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Academic literature on the topic 'FPI CONTROLLER'
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Journal articles on the topic "FPI CONTROLLER"
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Sheikh, M. R. I., R. Takahashi, and J. Tamura. "Robust Stabilizing Controllers to Automatic Generation Control for Load Frequency Control Application." Journal of Scientific Research 2, no. 2 (2010): 285–93. http://dx.doi.org/10.3329/jsr.v2i2.3063.
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Since superconducting magnetic energy storage (SMES) unit with a self-commutated converter is capable of controlling both the active and reactive powers simultaneously and quickly, increasing attention has been focused recently on power system stabilization by SMES control. This study presents the effects of novel control strategies of self-tuned fuzzy proportional integral (FPI) controller and fuzzy frequency (FF) controller associated with the automatic generation control (AGC) including SMES unit. The effects of the self-tuning configuration with FPI controller in AGC is also compared with that of FF controlled AGC on SMES control. The simulation results show that both self tuning control schemes of AGC are very effective in damping out of the oscillations caused by load disturbances and it is also seen that the FF controlled AGC with SMES perform better primary frequency control compared to FPI controlled AGC with SMES. Keywords: Load frequency control; Single area power system; FPI controller; FF controller; SMES unit. © 2010 JSR Publications. ISSN: 2070-0237 (Print); 2070-0245 (Online). All rights reserved. DOI: 10.3329/jsr.v2i2.3063 J. Sci. Res. 2 (2), 285-293 (2010)
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Alkargole, Hazim M., Abbas S. Hassan, and Raoof T. Hussein. "Analyze and Evaluate the Performance Velocity Control in DC Motor." Radioelectronics. Nanosystems. Information Technologies 12, no. 4 (2020): 507–16. http://dx.doi.org/10.17725/rensit.2020.12.507.
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A mathematical model of controlling the DC motor has been applied in this paper. There are many and different types of controllers have been used with purpose of analyzing and evaluating the performance of the of DC motor which are, Fuzzy Logic Controller (FLC), Linear Quadratic Regulator (LQR), Fuzzy Proportional Derivative (FPD) ,Proportional Integral Derivative (PID), Fuzzy Proportional Derivative with integral (FPD plus I) , and Fuzzy Proportional Integral (FPI) with membership functions of 3*3, 5*5, and 7*7 rule bases. The results show that the (FLC) controller with 5*5 rule base provides the best results among all the other controllers to design the DC motor controller.
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Alawad, Nasir Ahmed. "Comparison Performance of PI and FPI Controllers for Model Reduction of Binary Distillation Column Plant." Brilliant Engineering 2, no. 1 (2020): 25–29. http://dx.doi.org/10.36937/ben.2021.001.005.
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Distillation is the separation strategy in the oil and compound businesses for cleansing of conclusive items. This paper deals with the reduced dynamic model and control of the distillation tower by applying a multi-loop control framework in Matlab/Simulink for a double blend. The structure objective considered is to guarantee that the top item, the base item, the reflux rate and the reboiler rate stray inside their recommended limits forever and for all the aggravations. This paper proposes an optimal tuning method for fractional Proportional-Integral controller (FPI). The method consists of minimizing Integral Absolute Error (IAE) performance index criterion. Acceptable controller (FPI) is acquired via looking in the space of plan boundaries (Kp,Ki). An example of application (distillation column) plant is presented to evaluate the proposed method. A comparison with classical PI controller and optimal PI shows that the system under fractional state is robust in terms of transient specifications, maximum overshot, settling and rise times. The simulation results shows that more than (21%) improvement for reducing the max-overshot and(65%)improvement for increasing response speed for fractional PI compared with classical PI.MATLAB simulation toolbox is used to show the effectives of the proposed method.
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Ko, Jae-Sub, Jun-Ho Huh, and Jong-Chan Kim. "Improvement of Energy Efficiency and Control Performance of Cooling System Fan Applied to Industry 4.0 Data Center." Electronics 8, no. 5 (2019): 582. http://dx.doi.org/10.3390/electronics8050582.
