In this paper, a general structure using dual-output operational transconductance amplifiers (OTAs) is explored to derive new first-order and second-order multi-function filters using OTAs with multiple current outputs and with and without grounded capacitors. Two first-order all-pass filters that have been obtained are presented, together with an analysis of nonidealities of OTAs, viz., finite bandwidth and parasitic output and input resistance and capacitance. Second-order multi-function filters obtained by using OTA-C simulated inductances in the proposed general structure are also presented. The realization of quadrature oscillator using the proposed first-order all-pass networks is also considered. Detailed analysis of nonideal frequency performance of the OTAs as well as finite output and input impedances is presented. SPICE simulation results are also given for the proposed circuits.
The phenomenal growth of the Electric Vehicle (EV) technology demands efficient and intelligent control strategies for the propulsion system. In this work, a novel fuzzy fractional order PID (FOPID) controller using Ant Colony Optimization (ACO) algorithm has been proposed to control EV speed effectively. The controller parameters and the fuzzy logic controller's membership functions are tuned and updated in real-time using the multi-objective ACO technique. The proposed controller's speed tracking performance is verified using the new European driving cycle (NEDC) test in the MATLAB-Simulink platform. The proposed controller outperforms the ACO-based fuzzy integer-order PID (IOPID), FOPID, and traditional IOPID controllers. The sensitivity analysis confirms the robustness of the proposed controller for varying parameters of the EV model. The stabilization of EV speed in the presence of external disturbance is also confirmed. In the proposed work, an attempt is made to analyze the system's stability using Matignon's theorem, considering the linearized EV model. The proposed controller gives optimum speed tracking performance compared to the Genetic Algorithm (GA) and the Particle Swarm Optimization (PSO) based fuzzy FOPID controllers. Additionally, the optimized fuzzy FOPID controller is realized using a secondgeneration current conveyor with extra inputs (EX-CCII) and fractional-order capacitors with electronic tunability. The controller circuit's performance evaluation is carried out in the Cadence Analog Design Environment using GPDK 180 nm CMOS process.
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