Papers by Keyword: Fuzzy Logic Control

Abstract: Under both typical and partial shading conditions, this research seeks to assess how two maximum power point tracking (MPPT) solutions, Perturb and Observe (P&O) and fuzzy logic control (FLC), help maximize power extraction from a photovoltaic (PV) system. Applying MATLAB SIMULINK, a DC-DC converter and a PV generator were simulated to run these MPPT systems. The comparison focuses on the extracted power, the performance of each technique, and their ability to follow the global maximum power point (MPP). The simulation findings show that in standard and partial shading conditions, both P&O and fuzzy logic algorithms can effectively track the MPP. The fuzzy logic controller, however, turned out to be more accurate and efficient (≥98% efficiency vs. P&O's 97%) with minimal power oscillation, while the P&O algorithm had a faster response time.

Abstract: The application of photovoltaic (PV) system in different sectors increases dramatically since it is clean, sustainable, and easy to maintain. However, PV systems have a nonlinear voltage-current characteristic, with a distinct maximum power point (MPP), which depends on environmental factors like temperature and irradiation. Maximum power point tracking (MPPT) is crucial for PV power systems to consistently extract the maximum power from solar panels as it optimizes power output under varying conditions. In this paper, a standalone PV-powered water pumping system is designed for Bahir Dar University Health Science College. Then fuzzy sliding mode control (FSMC) is designed for MPPT. The proposed controller is simulated in MATLAB/ SIMULINK and the controller's performance for optimizing the system's power output under different environmental and load conditions is evaluated. The effectiveness of the proposed MPPT algorithm is validated by comparing its performance with fuzzy logic control (FLC) and sliding mode control (SMC). Based on the simulation result FSMC has an MPPT efficiency of 99.13% compared with 80.21% in FLC and 97.81% in SMC.

Abstract: This paper concerns with the control system design for a teleoperated endoscopic surgical manipulator system that uses PHANTOM Omni haptic device as the master and a 4-DOF parallel manipulator (2-PUU_2-PUS) as the slave. PID control algorithm was used to achieve the trajectory tracking, but the error in each actuated joint reached 0.6 mm which is not satisfactory in surgical application. The design of a control algorithm for achieving high trajectory tracking is needed. Simulation on the virtual prototype of the 4-DOF parallel manipulator has been achieved by combining MATLAB/Simulink with ADAMS. Fuzzy logic controller is designed and tested using the interface between ADAMS and MATLAB/Simulink. Signal constraint block adjusted the controller parameters for each actuated prismatic joint to eliminate the overshoot in most of position responses. The simulation results illustrate that the fuzzy logic control algorithm can achieve high trajectory tracking. Also, they show that the fuzzy controller has reduced the error by approximately 50 percent.

Abstract: A solar based air conditioning blower model of vehicle has been presented together with the development of its intelligent controller in this report. The model is dependent on its own battery that is recharged by the energy collected from solar panel system. An automatic variable speed blower is introduced into the system. Vehicle cabin temperature is controlled by varying the blower speed. The intelligent controller is embedded with fuzzy logic strategy. A control algorithm is obtained with a design of the model and the system. The results satisfied the project objectives. The system is able to run using a lead acid battery and a solar panel with power consumption of 98.4 W. The fuzzy logic controller performed well with a percentage error less than 1.64%.

Abstract: As pumps and pumping stations of oil collecting, maintaining reservoir pressure, transportation and treatment processes account for over 50 % of oil and gas enterprises estimated total cost of electricity, relevant issue is the development and application of intelligent control systems for energy efficiency of these processes. For the booster pump station as a multivariable nonlinear control object are proposed: a structure in which the function of regulating valves transferred to the pumps with frequency speed control; conceptual model with seven inputs and five outputs (adjustable) variables, which is the basis for constructing three-dimensional fuzzy controller with not-fuzzy terms to stabilize and improve the energy efficiency of oil transportation and treatment processes and minimize energy losses. In this paper we propose a control system of pumping station on the basis of multidimensional fuzzy logic controller with compensation of the mutual influence of control loops in the form of an additional system of production rules that helped to stabilize the liquid level at 2.5 m given level with an absolute error of ± 0.2 m and thus improve quality oil emulsion on the installation of oil and gas refining central collection point.

Abstract: In dual three-level converter system, the rectifier and inverter have unified problems of the neutral point potential imbalance.This paper analyzed the reasons of imbalance of neutral point potential in detail and summarized the relationship between vector status and four-quadrant status of three-level converters.Then a method based on fuzzy logic control (FLC) is proposed,which could be automatically adjust the balance factor.Combined the balance factor with the status of the converter the duration of positive and negative small vectors action could be obtained.Finally the balance of the neutral point potential is achieved.This method could be generally used on rectifier and inverter.At last, the simulation was done on both inverter and rectifier side.The results verified the feasibility of the proposed method.

Abstract: In this paper fuzzy logic based load frequency control (LFC) of two area power system in deregulated environment was studied. A two area system is considered in which all areas are interconnected by normal AC tie-lines. In the proposed system the effects of bilateral contracts between DISCOs and GENCOs are also considered. The performance of the fuzzy logic controller is tested on a deregulated two area load frequency control system for different operating conditions using MATLAB Simulink tool.

Abstract: The purpose of this research is to design and construct a marine self-balancing table with two-axis motion control system. This table has two degrees of freedom, is fixed in an ocean-going ship and can be self-balanced when the ship is moving in the sea. Control of the table is based on fuzzy logic control. A prototype of the marine self-balancing table is also manufactured in this research. Experimental results show that this table can be self-balanced with a tolerance of 1⁰.

Abstract: Due to the lack of cruising ability in HEV(Hybrid Electric Vehicle), along with concerns about environmental issues, a hybrid power source built from a battery and an ultracapacitor is used as vehicular power source and is charged during braking processes. Based on the rule of “the lower ultracapacitor voltage, the less battery charging; the higher ultracapacitor voltage, the more battery charging”, this paper adopts a fuzzy logic control strategy to supervise the braking energy. Simulation results obtained using MATLAB/SIMULINK indicate that this method can effectively manage the energy distribution during regenerative braking processes and extend driving distance. Furthermore, the present approach provides an improvement in fuel economy and reduces pollutant emissions.

Abstract: This paper presents a study and investigation of an improvement of boiler efficiency with an automatic control of air quantity into a combustion chamber. A fire tube boiler with a fixed gate and screw conveyor for feeding fuel was used to test the automatic control system, and a sub-bituminous was used as a fuel for this study. The increase in boiler efficiency was based on controlling amount of air quantity for fuel combustion before entering to the combustion chamber using fuzzy logic control algorithm. Automatic combustion control was achieved by measuring the amount of Oxygen gas (O₂) from flue gas stack. From the experimental results, it was indicated that the automatic control system can control the average amount of O₂ in flue gas at 11.09% when the O₂ in the flue gas was set at 10%. The boiler efficiency was increased by 4.34%, and the energy consumption was reduced to have a fuel saving of 195.88 ton/year.