Robust adaptive tracking control for unmanned helicopter with constraints. (5th June 2017)

• Record Type: Journal Article
• Authors: Li, Rong; Chen, Mou; Wu, Qingxian; Liu, Jianye
• Is Part Of: International journal of advanced robotic systems. Volume 14:Number 3(2017:May/Jun.)
• Publication Date: 2017-06-05
• Subjects: Unmanned helicopter -- input saturation -- output constraint -- neural network -- prescribed performance function; Robotics -- Periodicals; Robotics; Periodicals; 629.892
• DOI: 10.1177/1729881417712621
• Languages: English
• ISSNs: 1729-8806

Abstract

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.