Multi-target hierarchical prediction control method based on continuous stirred tank reactor

Abstract

The invention discloses a multi-target hierarchical prediction control method based on a continuous stirred tank reactor. According to the control method, a double-layer prediction control algorithm is introduced and changes the situation that in the control process of the CSTR, only a dynamic control target is controlled, and economic indexes are ignored. In the control process, a two-level hierarchical prediction control structure is adopted, an expansion Kalman observer is introduced in a dynamic control layer to perform unbiased estimation on the state, a multi-target hierarchical optimization is adopted in a steady-state optimization layer, and important optimization targets are met preferentially. Meanwhile, a finite element orthogonal configuration method is adopted in a whole control system so that a nonlinear optimization control proposition can be converted into a nonlinear programming problem, a model equation serves as a constraint condition, values on configuration points serve as prediction values, a prediction model can be obtained without linearization or step response, and therefore linear errors can be avoided, and integral objects need to be independently processed.

Description

technical field [0001] The invention belongs to the field of process industry optimization control, in particular to a multi-objective bi-level predictive control method based on nonlinear model discretization. Background technique [0002] The continuous stirring reactor is a chemical reactor with strong nonlinearity, and it is the core equipment in the chemical production process. The quality of the control performance directly affects the production efficiency and product quality. Therefore, many scholars have devoted themselves to the research of CSTR control methods, but the model has complex nonlinearity, and there is still no consistent control method for it. [0003] Although the control method that only considers the control target ensures the product quality, it ignores the economic benefits, which is not good for the factory production in the long run. Using a two-level hierarchical control method in which the steady-state objective function is weighted for each ...

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Problems solved by technology

The quality of the control performance directly affects the production efficiency and product quality. Therefore, many scholars have devoted themselves to the research of the CSTR control method, but the model has complex nonlinearity, and there is still no consistent control method for it.

[0003] Although the control method that only considers the control target ensures the product quality, it ignores the economic benefits, which is not good for the factory production in the long run

The two-level hierarchical control method using the steady-state objective function as the weight of each optimization objective function. Although the control objective and economic benefits are considered, it is difficult to guarantee the priority of each optimization objective function, and there is no certain criterion for the selection of weights.

The two-level hierarchical control method using model linearization has linearization errors. For a strongly nonlinear and real-time control system such as CSTR, the impact of errors cannot be ignored.

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