ABSTRACT
Alternative energy alternatives to traditional energy sources like coal and fossil fuels include solar PV and wind energy conversion systems. The solar and wind energy conversion system's maximum power may be obtained by activating the converters. There are several MPPT (Maximum Power Point Tracking) regulating methods for solar and wind energy conversion systems. For solar PV energy conversion systems, this study suggests two MPPT controlling techniques: Covid-19 MPPT and FLC-based MPPT. The two MPPT methods that are suggested are put into practise using MATLAB. The first Covid-19 approach that has been developed combines aspects of hill climbing and progressive conductance methods. Calculate the direction of the perturbation for the PV modules' operation using the incremental conductance approach. The method of ascending hills is straightforward and involves fewer variables. When dI/dV equals the incremental conductance, the Maximum Power Point (MPP) is attained using the incremental conductance approach. In the hill climbing approach, the MPP is determined by comparing the power in the present and the past. Both incremental conductance and change of power are taken into account in the proposed Covid-19 MPPT regulating approach to obtain the MPP. With this hybrid approach, solar PV generates the most electricity possible under all conditions of temperature and irradiance. As a result, the planned Covid-19 technique moves forward as intended and swiftly reaches the MPP.Copyright © 2022, Anka Publishers. All rights reserved.
ABSTRACT
This article presents the development of a ventilator and its control algorithm. The main feature of the developed ventilator is compressed by a pneumatic drive. The control algorithm is based on the adaptive fuzzy inference system (ANFIS), which integrates the principles of fuzzy logic. The paper also presents a simulation model to test the designed control approach. The results of the experiment provide verification of the developed control system. The novelty of the article is, on the one hand, the implementation of the ANFIS controller, pressure control, with a description of the training process. On the other hand, in the article presented a draft ventilator with a detailed description of the hardware and control system. © 2023, The Author(s), under exclusive license to Springer Nature Switzerland AG.
ABSTRACT
This paper presents an efficient interval type 2 fuzzy (IT2F) based on a single neuron proportional–integral–derivative (PID), also known as IT2FSNPID controller. The main purpose of the proposed control technique is to track the motion profile of the brushless DC (BLDC) motor. Also, a comparative study was investigated fuzzy type 1 (FT1) and IT2F. IT2F can treat the uncertainty and nonlinearity of the BLDC motor drive electric system in contrast to FT1. The parameters of each control technique were obtained using a new COVID-19 optimization algorithm according to an objective function. Moreover, several tests had been performed to ensure the ability of fuzzy type to absorb the system uncertainty and nonlinearity. All controllers were utilized to operate the BLDC motor sudden change in load and continuous load. The simulation results show that the IT2FSNPID can improve the dynamic response of linear and nonlinear of the same BLDC motor and accommodate the system uncertainty significantly. © 2023, Institute of Advanced Engineering and Science. All rights reserved.