Robust control system identification method

Abstract

The invention provides a robust control system identification method and belongs to the control field. The robust control system identification method is used for determining the value interval of non-linear system parameters and comprises establishing a discrete switch model equation, and simplifying a discrete switching model to acquire a concise expression of the equation; acquiring model inputand output data, substituting the model data into the concise expression for solving to acquire an equation parameter data set; filtering the data inside the parameter data set to acquire filtered data, and redistributing the filtered data to acquire a redistributed parameter data set. By basing the thought of maximum feasible set during a parameter data set determining process and meanwhile applying an efficient approximate calculation method, the robust control system identification method can help rapidly identify the parameter upper and lower limits of a time-varying system, make up the deficiency of various identification methods in the prior art and improve the efficiency of determining the value range of parameters.

Description

technical field [0001] The invention belongs to the field of control, in particular to a system identification method for robust control. Background technique [0002] In the process of controller design, the controlled object is usually described as a linear system or a nonlinear system is expanded near a certain operating point and then approximated as a linear system, and then a linear controller is introduced on this basis. [0003] In the chemical industry, the characteristics of the controlled object (such as flow, temperature, pressure, etc.) will change with time under many working conditions (this type of system is also called a time-varying system) or the controlled object has strong nonlinearity . Therefore, the parameters of the approximated linear system cannot represent the real system well. That is, the parameters of the actual system are uncertain; or there is a certain deviation between the model and the actual system. In order to ensure smooth production...

AI Technical Summary

Problems solved by technology

[0004] In the existing technology, robust control methods are relatively mature, but the identification methods for uncertain systems are very limited; at the same time, most robust control methods are based on the assumption that the uncertainty of the controlled system model is known, But this does not conform to the actual situation and cannot meet the needs of the actual control process

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