PI Fuzzy Logic Research Articles

Load Frequency Control in Four Area Power Systems Using Fuzzy Logic PI Controller

This paper presents a load frequency control in fourarea power systems using fuzzy gain scheduling of PI controlleris realized. The system simulation is realized by using Matlab/Simulink software. System dynamic performance is observed forconventional PI, fuzzy PI and fuzzy logic controllers.

Load Frequency Control in Four Area Power Systems Using Fuzzy Logic PI Controller

Load Frequency Control in Four Area Power Systems Using Fuzzy Logic PI Controller

PID and Novel Approach of PI Fuzzy Logic Controllers for Active Surge in Centrifugal Compressor

The operating range of aerodynamic compressors is usually limited by a phenomenon known as surge. Active surge control has showed the ability to extend the operating range significantly. This study presents a solution to this problem based on classical PID regulator and a new PI fuzzy logic approach with three lines of protection. The fuzzy controller is designed to avoid the surge instability on a given compressor model. Simulation studies show promising results at different operating points compared to the results obtained using PID controller.

Three-phase three-level grid interactive inverter with fuzzy logic based maximum power point tracking controller

In this study, three-phase single stage grid interactive inverter with maximum power point tracking capability is proposed. The proposed system consists of three-level neutral point clamped inverter, LCL output filter, line frequency transformer, PI current regulator and fuzzy logic based maximum power point tracking algorithm. Rate of change of photovoltaic power and voltage are defined as input variables, and the change in reference current is defined as output variable for the fuzzy logic controller. The proposed maximum power point tracking algorithm is robust with respect to parameter variations of photovoltaic system with adaptive feature of fuzzy logic controller. Maximum power point tracking algorithm determines the inverter current reference depending on the system conditions such as irradiation level and temperature, and PI regulator shapes the inverter output current. Two capacitors’ voltages of neutral point clamped inverter are also balanced. Simulation and experimental results show that the proposed inverter system has fast transient response and can track the maximum power point of PV system even if atmospheric condition changes rapidly. Also, the inverter output current is in sinusoidal waveform and in phase with line frequency and phase. In addition, total harmonic distortion level of the inverter output current is in the limits of international standards (<5%) and efficiencies of maximum power point tracking algorithm and total system are measured as 98.78% and 93.12%, respectively.

Load Frequency Control of Interconnected Hydro-Thermal Power System Using Conventional PI and Fuzzy Logic Controller

In industry or any area increasing load is a vast problem for power generation plants due to increase in demand for power. So making balance between generation and demand is the operating principle of load frequency control (LFC). The reliable operation of a large interconnected power system necessarily requires an Automatic Generation Control (AGC). The objective of AGC is to regulate the power output of Generators within a specified area in response to change in the system frequency, tie line power or relation of the two to each other, so as to maintain the scheduled system frequency and power interchange in the other are within the prescribed limits. This paper presents the use of conventional PI controller and artificial intelligence to study the load frequency control of interconnected power system. In the proposed scheme, a control methodology is developed using conventional PI controller and Fuzzy Logic controller (FLC) for interconnected hydro-thermal power system. The control strategies guarantees that the steady state error of frequencies and inadvertent interchange of tie-lines power are maintained in a given tolerance limitations. The performances of the controllers are simulated using MATLAB/SIMULINK package. A comparison of Fuzzy controller and PI controller based approaches shows the superiority of proposed Fuzzy logic controller for step change in loading conditions. The simulation results also tabulated as a comparative performance in view of settling time and peak over shoot.

Brushless Dc Motor Speed Control Using Proportional-Integral And Fuzzy Controller

This paper demonstrates the detailed analysis of Proportional-Integral (PI) controller and Fuzzy Logic controller for speed control of a Permanent Magnet Brushless DC (PMBLDC) motor for different speed commands and varying load torque conditions. Implementation of PI controller in closed loop conditions is done. Analysis of classical tuning methods to obtain best PI parameters for speed control is calculated. Fuzzy controller is also implemented for the same and the simulation results obtained for both PI and Fuzzy control in MATLAB/Simulink are compared. PI controllers have poor response due to overshoot, more drop in speed and oscillations. Intelligent control like Fuzzy Logic is gaining momentum as it can overcome these disadvantages. Microcontroller based controller implementation is tested using a virtual motor and the results or PI controller are validated using software results. Keywords- BLDC, Fuzzy logic controller, PI controller, PWM and virtual motor

A Novel Sensor Less Control of Induction Motor Based on Fuzzy Sliding-Mode Structure

A novel fuzzy sliding-mode structure has been proposed for Extend Kalman Filter (EKF) based on sensorless control of an induction motor in this paper. Fuzzy sliding-mode structure includes two nonlinear controllers, one of which is sliding mode type and the other is PI-fuzzy logic based controller. The new structure has two advantages: sliding-mode controller increasing system stability and PI-like fuzzy logic based controller reducing the chattering in permanent state. The scheme has been implemented and experimentally validated.

