This paper proposes an original approach to the design of intelligent control systems for complex time-varying (nonstationary) objects in which industrial processes are repeatedly reproduced over a certain period of time. Such reproduction allows accumulating data and knowledge about control programs, conditions and results of their implementation, and the trajectories of controlled variables. The motion of a controlled object is decomposed into perturbed and unperturbed motions. The unperturbed programmed motion of the object is described using expert systems and the concept of case-based reasoning (CBR); the perturbed motion of the object, using artificial neural networks.

本文提出了一种用于复杂时变（非平稳）对象的智能控制系统设计的原始方法，在该对象中，在一定时间段内重复复制了工业过程。这种再现允许积累有关控制程序，其执行条件和结果以及受控变量轨迹的数据和知识。受控对象的运动被分解为摄动和非摄动运动。使用专家系统和基于案例的推理（CBR）的概念来描述对象的不受干扰的编程运动。使用人工神经网络对物体进行扰动