Predictive control method and system based on multi-model generalized predictive controller

Abstract

The invention discloses a predictive control method and system based on a multi-model generalized predictive controller. While process disturbance is inhibited, a preset desired output value is enabled to track the optimum set value track, and dynamic characteristics of a system are distinguished in parallel by adopting a plurality of fixed models and a plurality of adaptive models so that an actual output value and an optimum input control quantity of the system can be obtained. The invention also provides a predictive control system which is of a DRTO (Dynamic Real-Time Optimization) dual-layer structure, and adopts a multi-mode generalized predictive controller to replace an existing single-model generalized predictive controller. The predictive control method has the following beneficial effects of well matching the actual process characteristic in the production, reducing the system cost consumption, increasing the system economic benefit, improving the system transient state performance and the system regulating capacity when a system model parameter hops, being capable of effectively eliminating the interference of disturbance to system output, and reducing the influence of inconsistency of models of an optimization layer and a control layer in the DRTO dual-layer structure to the economic benefit.

Description

technical field [0001] The invention belongs to the technical field of model predictive control (MPC), and in particular relates to a predictive control method and system based on a multi-model generalized predictive controller. Background technique [0002] The increasingly fierce competition in the industrial process requires more flexible equipment operation to increase productivity and reduce production costs, which requires economic optimization to be integrated into each stage of planning, scheduling, optimization, and control in equipment operation. The existing technology is like a typical two-tier RTO structure, which includes a real-time optimizer (RTO) based on economic indicators and a model predictive controller (MPC). The upper RTO layer obtains the optimal setting value of the output object by solving the real-time optimization problem based on the steady-state model, and transmits the optimal setting value to the lower MPC layer. The output object tracks the...

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Problems solved by technology

However, due to the existence of random noise, it is difficult for the conventional multi-model to match the actual process characteristics. Therefore, how to establish a controller that can not only consider economic benefits but also ensure the transient performance of the system and the ability to adjust when jumping is a special need to solve at present. a question of

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