Model order reducing method for a parameter system

Abstract

The present invention belongs to the field of microelectromechanical MEMS and electronic technology, and is especially one kind of order reducing method for system model with parameters. The model order reducing technology can raise simulating and verifying speed of system model effectively and improve the design scheme of circuit and device timely. The present invention establishes model order reducing method to parameter system. Transfer function of parameter system is multiple series developed to constitute son projection matrix, and the son projection matrix is orthogonalized to constitute projection matrix. The projection matrix is used in reducing order of the original parameter system and the obtained reduced-order system is independent on some special values of the system parameters and can maintain order reducing precision on different values. The present invention has greatly raised order reducing precision and efficiency.

Description

technical field [0001] The invention belongs to the field of micro-electromechanical MEMS and electronic technology, and in particular relates to a model order reduction method of a parameter system. technical background [0002] Thermal phenomena have always played a very important role in many MEMS devices, such as microhotplate sensors, microfluidics, electro-thermal micromotors[2] and so on. Therefore, electrothermal simulation is an important part of modern engineering design. Usually need to use the finite element method to carry on the accurate description to a thermal model, thus obtains is a large-scale ordinary differential equation system. The traditional method of direct simulation is very time-consuming, which causes great difficulties for design and system-level simulation. Recently, in the field of electrothermal simulation, the establishment of a compact model has become the focus of discussion [3][4]. In practice, an important requirement of the compact m...

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Problems solved by technology

[0037] 2. If in order to ensure the accuracy of the reduced-order system, the original parameter system needs to be reduced every time the parameters are changed, then the cost of reducing the order will be very high, especially when the parameters require many different values, it is necessary to The original system has been reduced many times. If the time spent for each reduction is not much different from the time spent on direct simulation of the original system, the traditional method of reduction will lose its meaning.

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