A multi-objective collaborative optimization pipe network automatic delivery control method

By using adversarial domain adaptation training and dynamic multi-objective evolutionary algorithms, robust features are generated, which solves the problems of insufficient model generalization ability and poor dynamic adaptability in automatic pipeline distribution control, and realizes efficient, reliable and economical operation of pipeline control system.

CN121364636BActive Publication Date: 2026-07-07LIAONING ZHONGAN ZHIDA TECHNOLOGY CO LTD
2 Cites 0 Cited by

Patent Information

Application Number
CN202511642178.0
Authority / Receiving Office
CN · China
Patent Type
Patents(China)
Current Assignee / Owner
Filing Date
2025-11-11
Publication Date
2026-07-07
Estimated Expiration
2045-11-11

AI Technical Summary

Technical Problem

Existing automatic pipeline distribution control methods lack model generalization ability when facing real-time changing operating conditions, making it difficult to respond quickly to sudden events. Furthermore, they lack dynamic adaptability and balance when performing multi-objective optimization, resulting in insufficient robustness and effectiveness of the control strategy.

Method used

By employing a combination of adversarial domain adaptation training, dynamic multi-objective evolutionary algorithms, and collaborative balance evaluation, robust features are generated by eliminating the differences between historical and real-time data. This allows for real-time monitoring of environmental changes, the construction of a dynamic multi-objective optimization model, rapid response to sudden environmental changes, and the achievement of collaborative and balanced control of multiple operational objectives.

Benefits of technology

It improves the model's generalization ability and prediction accuracy under complex operating conditions, ensures the long-term effectiveness and reliability of the control strategy, can quickly adapt to dynamic environmental changes, achieve synergy and balance among various objectives, and reduce system operating costs.

✦ Generated by Eureka AI based on patent content.
Patent Text Reader

Abstract

The application discloses a kind of multi-objective collaborative optimization's pipe network automatic delivery control method, belong to process control and system automation technical field, it includes obtaining pipe network operation data, generates robust feature by adversarial domain adaptation training, real-time monitoring environmental mutation, utilize robust feature to construct dynamic multi-objective optimization model, and adopt dynamic multi-objective evolutionary algorithm to generate Pareto solution set, finally combine collaborative balance degree index and preference function to select optimal control solution.The application adopts adversarial domain adaptation technology to eliminate data domain difference, obtain robust feature which is not sensitive to working condition change, and combine dynamic multi-objective evolutionary algorithm responding to environmental mutation, can track and determine optimal balance solution between energy consumption, pressure safety and service quality in real time when pipe network load and operating environment dynamically change, improve the real-time performance, robustness and multi-objective collaborative optimization level of pipe network automatic delivery control.
Need to check novelty before this filing date? Find Prior Art