Fuzzy neural network PID fireflood intelligent ignition control method

Abstract

The invention discloses a fuzzy neural network PID fireflooding intelligent ignition control method which comprises the steps that a PLC control system monitors a temperature value of a thermocouple and a gas flow value signal of a gas meter in real time, temperature is set through a stratum, fuzzy RBF neural network operation is carried out, and an operation result is fed back to a PID controller; the PID controller sends a signal to the measurement and control cabinet, the measurement and control cabinet gives a current value through the power cable, the coiled tubing electric igniter heats air near an underground oil layer according to the provided power, and the temperature change of the underground thermocouple is timely reflected to the PLC control system; and the PLC control system carries out operation according to the fed-back temperature and feeds back a given adjusted current value to the continuous pipe electric igniter, so that the feedback is cycled, and the underground temperature is accurately controlled. According to the fuzzy RBF neural network PID control, the transition time for the temperature to be stable in the ignition operation control is short, the overshoot is small, and the control precision and control stability of the temperature in the ignition operation are improved.

Description

technical field [0001] The invention relates to the field of intelligent control in fire drive ignition technology, in particular to a fuzzy neural network PID fire drive intelligent ignition control method. Background technique [0002] In the fire flooding process, the ignition control technology plays a vital role, especially in the electric ignition technology, the control of the ignition process determines the success or failure of the fire flooding process and the quality of the ignition effect. In today's ignition control, manual control is basically adopted. The on-site construction personnel will dynamically adjust the power of the ignition control cabinet in real time, and adjust the temperature of the heater at the bottom of the well to heat the air injected near the oil layer at the bottom of the well. According to the temperature requirements of the burning oil layer, the manual adjustment of the control cabinet is adopted. The workload of this method is cumbers...

AI Technical Summary

Problems solved by technology

However, the design of the conventional PID controller depends on the precise mathematical model of the controlled object, and the reaction mechanism of the ignition operation is complex, and each parameter has time-varying characteristics during the system reaction process, and is affected by uncertain factors such as external disturbances, so it is difficult to establish an accurate control system. It is difficult to adjust the parameters of the mathematical model, and it cannot solve the contradiction between the relative stability and rapidity of the system.

The conventional PID controller will not change with the change of the error or the rate of error change in the control process. For the control process with large inertia and large hysteresis, it is easy to produce a large overshoot and increase the adjustment time. Decrease the stability of regulation

Therefore, the use of conventional PID controllers cannot achieve precise control of temperature parameters in ignition operations

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