Adaptive dynamic surface control of Buck DC converter with input constraint

PDF(383 KB)

Journal of Dalian Maritime University ›› 2014, Vol. 40 ›› Issue (1) : 93-96.

LIU Lu¹, WANG Dan¹, PENG Zhou-hua¹，PENG Ming²

Author information +

History +

Abstract

Adaptive dynamic surface control was proposed for the uncertain DC-DC buck converter system with input constraint. The introduction of first-order filters allows the algorithm to be implemented without differentiating any model nonlinearities and suffering from the ‘explosion’ problem. By introducing an auxiliary control variable to ensure controller output within the specified range, an effective controller design method was developed. The proposed control law can guarantee the uniform ultimate boundness of all signals in the closed-loop system via Lyapunov synthesis ,and make the tracking error converge to less neighborhood nearby origin. Numerical simulations are provided to illustrate the validity of the proposed control method.

Key words

buck converter / adaptive dynamic surface / input constraint / control

Cite this article

EndNote

Ris (Procite)

Bibtex

Download Citations

LIU Lu, WANG Dan, PENG Zhou-hua, PENG Ming. Adaptive dynamic surface control of Buck DC converter with input constraint[J]. Journal of Dalian Maritime University. 2014, 40(1): 93-96

References

［1］ZHOU Wei, YE Xu-dong. Adaptive control of parallel DC-DC buck converters with uncertain parameters［C］//International Conference on Control Automation Robotics&Vision.［S.l.］:IEEE Press,2012:737-740.

［2］WANG Dan, HUANG Jie. Neural network-based adaptive dynamic surface control for a class of uncertain nonlinear systems in strict-feedback form［J］.Transactions on Neural Networks,2005,16(1): 195-202.

［3］ERICKSON R W. Fundamentals of power electronics［M］. ［S.l.］:Khwer Academic Publishers, 2000.

［4］CHEN Qiang, REN Xue-mei, OLIVER J A. Identifier-based adaptive neural dynamic surface control for uncertain DC-DC buck converter system with input constraint［J］. Commun Nonlinear Sci Numer Simulat,2012,17(4): 1871-1883.

［5］CHEN Mou, GE S S,YOO Sang-choo.Neural network tracking control of ocean surface vessels with input saturation［C］//Proceedings of the IEEE International Conference on Automation and Logistics,［S.l.］:IEEE Press,2009:85-89.