Essentially nonlinear compensation controller of servo system

Abstract

The invention relates to a non-linear compensating controller in essence of a servo system, belonging to the field of industrial control. The compensating controller of the invention comprises a variable structure neural network feedback compensation part, forward adaptive compensation part and a robust compensation part; therefore, the controller can simultaneously compensate friction non-linearity and driver dead area non-linearity existing in the compensating system. The variable structure neural network compensates for the friction non-linearity in the system while the adaptive robust control carries out compensation control on the dead area non-linearity and external perturbation in a system driver; the variable structure neural network technology reduces network size and calculation amount and strengthens practicality of the controller; the adaptive robust control ensures static precision, transient performance and robustness of the system; applied to location tracking control of the electric motor, as indicated by actual operation results, the compensating controller of the invention can endow the system with excellent static tracking precision and robustness.

Description

technical field [0001] The invention relates to an essential nonlinear compensation controller of a servo system, which belongs to the field of industrial control. Background technique [0002] Servo systems are widely used in industrial manufacturing, national defense and other fields. With the development of social economy, the working conditions of the production system are becoming more and more complex, and the requirements for the control performance of the servo system are also getting higher and higher (including high precision requirements and fast response). The friction nonlinearity and dead zone nonlinearity in the system are one of the main factors that damage the system performance. Taking friction nonlinearity as an example, if it is not well compensated, it will affect the steady-state accuracy of the system, and it will cause the so-called "crawling" phenomenon at low speeds, and may even lead to limit cycles or instability in the system; and death Area no...

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Problems solved by technology

However, such controllers generally require huge basis functions or fuzzy rules, and the computational complexity of the controller is too large, which is not conducive to practical applications.

[0004] For the compensation of dead zone nonlinearity in the servo system, the adaptive inverse model control idea in the book "Adaptive Control of Systems with Actuator

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