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An analog behavioral equivalence boundary search methodology for simulink models and circuit level designs utilizing evolutionary computation
Affiliation:1. Department of Electrical and Electronics Engineering, Bogazici University, Istanbul, Turkey;2. Department of Computer Engineering, Bogazici University, Istanbul, Turkey;1. Northwestern Polytechnical University, 127 West Youyi Road, Xi’an, 710072, PR China;2. National Key Laboratory of Aerospace Flight Dynamics, 127 West Youyi Road, Xi’an, 710072, PR China;1. LESyC, IMAE, Facultad de Ciencias Exactas, Ingeniería y Agrimensura, Univ. Nacional de Rosario, Rosario, Argentina;2. Area Física de la Atmósfera, Radiación Solar y Astropartículas, Instituto de Física Rosario (CONICET-Univ. Nacional de Rosario), Rosario, Argentina;3. Instituto en Tecnologías de Detección y Astropartículas (CONICET-CNEA-UNSAM), Mendoza, Argentina;4. UTN Facultad Mendoza, Laboratorio Pierre Auger, Mendoza, Argentina;5. Facultad de Ciencias Bioquímicas y Farmacéuticas, Univ. de Rosario, Rosario, Argentina;6. Escuela de Cs. Físicas y Nanotecnología, Yachay Tech, 100119 Urcuquí, Ecuador;7. Facultad de Ciencias Fisico-Matemáticas, UNSan Luis, San Luis, Argentina;8. Institute of Physics of Academy of Science of the Czech Republic, Czech Republic;9. RCPTM, Joint Laboratory of Optics of Palacky University and Institute of Physics of AS CR, Faculty of Science, Palacky University, Czech Republic;10. Astronomical Observatory, University of Warsaw, Aleje Ujazdowskie 4, 00-478 Warsaw, Poland;1. New York University Abu Dhabi, Abu Dhabi, United Arab Emirates;2. Age Scientific srl – Capezzano Pianore (LU), Italy
Abstract:We propose a simulation-based analog equivalence boundary search methodology for high level Simulink models and their low level HSpice counterparts.The equivalence of high and low level designs is determined by comparing a set of predefined performance parameters measured during the simulation of both models. Our methodology investigates the search space to obtain boundary of input parameters, where both models have equivalent performance parameters. We build an optimization problem, where the error percentage between the performance parameters of both models being less than a specified threshold is defined as success criteria. In this problem, input parameters are determined by utilizing evolutionary computation. At the end of the optimization, the border of equivalence for the models is found for input parameters satisfying the success criteria. We demonstrate the validity of our approach on three designs, an inverter, an operational amplifier, and a buck converter, where our approach proves to be an efficient tool in finding an equivalence boundary of analog circuits and models.
Keywords:Behavioral equivalence checking  Model based design  Evolutionary computation  Simulink  Boundary search methodology
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