Unmanned surface vehicle course motion control method

Abstract

The present invention provides an unmanned surface vehicle course motion control method. The method comprises the steps of receiving an unmanned surface vehicle real-time course angle acquired by a sensor module, wherein the sensor module comprises a gyroscope, an accelerometer and a magnetic field intensity sensor; comparing the real-time course angle and a set course angle to obtain an unmanned surface vehicle course deviation and a course deviation ratio; adopting a fuzzy PID control algorithm to determine an instruction rudder angle according to the course deviation and the course deviation ratio, wherein the instruction rudder angle comprises a steering direction and a steering speed; sending the instruction rudder angle to a motor driver; using the motor driver to control the unmanned surface vehicle motion according to the steering direction and the steering speed. The unmanned surface vehicle course motion control method of the present invention realizes the unmanned surface vehicle course control, and enables the steady-state performance, the dynamic performance and the control precision of the unmanned surface vehicle course motion to be improved and the course control adjustment time to be reduced.

Description

technical field [0001] Embodiments of the present invention relate to the technical field of motion control of unmanned boats, and in particular to a method for controlling heading motion of an unmanned boat. Background technique [0002] PID controller is a conventional design, because in the design, the parameters of the controlled system are considered as constants, they can only be effective within a certain range, their biggest disadvantage is that the closed-loop control system is not robust, the actual ship system Often has uncertainty, nonlinearity, instability and complexity, it is difficult to establish accurate model equations, and even cannot be analyzed and expressed directly, so the expected control effect cannot be obtained. Human operators can effectively control the navigation of the ship through their experience in handling the situation and intelligent understanding and interpretation of the situation they encounter. Therefore, it is natural for people to...

AI Technical Summary

Problems solved by technology

Among them, the fuzzy control algorithm can perform simple and effective control in the face of complex and unclear systems, but the simple fuzzy controller does not have an integral link, that is, when the input e and e of the fuzzy controller c When it is at zero or near zero, its output is also zero, so it is difficult to completely eliminate the steady-state error in the fuzzy control system, and in the case of insufficient variable classification, there will often be small oscillations near the equilibrium point

Images