Distributed PID (Proportion Integration Differentiation) predictive function control method for furnace box temperature of waste plastic cracking furnace

Abstract

The invention discloses a distributed PID (Proportion Integration Differentiation) predictive function control method for the furnace box temperature of a waste plastic cracking furnace. The distributed PID predictive function control method comprises the following steps: firstly, establishing a step response model vector of a process object by acquiring real-time step response data of a control system; secondly, converting an online optimization problem of a large-scale system into an optimization solving problem of each small-scale subsystem, and considering each subsystem under a network environment as an intelligent agent, wherein all the intelligent agents realize information sharing by network communication; thirdly, improving a performance index of a DPFC (Distributed Predictive Function Control) method by introducing a PID operator, and designing PID predictive function controllers of all the intelligent agents; fourthly, enabling an instant control law obtained at a current moment to act on each intelligent agent, and rolling a time domain to the next moment; finally, finishing an optimization task of the whole large-scale system by sequential iterative cycle. According to the distributed PID predictive function control method disclosed by the invention, the defects of a traditional DPFC method are effectively made up, and the degree of freedom of control parameter design is improved.

Description

technical field [0001] The invention belongs to the technical field of automation, and relates to a distributed PID predictive function control method for the furnace temperature of a waste plastic cracking furnace. Background technique [0002] With the development of computer network technology, control as a means of information processing is not limited to centralized control structure, but more replaced by distributed control structure, which brings many challenges to traditional control problems. . Distributed Predictive Functional Control (DPFC) is a typical application of predictive control in distributed control structures. While effectively solving complex high-dimensional large-scale system online optimization control problems, it usually has high requirements for models, poor steady-state performance, and inability to Quickly suppress unknown interference and other deficiencies. Therefore, for control systems with large uncertainties in model order, environmenta...

AI Technical Summary

Problems solved by technology

Distributed predictive function control (DPFC) is a typical application of predictive control in distributed control structures. While effectively solving complex high-dimensional large-scale system online optimization control problems, it usually has high requirements for models, poor steady-state performance, and inability to Quickly suppress unknown interference and other deficiencies

Therefore, for control systems with large uncertainties in model order, environmental disturbance, nonlinearity, etc., the conventional DPFC method is often difficult to achieve the expected control effect

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