Control method based on prediction model and controller

Abstract

The invention discloses a control method based on a prediction model and a controller. The prediction model on which the control method is based is a normalized prediction model, the normalized prediction model is a functional relationship between variables having no unit and ranging from 0 to 1, according to a predicted value of the measurement quantity of a controlled object normalized at the second time, when the control amount increment normalized at the second time is optimized, a numerical range of each coefficient of an established constraint equation is relatively stable, reduction ofthe number of iterations of the optimization algorithm is facilitated, so the optimization process takes less time, the optimization speed is improved, real-time control of the underlying controller can be realized, and thereby the control effect of the underlying controller on the controlled object can be optimized.

Description

technical field [0001] The present application relates to the technical field of industrial control, in particular to a control method and controller based on a predictive model. Background technique [0002] At present, in the industrial control system, the underlying controller used to control the controlled object (for example, the opening of the valve set on the pipeline) mostly uses a PID (proportion, integral differential) controller (proportional-integral-differential control device). [0003] A PID controller is a common feedback loop component in industrial control applications, consisting of a proportional unit P, an integral unit I and a differential unit D. The basis of PID control is proportional control; integral control can eliminate steady-state error, but may increase overshoot; differential control can speed up the response speed of large inertia system and weaken the overshoot tendency. [0004] However, in a nonlinear, large pure lag industrial process ...

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Problems solved by technology

[0004] However, in a nonlinear, large pure lag industrial process system, the PID controller cannot achieve the optimization of the control effect, for example, to find the best operating point of the control parameters under many constraints; when the system is disturbed, such as Material properties, environmental temperature changes, etc., timely stabilize the control parameters within the feasible operating range; strongly coupled system multi-input multi-output system decoupling control; monitor environmental changes, and calculate the optimal area of ​​​​system operation in real time, etc.

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