Genetic algorithms + data structures = evolution programs (3rd ed.)
Genetic algorithms + data structures = evolution programs (3rd ed.)
Genetic Algorithms in Search, Optimization and Machine Learning
Genetic Algorithms in Search, Optimization and Machine Learning
Nonlinear and Adaptive Control Design
Nonlinear and Adaptive Control Design
Stabilization of Nonlinear Uncertain Systems
Stabilization of Nonlinear Uncertain Systems
Robust backstepping control of nonlinear systems using neural networks
IEEE Transactions on Systems, Man, and Cybernetics, Part A: Systems and Humans
Brief Global tracking control of underactuated ships by Lyapunov's direct method
Automatica (Journal of IFAC)
Adaptive neural network control for strict-feedback nonlinear systems using backstepping design
Automatica (Journal of IFAC)
Survey Constructive nonlinear control: a historical perspective
Automatica (Journal of IFAC)
Robust adaptive path following of underactuated ships
Automatica (Journal of IFAC)
Adaptive maneuvering, with experiments, for a model ship in a marine control laboratory
Automatica (Journal of IFAC)
A neural approach for control of nonlinear systems with feedback linearization
IEEE Transactions on Neural Networks
Stable neural controller design for unknown nonlinear systems using backstepping
IEEE Transactions on Neural Networks
Fault Monitoring and Fault Recovery Control for Position-Moored Vessels
International Journal of Applied Mathematics and Computer Science - Issues in Advanced Control and Diagnosis
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As an object of course control, the ship is characterised by a nonlinear function describing static manoeuvring characteristics that reflect the steady-state relation between the rudder deflection and the rate of turn of the hull. One of the methods which can be used for designing a nonlinear ship course controller is the backstepping method. It is used here for designing two configurations of nonlinear controllers, which are then applied to ship course control. The parameters of the obtained nonlinear control structures are tuned to optimise the operation of the control system. The optimisation is performed using genetic algorithms. The quality of operation of the designed control algorithms is checked in simulation tests performed on the mathematical model of a tanker. In order to obtain reference results to be used for comparison with those recorded for nonlinear controllers designed using the backstepping method, a control system with the PD controller is examined as well.