Disturbance perception control method

Abstract

An advanced signal processing technology is integrated into a PID framework to improve performance, such as a self-correcting PID, a fuzzy PID, a nerve cell PID, a parameter self-learning PID, an expert PID and the like. Various improved PIDs can effectively solve the online stabilization problem of a controller gain parameter and improve a nonlinear control ability, but, the improved PIDs do nothave a high anti-disturbance capability. The ''disturbance perception control (DPC) method'' of the invention can be used to effectively solve the contradiction between rapidity and overshoot, and hascharacteristics that control precision is high, robust stability is good, an anti-disturbance capability is high, and the gain parameter is completely determined by an integration step and so on. Especially when an external environment changes drastically, the gain parameter of the DPC does not need to be re-stabilized, the control strategy of a classical control theory and a modern control theory is completely overturned. The method has a wide application value in the fields of electric power, machinery, a chemical industry, a light industry and a national defense industry.

Description

technical field [0001] Nonlinear uncertain system control, control theory and control engineering. Background technique [0002] For more than half a century, classical control (cybernetics) based on frequency-domain design methods and modern control (model theory) based on time-domain design methods have developed independently, forming their own methodological systems. In the practice of control engineering, the error between the control target and the actual behavior of the controlled object is easy to obtain and can be dealt with appropriately. Therefore, the prototype of the control strategy of "eliminating error based on error", that is, the PID controller in the actual It has been widely used in the field of industrial control. For practical control engineering problems, since it is usually difficult to give a "description of internal mechanism", the control strategy given by modern control theory based on mathematical models is difficult to be effectively applied in...

AI Technical Summary

Problems solved by technology

However, the development of science and technology has put forward higher requirements on the accuracy, speed and robustness of the controller, and the shortcomings of PID control have gradually emerged: although PID control can ensure system stability, the dynamic quality of the closed-loop system is sensitive to PID gain changes

This shortcoming leads to an irreconcilable contradiction between "rapidity" and "overshoot" in the control system. Therefore, when the operating conditions of the system change, the gain of the controller needs to change accordingly, and this is also the result of various improved PID The original motivation of control methods such as adaptive PID, nonlinear PID, neuron PID, intelligent PID, fuzzy PID, expert system PID, etc.

Although various improved PID can improve the adaptive control ability of the system by stabilizing the controller gain parameters online, however, the existing PID control is still powerless for the control problems of nonlinear uncertain systems, especially the anti-disturbance ability is poor

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