The ability of unmanned surface vessels for performing dexterous maneuvering is important for improving vessels' safety, reliability and operational capacity. The article proposes a nonlinear optimal control approach for unmanned surface vessels. These vessels exhibit three degrees of freedom while their dynamic model can be formulated in analogy to the one of robotic manipulators. This model undergoes approximate linearization around a temporary operating point that is recomputed at each time-step of the control method. The linearization relies on Taylor series expansion and on the associated Jacobian matrices. For the linearized state-space model of the system a stabilizing optimal (H-in¿nity) feedback controller is designed. This controller stands for the solution to the nonlinear optimal control problem under model uncertainty and external perturbations. To compute the controller's feedback gains an algebraic Riccati equation is repetitively solved at each iteration of the control algorithm. The stability properties of the control method are proven through Lyapunov analysis.
Nonlinear Optimal Control for Autonomous Surface Vessels
Cuccurullo G.;Siano P.;
2023-01-01
Abstract
The ability of unmanned surface vessels for performing dexterous maneuvering is important for improving vessels' safety, reliability and operational capacity. The article proposes a nonlinear optimal control approach for unmanned surface vessels. These vessels exhibit three degrees of freedom while their dynamic model can be formulated in analogy to the one of robotic manipulators. This model undergoes approximate linearization around a temporary operating point that is recomputed at each time-step of the control method. The linearization relies on Taylor series expansion and on the associated Jacobian matrices. For the linearized state-space model of the system a stabilizing optimal (H-in¿nity) feedback controller is designed. This controller stands for the solution to the nonlinear optimal control problem under model uncertainty and external perturbations. To compute the controller's feedback gains an algebraic Riccati equation is repetitively solved at each iteration of the control algorithm. The stability properties of the control method are proven through Lyapunov analysis.I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.