Complementarity framework formulation from bond graphs to model a class of nonlinear systems and hybrid systems with fixed causality

Author:

Villa-Villaseñor Noé1ORCID,Rico-Melgoza J Jesús2

Affiliation:

1. Department of IT-Electronics, CIATEQ Advanced Technology Center, San Luís Potosí, México

2. Faculty of Electrical Engineering, University of Michoacán, México

Abstract

A systematic method for constructing models in the complementarity framework from a bond graph is proposed. Bond graphs with and without storage elements in derivative causality are considered. The proposed method allows the study of switching systems represented by a bond graph model of fixed causality. The proposed methodology allows the complementarity framework to be exploited in different engineering areas by using bond graphs. The idea of representing a unidirectional switch with a model that is essentially the same as a diode is presented. By employing a similar representation for diodes and switches, the modeling and simulation of power switching converters are simplified and become more intuitive. Two application examples are shown. A non-inverting buck-boost converter and a zeta converter with an element in derivative causality are simulated.

Publisher

SAGE Publications

Subject

Computer Graphics and Computer-Aided Design,Modeling and Simulation,Software

Cited by 4 articles. 订阅此论文施引文献 订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献

1. Real-Time Simulation of Model Predictive Control for Boost Converters in the Linear Complementarity Framework;2022 IEEE International Autumn Meeting on Power, Electronics and Computing (ROPEC);2022-11-09

2. Efficiency of the Bond Graph Approach for Robust Diagnosis Micro Electro Mechanic System;Journal of Circuits, Systems and Computers;2021-04

3. Complementarity Model of a Photovoltaic Power Electronic System With Model Predictive Control;IEEE Transactions on Circuits and Systems I: Regular Papers;2019-11

4. Converting High Level Models into DEVS Modeling and Simulation Applications;Simulation Foundations, Methods and Applications;2019

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