Nonlinear Optimal Control of the UAV and Suspended Payload System

Abstract

A nonlinear optimal control approach is developed for the UAV and suspended load system. The dynamic model of the UAV and payload system undergoes approximate linearization. This makes use of Taylor series expansion around a temporary operating point which recomputed at each iteration of the control method. The linearization procedure relies on the computation of the Jacobian matrices of the state-space model of the system. Next, an H-infinity feedback controller is designed for the approximately linearized model. The proposed control method stands for the solution of the optimal control problem for the nonlinear and multivariable dynamics of the UAV and payload system, under model uncertainties and external perturbations. To compute the controller's feedback gains an algebraic Riccati equation is solved at each time-step of the control algorithm. The new nonlinear optimal control approach achieves fast and accurate tracking for all state variables of the UAV and payload system, under moderate variations of the control inputs. Finally, Lyapunov analysis is used to prove the global stability properties of the control scheme.