Pressure control method for waste heat drying device of waste plastic cracking furnace

Abstract

The invention discloses a pressure control method for a waste heat drying device of a waste plastic cracking furnace. A traditional open-loop control mode, even a manual operation means, is basically adopted by pressure control of existing drying devices, and adjustment of control parameters completely depends on experience of technicians. In addition, due to the facts that an observer which is in asymptotic convergence in an infinite time domain is usually adopted by an existing predictive control method based on state space to carry out system state estimation, and errors of estimation are difficult to converge in a limited time domain, precision of the estimation and the rate of convergence need improving. According to the pressure control method for the waste heat drying device of the waste plastic cracking furnace, the predictive control method is used for carrying out pressure control of the waste heat drying device of the household garbage waste plastic cracking furnace, an observer which is in the asymptotic convergence in the infinite time domain is designed for the first time, the estimation is carried out on system state vectors be used for prediction on a pressure output value, optimization solution is carried out through an optimization method based on a recurrent neural network, and thus accuracy and rapidness of the pressure control of the waste heat drying device are improved.

Description

technical field [0001] The invention belongs to the technical field of automation, and relates to a pressure control of a residual heat drying device of a domestic garbage waste plastic cracking furnace. Through predictive control, an observer converged in a limited time domain and a method based on recursive neural network optimization, the residual heat drying device is realized. The optimal control of pressure can be used for pressure control of waste plastic cracking and drying equipment in related industries. Background technique [0002] With the rapid development of urbanization, a huge amount of municipal solid waste is produced. If the renewable resources in domestic waste are not used rationally, it will cause serious environmental pollution and waste of resources. The waste plastics in domestic garbage are renewable resources, and the oil production through pyrolysis can not only reduce the pollution to the environment, but also alleviate the shortage of resource...

AI Technical Summary

Problems solved by technology

However, these methods still have room for improvement. For example, the existing predictive control methods based on state space usually use infinite time domain ( k →∞) Asymptotically convergent observers (such as the Kalman filter used in the object disturbed by white noise) perform system state estimation, and the estimation error is difficult to be within the finite time domain ( k is a positive integer of finite size), so the estimation accuracy and convergence speed need to be improved

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