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This paper proposes a control method to improve the energy efficiency and performance of cooling fans used for cooling. In Industry 4.0, a large number of digital data are used, and a large number of data centers are created to handle these data. These data centers consist of information technology (IT) equipment, power systems, and cooling systems. The cooling system is essential to prevent failure and malfunction of the IT equipment, which consumes a considerable amount of energy. This paper proposes a method to reduce the energy used in such cooling systems and to improve the temperature control performance. This paper proposes an fuzzy proportional integral(FPI) controller that controls the input value of the proportional integral(PI) controller by the fuzzy controller according to the operation state, a VFPI (Variable Fuzzy Proportional Integral) controller that adjusts the gain value of the fuzzy controller, and a variable fuzzy proportion integration-variable limit (VFPI-VL) controller that adjusts the limit value of the fuzzy controller’s output value. These controllers control the fan applied to the cooling system and compare the energy consumed and temperature control performance. When the PI controller consumes 100% of the power consumed, the FPI is 50.5%, the VFPI controller is 44.3%, and the VFPI-VL is 32.6%. The power consumption is greatly reduced. In addition, the VFPI-VL controller is the lowest in temperature variation, which improves the energy efficiency and performance of the cooling system using a fan. The methods presented in this paper can not only be applied to fans for cooling, but also to variable speed systems for various purposes and improvement of performance and efficiency can be expected.
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Wen, Jian-Ping. "Fractional Order Nonlinear Feedback Controller Design for PMSM Drives." Mathematical Problems in Engineering 2013 (2013): 1–5. http://dx.doi.org/10.1155/2013/290310.
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Fractional order integral is introduced into active disturbance rejection controller (ADRC) to establish the structure of fractional order proportional integral controller (FPI). Fractional order ADRC (FADRC) is designed by replacing the nonlinear state error feedback control law using nonlinear function combination in ADRC with FPI, which can combine the high performance of ADRC estimating disturbances with the characteristics of fractional order calculus more really describing the physical object and spreading the stable region of the system parameters. The proposed FADRC is applied to permanent magnet synchronous motor (PMSM) speed servo system in order to improve robustness of system against the disturbances. Compared with ADRC, simulation results verify that the proposed control method has given very good robust results and fast speed tracking performance.
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Elshenawy, Mahmoud, Ashraf Fahmy, Adel Elsamahy, Shaimaa A. Kandil, and Helmy M. El Zoghby. "Optimal Power Management of Interconnected Microgrids Using Virtual Inertia Control Technique." Energies 15, no. 19 (2022): 7026. http://dx.doi.org/10.3390/en15197026.
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Two interconnected AC microgrids are proposed based on three renewable energy sources (RESs): wind, solar, and biogas. The wind turbine drives a permanent magnet synchronous generator (PMSG). A solar photovoltaic system (SPVS) with an appropriate inverter was incorporated. The biogas genset (BG) consists of a biogas engine coupled with a synchronous generator. Two interconnected AC microgrids, M1 and M2, were considered for study in this work. The microgrid M2 is connected to a diesel engine (DE) characterized by a continuous power supply. The distribution power loss of the interconnected AC microgrids comprises in line loss. The M1 and M2 losses are modeled as an objective function (OF). The power quality enhancement of the interconnected microgrids will be achieved by minimizing this OF. This research also created a unique frequency control method called virtual inertia control (VIC), which stabilizes the microgrid frequency using an optimal controller. In this paper, the following five controllers are studied: a proportional integral controller (PI), a fractional order PI controller (FOPI), a fuzzy PI controller (FPI), a fuzzy fractional order PI controller (FFOPI), and a VIC based on FFOPI controller. The five controllers were tuned using particle swarm optimization (PSO) to minimize the (OF). The main contribution of this paper is the comprehensive study of the performance of interconnected AC microgrids under step load disturbances, step changes in wind/solar input power, and eventually grid following/forming contingencies as well as the virtual inertia control of renewable energy resources used in the structure of the microgrids.
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Yan, Qixiang, Ibrahim Adamu Tasiu, Hong Chen, Yuting Zhang, Siqi Wu, and Zhigang Liu. "Design and Hardware-in-the-Loop Implementation of Fuzzy-Based Proportional-Integral Control for the Traction Line-Side Converter of a High-Speed Train." Energies 12, no. 21 (2019): 4094. http://dx.doi.org/10.3390/en12214094.
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Power quality is one of many issues affecting the traction power supply system. Prominent among the causes of poor power quality is voltage low-frequency oscillation (VLFO). In this paper, a fuzzy-based PI (FPI) controller to optimize the performance of the traction line-side converter (TLSC) and suppress the effect of VLFO is proposed. Firstly, the mathematical model of China’s railway high-speed five single-phase TLSC is developed, and then the FPI control unit is designed based on specific requirements. The fuzzy antecedent and consequence rules were generated based on the expert and previous knowledge of TLSC operation. An offline simulation of the proposed control scheme under different loads and parameters is conducted to verify the designed. To validate the model, the traction power supply system (TPS) is built on the field-programmable gate array (FPGA) real-time digital simulator (FPGA-RTDS), while the FPI control algorithm is load on modeling tech rapid control prototyping (RCP) real-time digital controller (RTDC). Hardware-in-the-loop (HIL), and offline simulation studies between current decoupling (PI) control, sliding mode control (SMC), and the proposed control method confirms in addition to excellent dynamic performance; the proposed method can successfully suppress the effect of VLFO.
