Sliding mode estimation-based control for stochastic time delays in networked microgrid
Author(s)
Zhou, Xuping
Yan, Huaicheng
Peng, Chen
Yang, Fuwen
Griffith University Author(s)
Year published
2017
Metadata
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This paper proposes a sliding mode estimation-based control to solve the stochastic time delay problem in networked microgrid, because stochastic delay has a great impact on the stability and performance of large power grids (LPG). To analyze the delay effects, the microgrid system model is derived according to the characteristics of the inverter in grid-connected microgrid. Based on the microgrid system model, the stochastic delay estimation with learning parameter and delayed states are derived. The control signal designed by sliding mode control (SMC) and the learning parameter of delay estimation are adaptively changed ...
View more >This paper proposes a sliding mode estimation-based control to solve the stochastic time delay problem in networked microgrid, because stochastic delay has a great impact on the stability and performance of large power grids (LPG). To analyze the delay effects, the microgrid system model is derived according to the characteristics of the inverter in grid-connected microgrid. Based on the microgrid system model, the stochastic delay estimation with learning parameter and delayed states are derived. The control signal designed by sliding mode control (SMC) and the learning parameter of delay estimation are adaptively changed in the sliding mode estimation-based control loop. Exponential reaching law (ERL) is proposed to solve the chattering issues of SMC. The 3.3 KW microgrid parameters are added into simulation to verify the effectiveness and performance of the proposed control strategy.
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View more >This paper proposes a sliding mode estimation-based control to solve the stochastic time delay problem in networked microgrid, because stochastic delay has a great impact on the stability and performance of large power grids (LPG). To analyze the delay effects, the microgrid system model is derived according to the characteristics of the inverter in grid-connected microgrid. Based on the microgrid system model, the stochastic delay estimation with learning parameter and delayed states are derived. The control signal designed by sliding mode control (SMC) and the learning parameter of delay estimation are adaptively changed in the sliding mode estimation-based control loop. Exponential reaching law (ERL) is proposed to solve the chattering issues of SMC. The 3.3 KW microgrid parameters are added into simulation to verify the effectiveness and performance of the proposed control strategy.
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Conference Title
PROCEEDINGS OF THE 36TH CHINESE CONTROL CONFERENCE (CCC 2017)
Subject
Automation engineering
Control engineering