Adaptive Fuzzy Dynamic Surface Control for Multi-Machine Power System Based on Composite Learning Method and Disturbance Observer

Guoqiang Zhu,Xiuyu Zhang,Miaolei Zhou,Lingfang Sun,Linlin Nie,Cheng Zhong

doi:10.1109/access.2020.3022293

Guoqiang Zhu, Xiuyu Zhang + Show 4 more

Open Access

https://doi.org/10.1109/access.2020.3022293

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Abstract

A composite learning dynamic surface control is proposed for a class of multi-machine power systems with uncertainties and external disturbances by using fuzzy logic systems (FLSs) and disturbance observer (DOB). The main characteristics of the proposed strategy are as follows: (1) The approximation ability of FLSs for nonlinear model of multi-machine power systems is enhanced considerably by using the composite learning method and providing additional correction information for the FLSs. These findings differ considerably from previous designs that focus directly on the system's tracking performance. (2) The filtering errors caused by the utilizations of the first-order low-pass filters in dynamic surface control (DSC) are compensated effectively by designing the compensating signals in the control law design process. (3) The compound disturbances including the FLSs' approximation error and external disturbances are estimated and mitigated by constructing DOB. Finally, the proposed control algorithm is verified on the StarSim Hardware-in-loop experimental platform, and the experimental results validate the effectiveness of the proposed control strategy in suppressing disturbances and enhancing the robustness of the controller.

Highlights

With the expansion of the power grid’s scale, modern power systems have gradually formed a strong coupling dynamic nonlinear system
In [11], stability sensitive parameters are brought into the multi-machine power system model and a robust adaptive backstepping excitation controller that can which overcome the over-parameterization problem of stability sensitive parameters was design
EXPERIMENTAL RESULTS The StarSim Hardware-in-loop testing platform is used to demonstrate the performance of the proposed control scheme

Summary

Introduction

With the expansion of the power grid’s scale, modern power systems have gradually formed a strong coupling dynamic nonlinear system. Improving the control ability of multi-machine excitation system has aroused considerable concern among researchers. Nonlinear control methods have been applied to multi-machine power systems [5]–[9]. The traditional excitation control strategy usually adopts the PID control method [10]. This strategy is no longer suitable for a highly nonlinear multi-machine power system. Backstepping control method provides a systemic framework for tracking and regulating problem of nonlinear systems, which are utilized widely in the excitation control field. In [11], stability sensitive parameters are brought into the multi-machine power system model and a robust adaptive backstepping excitation controller that can which overcome the over-parameterization problem of stability sensitive parameters was design.

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Conclusion