系},
 title = {A Model-Free Predictive Control Method Based on Polynomial Regression},
 year = {2016}
}