An assessment of fuzzy logic vessel path control

A fuzzy logic controller for ship path control in restricted waters is developed and evaluated. The controller uses inputs of heading, yaw rate, and lateral offset from the nominal track to produce a commanded rudder angle. Input variable fuzzification, fuzzy associative memory rules, and output set defuzzification are described. Two maneuvering situations are evaluated: track keeping along a specified path where linearized regulator control is valid; and larger maneuvers onto a specified path where nonlinear modeling and control are required. For the track keeping assessment, the controller is benchmarked against a conventional linear quadratic Gaussian (LQG) optimal controller and Kalman filter control system. The Kalman filter is used to produce the input state variable estimates for the fuzzy controller as well. An initial startup transient and regulator control performance with an external hydrodynamic disturbance are evaluated using linear model simulations of a crude oil tanker. A fully nonlinear maneuvering model for a smaller product tanker is used to assess the larger maneuvers