EOS-ELM-based piezoelectric driving positioning platform modeling method and system, and EOS-ELM-based piezoelectric driving positioning platform control method

Abstract

The application discloses an EOS-ELM-based piezoelectric driving positioning platform modeling method and system, and an EOS-ELM-based piezoelectric driving positioning platform control method. According to the application, by taking the current desired output displacement, a plurality of previous output displacements and an input driving voltage as the input values of a model, and taking the input driving voltage value of a piezoelectric driver at the current moment as an output value of the model, a hysteretic nonlinear multi-value mapping problem is solved, and a complicated model inversion process can be avoided; secondly, the weights and the threshold values between a hidden layer and an input layer are given randomly, and a conventional neural network can be transformed into a linear equation model, so that the training time of the model is shortened greatly; thirdly, an infinite differentiable function is used as a hidden layer activation function, so that an excellent training effect can be realized; additionally, just by adopting a recursive least square method, the parameter online adaptive updating can be realized, and the applicability of the model is improved; furthermore, by integrating a plurality of weak learning machines, the precision and the stability of the model can be improved.

Description

technical field [0001] The invention relates to the field of precision control, in particular to an EOS-ELM-based piezoelectric drive positioning platform modeling method, control method and system. Background technique [0002] Piezoelectric actuators have the advantages of small size, light weight, high stiffness, large output force, high output displacement resolution, and fast dynamic response, and are widely used in piezoelectric-driven micro / nano positioning platforms. But actuators made of piezoelectric materials are inherently hysteretic nonlinear. In the motion control of piezoelectric-driven micro / nano positioning platforms, it is a very challenging problem to solve the control error problem caused by hysteresis nonlinear characteristics, and it is also a key problem to improve the control accuracy. [0003] At present, there are three main categories of hysteretic nonlinear modeling methods: physical (such as Maxwell model, Duhem model, and JA model), semi-physic...

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Problems solved by technology

[0004] These models either have low precision and slow modeling speed, or it is difficult to model online or the inverse model is difficult to obtain; and almost none of them can be applied in a well-combined control, and most hysteretic nonlinear models must rely on Some other control links are used, such as PID control, repetitive control, etc.; even if there are a few hysteretic nonlinear models that can realize motion control, it is difficult for these models to perform effective online adaptive parameter adjustment

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