期刊名称:International Journal of Advanced Robotic Systems
印刷版ISSN:1729-8806
电子版ISSN:1729-8814
出版年度:2017
卷号:14
期号:3
DOI:10.1177/1729881417712621
语种:English
出版社:SAGE Publications
摘要:In this article, a prescribed performance-based adaptive neural network control scheme is proposed for an uncertain small-scale unmanned helicopter system subject to input saturations and output constraints. The radial basis function neural networks are employed to approximate system uncertainties. A nonlinear disturbance observer is developed to tackle input saturation. Meanwhile, the prescribed performance function is adopted to deal with output constraint. The closed-loop system stability is rigorously proved using Lyapunov synthesis. Finally, simulation results for unmanned helicopter system are presented to demonstrate the effectiveness of developed tracking control scheme using disturbance observer and radial basis function neural network.