Adaptive Control of Gas Control Systems Based on Dynamic Neural Networks
摘要
The basic principle underlying the construction of automatic control systems is the principle of control by deviation, or the principle of negative feedback. Increasing the corresponding gain factors in closed loops makes it possible to reduce the influence of uncontrolled external influences and changes in the characteristics of the controlled object the stability of closed-loop systems is ensured. It should be taken into account that the effect of deep negative feedback can be used only when, simultaneously with an increase in the gain, the stability of closed-loop systems is ensured. The presence of time delay, inertia and nonlinearities does not allow an unlimited increase in the gain factor, as this leads to a violation of the stability of the system. Without increasing the amount of a priori information, it is impossible to increase the gain factor without violating stability. Other possibilities based on disturbance compensation effects are also inapplicable in conditions of insufficient a priori information. They are based on the use of various control principles, in particular of invariant control, the principles and associated with the construction of the open-loop transfer function of the combined control system. This requires detailed knowledge of the characteristics of the controlled object, which are often unknown.