Improved model-free adaptive course control algorithm based on input-output data fusion for naval vessel

Abstract

The invention belongs to the field of naval vessel motion control, and specifically relates to an improved model-free adaptive course control algorithm based on input-output data fusion for a naval vessel. The control algorithm comprises the following steps: expressing the output form of an original course system as y(k)=f(delta, psi), and outputting y(k) as k<1>xdelta+psi by a system, wherein delta is a rudder angle, and k<1> is a gain coefficient being relevant to the kinetic characteristics of a naval vessel system; and subtracting actual output y(k) from the expected output y<*>(k)(kxdelta<*>+psi<*>) of a course system to obtain an error e(k), considering that the actual course convergence of the naval vessel reaches a desired course and jumping out of the cycle when |e(k)| is less than an expected constant e0, otherwise solving the expected input u(k) of the course system by using e(k) as the input of the model-free adaptive controller. The improved model-free adaptive course control algorithm based on input-output data fusion for the naval vessel can be applied to the course control of the naval vessel.

Description

technical field [0001] The invention belongs to the field of ship motion control, in particular to an improved model-free self-adaptive course control algorithm for ship input and output data fusion. Background technique [0002] The course control of the ship is very important to the ship system. Only when the course stability of the ship is guaranteed can the desired track be effectively tracked. At present, in practical engineering applications, the course control of ships basically adopts PID control algorithm and conventional control algorithm based on "model-oriented" design strategy development. The PID controller is a data-driven control algorithm based on offline data. However, when the ship is operating in the ocean environment, it is easily affected by model perturbation and ocean environment interference, which makes it difficult for the PID controller to maintain a consistent control effect. Only by adjusting the parameters can the system maintain good control ...

AI Technical Summary

Problems solved by technology

[0004] To sum up, none of the above MFAC algorithms is suitable for ship heading control, because the ship heading system does not meet the requirements of the MFAC algorithm for the "quasilinear" assumption of the controlled system, that is, when the input of the controlled system increases, the corresponding The output of the controlled system is undiminished

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