A Robust Iterative Learning Model Predictive Control Method Applied to Batch Stirred Tank Reactor

Abstract

The invention relates to a robust iterative learning model predictive control method which can be applied to control of an intermittent stirred tank reactor and solves the problem of high-precision tracking of reaction temperature of the intermittent stirred tank reactor under a variable reference track. The method mainly comprises the following steps: constructing a linear parameter varying (LPV)prediction model according to a nonlinear mechanism model of the intermittent stirred tank reactor; absorbing the control experience of the past batch through iterative learning control, and improving the tracking precision; processing real-time interference effectively by adopting model prediction control, and ensuring the time domain stability and robustness of the system; regarding the changeof the reference track among batches of the intermittent stirred tank reactor as the bounded interference of the iterative shaft, and constructing the H infinite constraint to ensure the control effect under the variable reference track. Compared with the traditional iterative learning model predictive control method, the robust iterative learning model predictive control method has higher adaptability and better tracking performance under the variable reference track of the intermittent stirred tank reactor.

Description

technical field [0001] The invention relates to the field of chemical production, in particular to a robust iterative learning model predictive control method applied to batch stirred tank reactors. Background technique [0002] A batch reactor refers to a device that performs chemical reactions intermittently. In the chemical production process, batch reactors are often used for mass production, especially for products with different specifications and high output value. Batch reactors have the characteristics of flexible operation, variable production, low investment, and quick start-up, so they are widely used in pharmaceutical, pesticide, dye and various fine chemical industries. The product quality of the batch reactor is very unstable, and the production capacity of the equipment is also very different. Therefore, the automatic control of the batch reactor is very important. The important direction of its development is to apply advanced control theory to achieve opti...

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Problems solved by technology

[0004] Aiming at the problems existing in the prior art, the present invention provides a robust iterative learning model predictive control method applied to batch stirred tank reactors to solve the variable reference trajectory tracking problem of batch stirred tank reactors

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