Nonlinear Model Predictive Control for Trajectory Tracking and Collision Avoidance of Surface Vessels
05. Februar 2018, 16:15 , 17:45
This thesis presents a combined Nonlinear Model Predictive Control (NMPC) for position and
velocity tracking of surface vessels, and collision avoidance of static and dynamic objects into a
single control scheme. This scheme is suitable for critical maneuvering of autonomous vessels in
near-collision situation. It accounts for sideslip angle and counteracts environmental
disturbances. The ship domain of the vessel is assumed to be either circular or elliptical desk.
A three-degree-of-freedom (3-DOF) dynamic model is used with only two control variables:
namely, surge force and yaw moment. External environmental forces are considered as constant
or slowly varying disturbances with respect to the inertial frame, and hence nonlinear for the
body frame of the vessel. Nonlinear disturbance observer (NDO) is used to estimate these
disturbances in order to be fed into the prediction model and enhance the robustness of the
controller. A nonlinear optimization problem is formulated to minimize the deviation of the
vessel states from a time varying reference generated over a finite horizon by a virtual vessel.
Sideslip angle is considered in the cost function formulation to account for tracking error caused
by the transverse external force in the absence of sway control force. Collision avoidance is
embedded into the trajectory tracking control problem as a time-varying nonlinear constraint of
position states to account for static and dynamic obstacles. This constraint takes a simple
Euclidean distance form for curricular ship domain, and an elliptical disk separation condition
for elliptical ones.
This algorithm is exported as a static memory C code that facilitates real-time implementation due to the efficient computation. MATLAB simulations are used to assess the validity of the proposed technique after compiling it into mex files.
Betreuer: Prof. Dr.-Ing. Axel Hahn , Prof. Dr. Martin Fränzle