%0 Journal Article
%T Multiobjective Genetic Algorithms Program for the Optimization of an OTA for Front-End Electronics
%A Abdelghani Dendouga
%A Slimane Oussalah
%A Damien Thienpont
%A Abdenour Lounis
%J Advances in Electrical Engineering
%D 2014
%R 10.1155/2014/374741
%X The design of an interface to a specific sensor induces costs and design time mainly related to the analog part. So to reduce these costs, it should have been standardized like digital electronics. The aim of the present work is the elaboration of a method based on multiobjectives genetic algorithms (MOGAs) to allow automated synthesis of analog and mixed systems. This proposed methodology is used to find the optimal dimensional transistor parameters (length and width) in order to obtain operational amplifier performances for analog and mixed CMOS-(complementary metal oxide semiconductor-) based circuit applications. Six performances are considered in this study, direct current (DC) gain, unity-gain bandwidth (GBW), phase margin (PM), power consumption (P), area (A), and slew rate (SR). We used the Matlab optimization toolbox to implement the program. Also, by using variables obtained from genetic algorithms, the operational transconductance amplifier (OTA) is simulated by using Cadence Virtuoso Spectre circuit simulator in standard TSMC (Taiwan Semiconductor Manufacturing Company) RF 0.18£¿¦Ìm CMOS technology. A good agreement is observed between the program optimization and electric simulation. 1. Introduction Microelectronics industry is distinguished by the raising level of integration and complexity. It aims at decreasing exponentially the minimum feature sizes used to design integrated circuits [1]. The cost in time of design is a great problem to the continuation of this evolution. Senior designer¡¯s knowledge and skills are required to ensure a good analog integrated circuit design. To fulfill the given requirements, the designer must choose the suitable circuit architecture, although different tools which partially automated the topology synthesis appeared in the past [2, 3]. Therefore, the use of multiple-objective optimization algorithms is of a great importance to the automatic design of operational amplifier. Accuracy, ease of use, generality, robustness, and reasonable run-time are necessary for a circuit synthesis solution to gain acceptance by using optimization methods [4¨C9]. This method uses a program based on multiobjective optimization using a genetic algorithm to calculate the optimal transistors dimensions, length, and width of an operational amplifier (Figure 1) which is used as part of an electronic front-end for signal shaping stage. The method which handles a wide variety of specifications and constraints is extremely fast and results in globally optimal designs. Figure 1: Operational amplifier design flow. The aim of this work is
%U http://www.hindawi.com/journals/aee/2014/374741/