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Omar, Abeer, Dalia Yousri, Hazem A. Attia, and Dalia Allam. "A new optimal control methodology for improving MPPT based on FOINC integrated with FPI controller using AHA." Electric Power Systems Research 224 (November 2023): 109742. http://dx.doi.org/10.1016/j.epsr.2023.109742.
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Rabbani, Moazzam Ali, Muhammad Bilal Qureshi, Salman A. Al Qahtani, Muhammad Mohsin Khan, and Pranavkumar Pathak. "Enhancing MPPT Performance in Partially Shaded PV Systems under Sensor Malfunctioning with Fuzzy Control." Energies 16, no. 12 (2023): 4665. http://dx.doi.org/10.3390/en16124665.
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The shift towards sustainable energy sources is gaining momentum due to their environmental cleanliness, abundant availability, and eco-friendly characteristics. Solar energy, specifically harnessed through photovoltaic (PV) systems, emerges as a clean, abundant, and environmentally friendly alternative. However, the efficacy of PV systems is subjective depending on two critical factors: irradiance and temperature. To optimize power output, maximum power point tracking (MPPT) strategies are essential, allowing operation at the system’s optimal point. In the presence of partial shading, the power–voltage curve exhibits multiple peaks, yet only one global maximum power point (GMPP) can be identified. Existing algorithms for GMPP tracking often encounter challenges, including overshooting during transient periods and chattering during steady states. This study proposes the utilization of fuzzy sliding mode controllers (FSMC) and fuzzy proportional-integral (FPI) control to enhance global MPPT reference tracking under partial shading conditions. Additionally, the system’s performance is evaluated considering potential sensor malfunctions. The proposed techniques ensure precise tracking of the reference voltage and maximum power in partial shading scenarios, facilitating rapid convergence, improved system stability during transitions, and reduced chattering during steady states. The usefulness of the proposed scheme is confirmed through the use of performance indices. FSMC has the lowest integral absolute error (IAE) of 946.94, followed closely by FPI (947.21), in comparison to the sliding mode controller (SMC) (1241.6) and perturb and observe (P&O) (2433.1). Similarly, in integral time absolute error (ITAE), FSMC (56.84) and FPI (57.06) excel over SMC (91.03) and P&O (635.50).
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Nayak, Smrutiranjan, Sanjeeb Kumar Kar, and Subhransu Sekhar Dash. "Combined fuzzy PID regulator for frequency regulation of smart grid and conventional power systems." Indonesian Journal of Electrical Engineering and Computer Science 24, no. 1 (2021): 12. http://dx.doi.org/10.11591/ijeecs.v24.i1.pp12-21.
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In continually increasing area and structure of modern power system having burden demand uncertainties, the use of knowledgeable and vigorous frequency power strategy is essential for the satisfactory functioning of the Power system. A combined fuzzy proportional-integral-derivative (CFPID) controller is suggested for frequency supervision of the power system. To optimize the controller parameters, a review of sine and cosine work adjusted improved whale optimization algorithm (SCiWOA) has been utilized. The next practical application of power-system frequency control is performed by designing a CFPID controller using the proposed SCiWOA technique for a smart grid system having inexhaustible sources like sun oriented, wind, photovoltaic and capacity gadgets like a battery, flywheel just as module electric vehicles. The first advantages of the SCiWOA tuned CFPID controller over hybrid-particle-swarm-optimization and pattern-search (hPSO-PS) adjusted fuzzy proportional-integral (FPI) controller, hybrid bacterial foraging optimization algorithm-particle swarm optimization (hBFOA-PSO) adjusted proportional-integral (PI) controller, genetic algorithm (GA) tuned proportional and integral (PI) controller, BFOA adjusted PI controller, jaya algoritm (JA) tuned PID with derivative filter (PIDN) controller and teaching learning based optimization (TLBO) tuned proportional-integral-derivative (PID) controller are demonstrated for the two-area non-reheat thermal power system. The second advantages of the SCiWOA tuned CFPID controller over artificial-bee-colony (ABC) tuned PID controller, SOSA tuned PID controller and Firefly algorithm (FA) tuned PID controller are demonstrated for two-area reheat thermal power system. It is seen that SCiWOA based CFPID controller is more effective in controlling the recurrence comparative with PID regulator.