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Optimization and control of CMOS analog integrated circuits for cyber-physical systems using hybrid grey wolf optimization algorithm

机译:使用混合灰狼优化算法的网络地理系统CMOS模拟集成电路的优化与控制

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Guaranteeing the reliability of cyber-physical systems (CPS) requires analog integrated circuits for correct functioning. Analog integrated circuits capture the continuous signal and amplify the signal for further processing in CPS applications. This paper presents the hybrid swarm intelligence based approach for determining the optimal transistors sizes and bias current values of CMOS differential amplifier and an operational amplifier. We proposed the simplex search based global optimization method called a hybrid grey wolf optimization (GWO) for solving amplifiers circuit sizing problems. Simplex and GWO techniques were combined to improve the local search capabilities of the optimization method. Our main aim is to optimize the transistor size and bias current values using hybrid GWO algorithm for an optimal design of the CMOS amplifiers. CMOS 180 nm technology was utilized to finding the circuit performance using proposed optimization approach. Simulation result shows that the proposed method provides the better result for circuit performance parameters such as DC gain, phase margin, unity gain bandwidth and power dissipation.
机译:保证网络物理系统(CPS)的可靠性需要模拟集成电路进行正确运行。模拟集成电路捕获连续信号并放大信号,以进一步处理CPS应用。本文介绍了用于确定CMOS差分放大器和运算放大器的最佳晶体管尺寸和偏置电流值的基于混合群体的方法。我们提出了基于Simplex搜索的全局优化方法,称为混合灰狼优化(GWO),用于求解放大器电路尺寸问题。组合单纯X和GWO技术以改善优化方法的本地搜索能力。我们的主要目的是使用混合GWO算法优化晶体管尺寸和偏置电流值,以实现CMOS放大器的最佳设计。 CMOS 180 NM技术用于使用所提出的优化方法来寻找电路性能。仿真结果表明,该方法为电路性能参数提供了更好的电路性能参数,如DC增益,相位裕度,Unity GAND带宽和功耗。

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