PID control method, apparatus and system based on network optimization algorithm

Abstract

The invention belonging to the field of artificial intelligence particularly relates to a PID control method, apparatus and system based on a network optimization algorithm. The method comprises: a target quantity and an actual output of a controlled object are obtained, wherein an error is obtained by subtracting the target quantity by the actual output; on the basis of a neural network optimization algorithm, calculation is carried out to obtain membership degrees of input variables, wherein the input variables of the neural network optimization algorithm are the error and an error changing rate; according to the membership degrees of the error and the error changing rate, calculation is carried out by using a fuzzy control algorithm by using the error and an error changing rate as the input variables so as to obtain a PID control parameter; on the basis of the error and the PID control parameter, calculation is carried out to obtain a control parameter of the controlled object; and then the control parameter is inputted into the controlled object. The method, apparatus and system are suitable for a non-linear controlled object; and the robustness to the uncertain interference during the control process is high.

Description

technical field [0001] The invention belongs to the field of artificial intelligence, and in particular relates to a PID control method, device and system based on a network optimization algorithm. Background technique [0002] With the continuous development of artificial intelligence technology, the automation level of unmanned surface vehicle (USV) is also continuously improved. Relying on its intelligent and unmanned characteristics, USV can complete various marine scientific research tasks quickly, efficiently and at low cost, and has become the focus of the development of intelligent ships. Therefore, research on USV can promote the upgrading and development of ship automation, intelligent equipment and system supporting industries. [0003] Heading control is the core of fully autonomous navigation and intelligent control of surface unmanned boats. Since the motion process of unmanned boats is essentially nonlinear, the disturbances encountered are uncertain, while t...

AI Technical Summary

Problems solved by technology

[0003] Heading control is the core of fully autonomous navigation and intelligent control of surface unmanned boats. Since the motion process of unmanned boats is essentially nonlinear, the disturbances encountered are uncertain, while the control objects of conventional PID controllers are mostly linear and Precise mathematical model is difficult to meet the requirements of heading control of unmanned boats

The intelligent algorithms proposed at this stage have their own shortcomings, such as the adaptive inverse control method, which seldom considers the uncertain factors that are common in the actual system; Backstepping control requires an accurate nonlinear motion model of the ship, etc., which is difficult to achieve in engineering

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