期刊
IEEE TRANSACTIONS ON CIRCUITS AND SYSTEMS I-REGULAR PAPERS
卷 70, 期 7, 页码 3005-3016出版社
IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
DOI: 10.1109/TCSI.2023.3264536
关键词
DC-DC boost converter; neural network; finite time; observer; voltage control
This paper investigates the problem of accurate voltage tracking control for DC-DC boost converter under unknown system parameters and load. Uncertainties caused by the perturbation of the inductor, capacitor, input voltage and load are approximated by neural networks. A finite-time observer is proposed to obtain the estimates of lumped uncertainty without any true parameters of the system. Finally, a finite-time control scheme is proposed for the DC-DC boost converter to improve the convergence of output voltage.
This paper investigates the problem of accurate voltage tracking control for direct current-direct current (DC-DC) boost converter under unknown system parameters and load. Firstly, uncertainties caused by the perturbation of the inductor, capacitor, input voltage and load are approximated by neural networks. Meanwhile, a finite-time observer is proposed to obtain the estimates of lumped uncertainty without any true parameters of the system. Finally, to improve the convergence of output voltage, a finite-time control scheme is proposed for the DC-DC boost converter. It is proven that all signals of the closed-loop system are bounded and both the estimate errors and tracking errors can converge to a small neighborhood of the origin in finite time. Numerical simulations and real-time experiments are presented to demonstrate the effectiveness and superiority of the proposed controller.
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