Journal of System Simulation
Abstract
Abstract: Depending on the online implementation demand of Model Predictive Control (MPC) for the receding horizon control characteristic, a control strategy of dual feedback structure based on state extension was proposed. The control strategy was aimed to improve the online computational capability about the control system to achieve the control target without any change of the system information. Based on the analysis of the characteristic of MPC, the extension and conversion method of state variable was proposed according to the relationship between state variable, control variable, output variable and system model. And the structure of the control system after state extension was manifested as a dual feedback style. Thus, the control horizon of MPC system was decreased because of the introduction of the output feedback without any constraint and treatment to the system information. The decrease of the control horizon will conducive to improve the online computational capability of the control system remarkably. The feasibility and validity of the proposed method was verified by an example of maximum power point tracking (MPPT) control of photovoltaic system.
Recommended Citation
Xilin, Zho and Yin, Lijuan
(2020)
"Research on Model Predictive Control with Dual Feedback Based on State Extension,"
Journal of System Simulation: Vol. 27:
Iss.
3, Article 20.
Available at:
https://dc-china-simulation.researchcommons.org/journal/vol27/iss3/20
First Page
591
Revised Date
2014-09-07
DOI Link
https://doi.org/
Last Page
597
CLC
TP273+.1
Recommended Citation
Zho Xilin, Yin Lijuan. Research on Model Predictive Control with Dual Feedback Based on State Extension[J]. Journal of System Simulation, 2015, 27(3): 591-597.
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