Control parameter optimization method and system through vector time series prediction and expert fuzzy transformation ratio

Abstract

The invention discloses a control parameter optimization method and system through vector time series prediction and the expert fuzzy transformation ratio. The control parameter optimization method and system through vector time series prediction and the expert fuzzy transformation ratio can be applied to the fields such as the field of control, the field of decision making and the field of artificial intelligence. According to the scheme, input which serves as control parameter on-line optimization setting is predicted and is output through a vector time series prediction method according to the states of a control system and output time series, a transformation ratio value of the control parameter on-line optimization setting is predicted through an expert rule table or a fuzzy controller to carry out on-line optimization setting on control parameters, and the control parameter optimization method through vector time series prediction and the expert fuzzy transformation ratio is formed by combining the two points and a classic control method, further, a specific device and a specific connection relation are designed, and the control parameter optimization system through vector time series prediction and the expert fuzzy transformation ratio is formed. According to the control parameter optimization method and system through vector time series prediction and the expert fuzzy transformation ratio, on-line optimization setting can be carried out on the control parameters according to difference between the working environments and uncertainty of the working environments, a control system can deal with various sudden environmental changes, dynamic performance, anti-interference performance and static performance are improved, and the defect of overshoot is overcome.

Description

technical field [0001] The invention proposes a vector time series forecasting expert fuzzy variable ratio control parameter optimization method and system, which can be applied to the fields of control, decision-making, artificial intelligence and the like. Background technique [0002] How to enable the control system to simulate human thinking, automatically adjust (optimize) control parameters online according to the application environment, and obtain better control performance is the long-term goal of scientists in the field of automatic control, and it is also the problem solved by the present invention. Experts and scholars in this field combine artificial intelligence methods with classical control methods to obtain various advanced intelligent control methods, which can be divided into two categories: the first category is the intelligent control method based on rule reasoning mechanism (unified abbreviation R-PID control method), such as expert PID (Expert PID, E-...

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Problems solved by technology

That is, goal 1 is to solve the problem that the controller parameters cannot be optimized and adjusted online according to the differences and uncertainties of the working environment and the controlled object. Before each application of the control system, the engineer has to repeatedly debug the control parameters, and the system runs for a period of time Finally, engineers have to repeatedly check the problem of debugging control parameters; goal 2 is to solve the problem that the control system lacks a response mechanism for various sudden changes in the environment, and can only make control decisions based on the current situation, even if the control decisions are important for the future of the system. The output is harmful, and you can only respond after the harmful effect occurs; goal 3 is to solve the problem that the dynamic performance and anti-disturbance performance of the control system need to be improved; goal 4 is to solve the problem that the static performance of the control system needs to be improved Problem; Objective 5 is to solve the problem that overshoot will occur in some applications, but some engineering applications do not allow overshoot

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