电动调节阀作为天然气场站自动分输控制系统中重要的被控设备,承担着燃气输送压力、流量等关键输气参数的调节与控制任务,天然气场站电动调节阀多采用比例—积分—微分(Proportional-Integral-Derivative,PID)控制算法进行控制。大量工程实践表明,PID控制算法存在参数难以整定、抗干扰性能差以及难以适应时变系统等问题,导致控制调节精度不高,人力物力成本占用量高。针对上述问题,对天然气自动分输PID控制算法进行优化,研究学习规则的选用思路,提出单神经元PID的控制方案。在此基础上,以输气系统支路上的电动调节阀的阀门开度与支路压力之间的传递函数为研究对象,通过仿真模拟多种现场使用场景,对传统PID控制算法以及单神经元自适应PID控制算法的控制性能进行比对。结果表明,2种算法均能实现对输气压力的调控,但单神经元自适应PID控制算法控制更平缓,能够减少调节阀大幅瞬开或瞬关的次数,调节支路压力更快速有效,抗干扰能力较强。研究结果为天然气站场输气过程中的电动调节阀控制提供了参考。

As a key controlled device in the automatic distribution control system of natural gas stations, the electric regulating valve is responsible for adjusting and controlling critical gas transmission parameters such as pressure and flow rate. The Proportional-Integral-Derivative(PID) controlling algorithm is used to control the electric regulating valve in most natural gas stations. However, extensive engineering practice shows that the PID controlling algorithm suffers from difficulties in parameter tuning, poor anti-interference capability, and challenges in adapting to time-varying systems, resulting in low control accuracy and high manpower and resource consumption. To address these issues, this paper proposes an optimized PID control algorithm for natural gas automatic distribution based on a single neuron algorithm and investigates the selection of relevant learning rules. Taking the transfer function between the valve opening of an electric regulating valve in a gas transmission system branch and the branch pressure as the research object, control performances of the traditional PID and the single neuron adaptive PID controlling algorithms are compared through simulation of various field scenarios. The above results show that both traditional PID controlling algorithm and single neuron adaptive PID controlling algorithm can effectively regulate the gas transmission pressure. However, the single neuron adaptive PID controlling algorithm provides smoother control, reduces the frequency of large instantaneous valve openings or closings, achieves quicker and more effective pressure regulation, and exhibits stronger anti-interference capability. The reasearch provides reference for electric regulating valve control in gas transmission of natural gas stations.