Vision-Based Prescribed Performance Control for UAV Target Tracking Subject to Actuator Saturation
Peng Sun, Bing Zhu, Siqi Li
Abstract
In this article, a vision-based prescribed performance control is proposed for an unmanned aerial vehicle (UAV) subject to actuator saturation to track an uncooperative target. It is supposed that states cannot be measured directly, and are estimated by a on-board camera. The proposed controller is designed within a backstepping framework, where an error transforming function and Barrier Lyapunov Function are applied, and a robust adaptive controller is designed to deal with initial conditions violating the prescribed performance. It is proven that, with the proposed controller, the tracking error converges into the prescribed performance boundary before the finite preset time.
Topics & Concepts
Control theory (sociology)BacksteppingTracking errorActuatorLyapunov functionController (irrigation)Computer scienceTracking (education)Control engineeringEngineeringAdaptive controlArtificial intelligenceControl (management)Nonlinear systemQuantum mechanicsPsychologyAgronomyPhysicsPedagogyBiologyAdaptive Control of Nonlinear SystemsDistributed Control Multi-Agent SystemsGuidance and Control Systems