Optimal Sizing Of Transistor's Parameter Using Genetic Algorithm

Yap, Yung Lin (2010) Optimal Sizing Of Transistor's Parameter Using Genetic Algorithm. Project Report. UTeM, Melaka, Malaysia. (Submitted)

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Abstract

This project report presents the design and development of genetic circuit optimizer. Initially, genetic circuit optimizer is based on the Simple Genetic Algorithm (SGA) to perform the optimization function. Genetic algorithm is the programming concept that mimics the mutation concept of biological evolution. Genetic circuit optimizer tends to use the transistor width and length in the selected circuit to tune circuit performance near to optimal. Genetic Circuit Optimizer developed by using Pspice and Matlab. SGA was written in Matlab environment to perform the optimization task. The random transistor width and length named chromosome are generated in Matlab by uing SGA. Chromosomes are decoded into format that recognized by PC Simulation Program with Integrated Circuit Emphasis (PSpice) to simulating corresponding output. Interfacing part is essential part of the project. The output with the transistor’s width and length are encoded into chromosome to perform genetic operation. Genetic operation performed to optimal the chromosome. Previous research had concluded the GA optimization process. Moreover, researcher had found the way to decode and encode the transistor sizing into chromosome. Improved Non-dominate Sorting Genetic Algorithm was used to upgrade the Genetic Circuit optimizer. Hence, the Genetic Circuit Optimizer manages to optimization more circuit parameters. The capabilities of Genetic Circuit Optimizer are proved by optimizing the inverter circuit, four stage amplifier circuit and Operational Transconductance Amplifier circuit. Furthermore, the speed and accuracy of Genetic Circuit Optimizer are improved by changing the simulator into Disk Operation Mode (Dos) and using Hspice respectively. Finally, verification and validation of Genetic Circuit Optimizer are statistically showed and studied.

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