Improving computational efficiency of model predictive control algorithm using wavelet transformation

Autor:	Yugender Chikkula, Zhenghong Yu, Jay H. Lee, Jeffrey C. Kantor
Rok vydání:	1995
Předmět:	Constraint (information theory) Model predictive control Transformation (function) Wavelet Control and Systems Engineering Condensation Stability (learning theory) Blocking (statistics) Algorithm Computer Science Applications Mathematics
Zdroj:	International Journal of Control. 61:859-883
ISSN:	1366-5820 0020-7179
DOI:	10.1080/00207179508921935
Popis:	We propose an MPC algorithm with desirable stability and constraint-handling properties, yet which retains computational simplicity. The closed-loop stability and constraint-handling are achieved by formulating an infinite-horizon objective and then solving an equivalent finite-horizon problem. On-line computational requirements for multi-time-scale systems, are reduced substantially by techniques called ‘blocking’ and ‘condensation’. We show that the blocking and condensation techniques are conveniently applied after expressing the MPC objective and constraint equations in terms of wavelet bases.
Databáze:	OpenAIRE
Externí odkaz:	https://explore.openaire.eu/search/publication?articleId=doi_________::34a827e637e1dcc802e5c84743aa8f6a https://doi.org/10.1080/00207179508921935 Zobrazit plný text záznamu