Model Predictive Control With Mixed Performances for Uncertain Positive Systems | Zendy

Junfeng Zhang | Zendy; Haoyue Yang | Zendy; Xianglei Jia | Zendy

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Model Predictive Control With Mixed Performances for Uncertain Positive Systems

Author(s) -

Junfeng Zhang,

Haoyue Yang,

Xianglei Jia

Publication year - 2018

Publication title -

ieee access

Language(s) - English

Resource type - Journals

SCImago Journal Rank - 0.587

H-Index - 127

ISSN - 2169-3536

DOI - 10.1109/access.2018.2799159

Subject(s) - aerospace , bioengineering , communication, networking and broadcast technologies , components, circuits, devices and systems , computing and processing , engineered materials, dielectrics and plasmas , engineering profession , fields, waves and electromagnetics , general topics for engineers , geoscience , nuclear engineering , photonics and electrooptics , power, energy and industry applications , robotics and control systems , signal processing and analysis , transportation

This paper addresses the model predictive control for positive systems with uncertainty and exogenous disturbance input. By utilizing a linear Lyapunov function, a sequence of model predictive controllers for positive systems is designed based on multi-step control sets guaranteeing robust stability with mixed performances. A sequence of cone sets is chosen as the invariant sets of the model predictive control. With the above idea, a model predictive control algorithm is established to compute the optimal value of the mixed performances. All conditions are in terms of linear programming to cope with largescale computation with low computation burden. Finally, a numerical example is provided to verify the effectiveness of the proposed design.

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