A disturbance rejection iterative learning control method for steam-water heat exchange system

By employing a model-free adaptive iterative learning control method and utilizing data-driven design of disturbance observers and adaptive update algorithms, the control accuracy and stability issues caused by non-repetitive disturbances in steam-water heat exchange systems are resolved, achieving high-precision control of the steam-water heat exchange system.

CN122386697APending Publication Date: 2026-07-14JIANGNAN UNIV
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Patent Information

Authority / Receiving Office
CN · China
Patent Type
Applications(China)
Current Assignee / Owner
JIANGNAN UNIV
Filing Date
2026-04-28
Publication Date
2026-07-14

AI Technical Summary

Technical Problem

Traditional control methods are difficult to effectively suppress the effects of non-repetitive disturbances in steam-water heat exchange systems, resulting in control accuracy and stability that cannot meet high-precision requirements. This is especially true in applications in chemical, HVAC, and energy fields, where there are problems with time-varying model parameters and complex dynamic characteristics.

Method used

A disturbance-resistant iterative learning control method that does not require system model information is designed. A model-free adaptive iterative learning control scheme based on disturbance observer is adopted. The disturbance observer and controller are designed through data-driven design, and the observer gain vector is estimated in real time by combining an adaptive update algorithm to achieve fast compensation for non-repetitive disturbances.

Benefits of technology

The tracking accuracy and disturbance rejection capability of the steam-water heat exchange system during batch operation were improved, achieving high-precision and stable control. Simulation results show that bounded convergence and fast convergence can be achieved under non-repetitive disturbances.

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Abstract

The application discloses a kind of anti-disturbance iterative learning control methods of steam-water heat exchange system, it is related to industrial process control field.This method is based on dynamic linearization technique, constructs equivalent linearization data model in iterative domain, which can describe the nonlinear dynamic characteristics of steam-water heat exchange system.For unknown non-repetitive disturbance, the partial format iterative dynamic linearization technique is used to design data-driven disturbance observer;To realize the real-time estimation of observer gain vector in batch direction, the adaptive updating algorithm of the vector is derived by minimizing the performance index function.The disturbance observer and the model-free adaptive iterative learning control framework are integrated to construct an anti-disturbance iterative learning control scheme and applied to the steam-water heat exchange system.The scheme has a pure data-driven feature, and the design of the disturbance observer and the controller only depends on the input-output data, without the need for system model information, which can effectively suppress the influence of non-repetitive disturbance and achieve high-precision tracking control of the desired trajectory.
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