Ljubomir Kuljaca

Improved Fuzzy Autopilot for Track-Keeping

Abstract Improved 2-input fuzzy autopilot for ship course control and 3-input fuzzy autopilot for track-keeping are proposed. Nonlinear model of a ship and a steering subsystem is used. The 3-input fuzzy autopilot uses heading signal, yaw rate signal and lateral offset from the nominal track to produce a command rudder angle. Input variable fuzzyfication, fuzzy associative memory rules and output set defuzzyfication are described. Obtaining of FAM rules for 3-input fuzzy is described. Dynamical behavior of 2 and 3-input fuzzy autopilot is compared. The influence of wave disturbance, sea current and external disturbance from a passing ship on track-keeping performance was analyzed.

Analytical Determination of Describing Function of Nonlinear Element with Fuzzy Logic

The paper presents the procedure for analytical determination of describing function of nonlinear element with fuzzy logic nonlinearity. The procedure is based on the method of analytical determination of describing function of generalized static characteristic of nonlinear element. The procedure is also illustrated with examples.

Engineering procedure for analysis of nonlinear structure consisting of fuzzy element and typical nonlinear element

Engineering procedure for approximate analytical determination of describing function of nonlinear systems with odd static characteristics is presented in the paper. Generalized mathematical expressions for determining such describing function with error estimation are given. The procedure is illustrated on determination of describing function, and corresponding error estimation, of nonlinear structure consisting of fuzzy element and typical nonlinear element.

Computer Aided Harmonic Linearization of SISO Systems Using Linearly Approximated Static Characteristic

Harmonic linearization, also known as describing function analysis is well known method for analysis of SISO systems. Computer aided harmonic linearization, as experimental practical method for determining static characteristics and describing functions is described. The use of linearly approximated static characteristic in determination of describing function introduces an inherent error resulting from the difference between original static characteristic and corresponding linearly approximated static characteristic. Error estimation and comparison of approximated characteristic error with the actual error is illustrated on several examples.

Predictive gain scheduling autopilot for ships

The paper presents results of research with the new predictive autopilot structure (PIP+D) with gain scheduling. The autopilot is tested and compared with conventional PID autopilot for a mariner class ship. The autopilot parameters are changed with the speed of the ship using the gain scheduling technique. Results obtained during the research show that the proposed autopilot structure is to be recommended if improved performance is of prime interest, when the velocity of the ship is changing. The analysis is based on the simulation of a mariner class ship as a nonlinear system, with the steering servo system taken as a nonlinear model. Results of the simulation are included.

Fuzzy Autopilot for Ships Experiencing Shallow Water Effect in Manoeuvering

Abstract A fuzzy autopilot for ship path control is proposed. Nonlinear model of a ship and a steering subsystem is used. The autopilot uses heading signal and yaw rate signal to produce a command rudder angle. The autopilot does not use lateral offset from the nominal track. Input variable fuzzyfication, fuzzy associative memory rules and output set defuzzyfication are described. The influence of the shallow water effect during larger maneuver is analyzed.

Describing Function and Error Estimation for Class of Nonlinear Systems with Fuzzy elements

– The procedure for approximate analytical determination of describing function of nonlinear systems with odd static characteristics is presented in the paper. Generalized mathematical expressions for determining such describing function with error estimation are given. The procedure is illustrated on determination of describing function, and corresponding error estimation, of Mamdani fuzzy element and nonlinear system with fuzzy element and saturation nonlinearity.