An active controller for a UAV helicopter carrying a slung load is described in this paper. The objective of the controller is to allow the UAV to safely transport a slung load and to place it precisely on a moving ground platform such as a moving truck or a ship. In order to fulfill this objective, an active slung load controller is synthesized that forms an outer loop in providing trajectory commands to an existing automatic flight control system (AFCS) of an unmanned helicopter. The synthesized controller consists of three sub-components; first a target position tracker which generates position tracking commands, second a load oscillation controller which generates load oscillation damping commands, and third an adaptive neural network which compensates for uncertainties associated with flight environment and/or modeling errors. A linear proportional-plus-derivative (PD) controller is used for the target position tracking control. A nonlinear controller based on feedback linearization of the slung load dynamics is used for the load oscillation control. A single hidden layer neural network with an adaptive gain update is used for uncertainty compensation. The proposed controller is evaluated in simulations within the Georgia Tech UAV Simulation Tool (GUST) and inflight tests using the GTMax UAV helicopter test-bed. Both simulation and flight test results are presented to demonstrate the effectiveness of the proposed controller in dampening of load oscillations while simultaneously reducing position errors relative to a virtual moving ground platform, in the presence of random ground vehicle motion, wind gusts, and modeling errors.
All Science Journal Classification (ASJC) codes
- Control and Systems Engineering
- Automotive Engineering
- Aerospace Engineering
- Control and Optimization