Modeling of Hammerstein nonlinear dynamic system and concentration control of continuous stirring reactor

Abstract

The invention provides modeling of a Hammerstein nonlinear dynamic system and concentration control of a continuous stirring reactor, and the method comprises the steps: building a continuous stirring reactor model by using the Hammerstein nonlinear dynamic system, approaching a static nonlinear module by using a three-layer BP neural network, and building a linear dynamic module model by using a transfer function model. In the method, firstly, according to input and output data of a binary signal, a least square method is adopted to estimate parameters of a dynamic linear module in a model; secondly, on the basis of input and output data of random signals, parameters of a static nonlinear module in the model are estimated through a stochastic gradient descent optimization algorithm containing momentum factors; and finally, a reactant concentration control problem of the continuous stirring reactor system is converted into a linear system control problem by utilizing a special structure of a Hammerstein nonlinear system, so that the design of the control system is simplified, and a better control effect is achieved.

Description

technical field [0001] The invention belongs to the field of process industry, and relates to the modeling of a Hammerstein nonlinear dynamic system and the concentration control of a continuous stirring reactor. The method is applicable to related fields such as chemical industry, biopharmaceutical, and petroleum production. Background technique [0002] At present, in the field of modeling and control of nonlinear dynamic systems, a novel class of block-structured nonlinear dynamic systems has become a hot research topic. Among the block-structure nonlinear dynamic systems, the Hammerstein nonlinear dynamic system is a typical nonlinear system with a specific structure. It combines static nonlinear modules and linear dynamic modules. The system can better describe industrial equipment and processes. Such as fermentation bioreactor system, continuous stirring reactor, neutralization process, distillation tower and other nonlinear processes. [0003] The modeling research o...

AI Technical Summary

Problems solved by technology

[0005] 1. Complex industrial processes are characterized by strong nonlinearity and uncertainty, which makes it difficult to model problems. How to establish a mathematical model of Hammerstein nonlinear system that satisfies the process characteristics is the basis for solving optimization problems and implementing effective control;

[0006] 2. In terms of parameter estimation of Hammerstein nonlinear systems, existing parameter estimation methods often contain product terms of system parameters, and decomposition techniques are required to separate parameters, which increases the complexity of calculation and the difficulty of parameter estimation

[0007] 3. In terms of control of nonlinear systems, the existing composite control strategy can achieve good control results, but there are still defects such as large amount of calculation and complex control laws

Images