DocumentCode
2424189
Title
Internal model control strategy for SPWM inverter based on dynamic matrix control algorithm
Author
Yang, Mingjie ; Cao, Jianan ; Yu, Min ; Sun, Jin
Author_Institution
Sch. of Electr. Eng., Xi´´an Jiaotong Univ., Xi´´an, China
fYear
2009
fDate
17-20 May 2009
Firstpage
1752
Lastpage
1756
Abstract
It´s difficult for digitalized SPWM inverter to obtain high quality sine waveform and strong robustness since its time-delay phenomenon and load parameter uncertainty using the traditional control strategies. In this paper, internal model control strategy based on dynamic matrix control algorithm is proposed as a new solution. It´s also proved that this new control strategy is suitable for the system with time-delay phenomenon, external disturbance and load parameter uncertainty; in addition, the reference signal is inconstant. Further more, because of its simplicity, this algorithm can be used for real-time controlling system where the speediness is critical. A single closed-loop SPWM inverter is designed using the proposed control algorithm to achieve accurate control. Then, robustness and performance in rejection to disturbance are depicted. Finally, simulation and experimental results illustrate that the control algorithm can overcome external disturbance and load parameter uncertainty, and SPWM inverter can achieve good robustness, steady-state accuracy, and fast dynamic performance.
Keywords
PWM invertors; power system control; SPWM inverter; dynamic matrix control algorithm; fast dynamic performance; high quality sine waveform; internal model control strategy; load parameter uncertainty; steady-state accuracy; time-delay phenomenon; traditional control strategies; Control systems; Force control; Heuristic algorithms; Inverters; Open loop systems; Predictive models; Robust control; Sampling methods; Sliding mode control; Uncertain systems;
fLanguage
English
Publisher
ieee
Conference_Titel
Power Electronics and Motion Control Conference, 2009. IPEMC '09. IEEE 6th International
Conference_Location
Wuhan
Print_ISBN
978-1-4244-3556-2
Electronic_ISBN
978-1-4244-3557-9
Type
conf
DOI
10.1109/IPEMC.2009.5157676
Filename
5157676
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