Special efficient data-driven internal-model polynomial controller for industrial processes

Abstract

The invention discloses a special efficient data-driven internal-model polynomial controller for industrial processes. The special efficient data-driven internal-model polynomial controller is characterized in that an integral control structure with polynomial and internal-model functions is designed, an error series [e(k)] is inputted into a polynomial controller, a series [u(k)] is outputted by the polynomial controller, the structure is shown as an equation, and a<0>-a<n> and b<1>-b<n> are coefficients to be determined; parameters of a internal-model polynomial controller are optimized by means of data-driven stochastic approximation. The special efficient data-driven internal-model polynomial controller has the advantages that the essence of simplicity and practicality of a PID (proportion, integration and differentiation) controller is inherited, shortcomings of single structure and low error utilization efficiency of the PID controller are overcome, the PID controller is developed into the structure-variable internal-model polynomial controller, dependency on a mathematical model of a controlled object is omitted, and an internal-model driving function is directly added into the internal-model polynomial controller on the basis of data by the aid of a stochastic approximation principle; an internal-model compensation function can be automatically started specifically for a process with obvious large lag, stochastic approximation is synchronously performed on parameters of the internal-model controller and the parameters of the polynomial controllers, and the optimal control parameters can be obtained.

Description

technical field [0001] The invention relates to a control technology in an industrial process, in particular to an efficient data-driven internal model polynomial controller for the industrial process. Background technique [0002] In industrial process control, it has become increasingly difficult for traditional controllers to establish precise mathematical models based on physical and chemical mechanisms to control, predict and evaluate production processes and equipment. Although many methods based on modern control theory, intelligent control theory, and model-free control are theoretically advanced, the gap between them and engineering practice shows no sign of bridging, on the contrary, it has a tendency to intensify. Therefore, the simple and stable PID controller has to still occupy a dominant position in industrial process control, motion control, and aerospace control, although in some complex systems, the control effect is not good. When the model is unknown, it...

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Problems solved by technology

Therefore, the simple and stable PID controller has to still occupy a dominant position in industrial process control, motion control, and aerospace control, although in some complex systems, the control effect is not good

When the model is unknown, it is difficult to tune the parameters of the PID controller, and when the object has complex characteristics such as large time delay, the adjustment function of the PID controller is limited, and the stability of the system is difficult to guarantee

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