Application of an Improved STSMC Method to the Bidirectional DC–DC Converter in Photovoltaic DC Microgrid

Abstract

In a photovoltaic DC microgrid, the intermittent power supply of the distributed generation and the fluctuation of the load power will cause the instability of the bus voltage. An improved super-twisting sliding mode control method based on the super-twisting algorithm is proposed to solve this problem. In this paper, a bidirectional half-bridge buck–boost converter was selected as the research topic. The proposed control method replaces the sign function with the saturation function to further mitigate the chattering effect. The stability of the proposed control method was proven to be finite-time convergent using the Lyapunov theory control. Compared with PI control, linear sliding mode control, and terminal sliding mode control, the proposed control method reduces the system overshoot by up to 33% and greatly improves the response speed; compared with the traditional super-twisting sliding mode control method, the system overshoot is reduced by 6.8%, and the response speed is increased by 38%. The experimental results show that the proposed control method can reduce the fluctuation range of the bus voltage, shorten the time of bus voltage stability, effectively stabilize the bus voltage of the photovoltaic DC microgrid, and maintain strong robustness.

Direct Model Reference Adaptive Control of a Boost Converter for Voltage Regulation in Microgrids

“…Therefore, it is evident from the simulation results that the proposed algorithm has better performance in dealing with the maximum overshoot issues. Moreover, comparing the proposed method with nonlinear methods, such as the improved sliding mode controller presented in [23], shows that the output's overshoot of DMRAC is still negligible.…”

SMC Algorithms in T-Type Bidirectional Power Grid Converter

“…In the case of sliding mode control, it should be mentioned that many different methods of developing classical SMC algorithms have been proposed in the literature on the subject. These include, among others, Fractional-Order SMC with Synergetic Controllers, which allows us to increase the efficiency of the control system and reduce the settling time [24], the SMC algorithm with adaptation based on the Neural Network, which allows for estimating and reacting to uncertain system parameters and external disturbances [25], a method using TSMC (Terminal Sliding Mode Control) that allows for convergence with finite-time [26], Fuzzy SMC increasing the robustness of the system [27], SMC-ANFIS (Artificial Neuro Fuzzy System) algorithm offering a combination of Fuzzy SMC control features with Neural Networks [28] and Super Twisting SMC improving the quality of control and reducing the impact of chattering phenomena [29]. However, in this work, it was decided to use easily applicable methods, which would be based on analytical methods.…”

Robust Adaptive Control Strategy for a Bidirectional DC-DC Converter Based on Extremum Seeking and Sliding Mode Control

“…Among these methods, the SMC is known as an advanced technique that has attracted a lot of interest due to its significant benefits in terms of robustness against perturbations and parameter variations, ease of implementation, and reference for many industrial applications. Several works using this technique for voltage regulation were reported [ 16 , 17 , 18 , 19 , 20 , 21 ]. Qi et al [ 16 ] presented a new structure of a DC-DC boost converter combined with a conventional sliding mode controller to improve the DC voltage gain and reduce voltage stress on the power switch.…”

“…This strategy precisely determined the frequency and amplitude of the self-sustaining ripple, as well as the equivalent gain of the relay function, which could improve the system stability and performance under different experimental tests. Meanwhile, an improved super-twisting SMC method [ 18 ] was proposed to mitigate the chattering effect and improve the response speed of the bus voltage for a bidirectional DC-DC converter. The obtained simulation results show that the proposed strategy can reduce system overshoot by 6.8% and increase response speed by 38% in comparison to the traditional super-twisting SMC method.…”