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Self‐triggered model predictive control for networked control systems based on first‐order hold
Author(s) -
He Ning,
Shi Dawei,
Chen Tongwen
Publication year - 2017
Publication title -
international journal of robust and nonlinear control
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.361
H-Index - 106
eISSN - 1099-1239
pISSN - 1049-8923
DOI - 10.1002/rnc.3953
Subject(s) - model predictive control , control theory (sociology) , computer science , interpolation (computer graphics) , zero (linguistics) , control (management) , control system , signal (programming language) , order (exchange) , engineering , artificial intelligence , finance , electrical engineering , motion (physics) , linguistics , philosophy , economics , programming language
Summary In this work, a new self‐triggered model predictive control (STMPC) algorithm is proposed for continuous‐time networked control systems. Compared with existing STMPC algorithms, the proposed STMPC is implemented based on linear interpolation (first‐order hold) rather than the standard zero‐order hold, which helps further reduce the difference between the self‐triggered control signal and the original time‐triggered counterpart and thus reduce the rate of triggering. Based on the first‐order hold implementation, a self‐triggering condition is derived and the corresponding theoretical properties of the closed‐loop system are analyzed. Finally, the comparison between the proposed algorithm and the zero‐order hold–based STMPC is carried out through both theoretical analysis and a simulation example to illustrate the effectiveness of the proposed method.