Model-free control method based on cascade observer

Abstract

The invention provides a model-free control method for a high-order nonlinear system, and popularizes the provided method to a high-order multiple-input-multiple-output nonlinear system. Dynamics information of the system is essentially implied in a higher-order differential signal, so that the method is characterized by, to begin with, designing a cascade observer to obtain a high-order differential signal; then, designing a feedback controller by utilizing the high-order differential signal; and popularizing the method to the multiple-input-multiple-output nonlinear system. Theoretical analysis and simulation study show effectiveness of the method. The provided controller method does not need an accurate dynamical model of a model, and information of external disturbance and the like is implied in the observed higher-order differential signal, so that accurate obtaining of the higher-order differential signal in the method is particularly important, and rapidity and estimation precision of the method can cause great influence on the tracking performance of the system.

Description

technical field [0001] The invention relates to the field of control methods for high-order nonlinear systems, in particular to a model-free control method based on cascade observers. Background technique [0002] Although many high-order systems are often studied approximately as second-order systems under certain conditions. However, it is more general to design controllers from the perspective of high-order systems. There are many methods for designing controllers for high-order nonlinear systems, such as methods based on neural networks and methods based on fuzzy techniques. Although the intelligent control method has been widely concerned by scholars as one of the important methods in the field of model-free control, but because it is still in the stage of theoretical research, there are not many practical applications. [0003] The design of fuzzy controller does not rely on the model of the controlled object, but it relies heavily on the experience knowledge of contr...

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