Thrust Control of Small Turbojet Engines Using Fuzzy Logic: Design and Experimental Validation

The aim of this paper is to propose an effective technique which employs a proportional-integral Fuzzy logic controller for the thrust regulation of small scale turbojet engines, capable of ensuring high performance in terms of response speed, precision and stability. Fuzzy rules have been chosen by logical deduction and some specific parameters of the closed loop control have been optimized using a numerical simulator, so as to achieve rapidity and stability of response, as well as absence of overshoots. The proposed Fuzzy logic controller has been tested on the Pegasus MK3 microturbine: the high response speed and precision of the proposed thrust control, revealed by the simulations, have been confirmed by several experimental tests with step response. Its stability has been demonstrated by means of the frequency response analysis of the system. The proposed thrust control technique has general validity and can be applied to any small-scale turbojet engine, as well as to microturbines for electricity production, provided that thrust being substituted with the net mechanical power.

A new control strategy for a stand-alone self-excited induction generator driven by a variable speed wind turbine

This paper presents a new control strategy of a stand-alone self-excited induction generator (SEIG) driven by a variable speed wind turbine. The proposed system consists of a three phase squirrel-cage induction machine connected to a wind turbine through a step-up gear box. A current controlled voltage source inverter (CC–VSI) with an electronic load controller (ELC) is connected in parallel with the main consumer load to the AC terminals of the induction machine. The proposed control strategy is based on fuzzy logic control principles which enhance the dynamic performance of the proposed system. Three fuzzy logic PI controllers and one hysteresis current controller (HCC) are used to extract the maximum available energy from the wind turbine as well as to regulate the generator terminal voltage simultaneously against wind speed and main load variations. However, in order to extract the maximum available energy from the turbine over a wide range of wind speeds, the captured energy is limited due to electrical constraints. Therefore the control strategy proposed three modes of control operation. The steady state characteristics of the proposed system are obtained and examined in order to design the required control parameters. The proposed system is modeled and simulated using Matlab/Simulink software program to examine the dynamic characteristics of the system with proposed control strategy. Dynamic simulation results demonstrate the effectiveness of the proposed control strategy.

Optimal Speed Control of Hybrid Electric Vehicles

The main objective of this paper is to control the speed of Nonlinear Hybrid Electric Vehicle (HEV) by controlling the throttle position. Various control techniques such as well known Proportional-Integral-Derivative (PID) controller in conjunction with state feedback controller (SFC) such as Pole Placement Technique (PPT), Observer Based Controller (OBC) and Linear Quadratic Regulator (LQR) Controller are designed. Some Intelligent control techniques e.g. fuzzy logic PD, Fuzzy logic PI along with Adaptive Controller such as Self Organizing Controller (SOC) is also designed. The design objective in this research paper is to provide smooth throttle movement, zero steady-state speed error, and to maintain a Selected Vehicle (SV) speed. A comparative study is carried out in order to identify the superiority of optimal control technique so as to get improved fuel economy, reduced pollution, improved driving safety and reduced manufacturing costs.

Integral control system of indoor environment in continuously occupied spaces

Abstract The paper describes detailed structure of the integral automated regulation system for the control of indoor environment (ICsIE) which harmonises occupant comfort requirements and principles of bioclimatic approach. The ICsIE regulates indoor illumination, thermal conditions and air quality. The control unit of the system is designed as a hybrid cascade system incorporating fuzzy logic and conventional PI controllers. Regulation is executed with the use of sensors, which monitor the environmental conditions and adherent actuators. The ICsIE is currently installed in an occupied office in the building of the Faculty of Civil and Geodetic Engineering, University of Ljubljana, Slovenia. During the operation the ICsIE was able to synchronise the aspects of thermal, illuminance and ventilation control and maintain indoor environmental conditions in the desired range of the set-point values. From the occupant point of view the ICsIE performed adequately, as manual interventions into the functioning of the system were rare.

Optimal PI-fuzzy logic controller of glucose concentration using genetic algorithm

In this paper, an optimal PI-fuzzy controller to regulate plasma glucose in Type1 diabetic patients is introduced. This controller is designed to mimic the functionality of β -cell in pancreas. Complete lack of insulin resulting from β -cell deficien

A robust self-tuning fuzzy PI scheme for DTC induction motor drive

In this paper, application of self-tuning fuzzy PI scheme (STPIFLC) for Direct Torque Controlled Induction Motor (DTC IM) drive is proposed. In the proposed approach, the output scaling factor (SF) is adjusted online by fuzzy rules according to the current trend of the controlled process. The rule base for tuning the output SF is defined on error (e) and change of error (?e) of the controlled variable using triangular equally overlapped membership functions (MFs). The performance of the proposed self-tuning fuzzy PI controller is compared with the corresponding fuzzy logic controller and PI controller. The performance index based on speed error is assigned to provide a numerical comparison among different controllers. Simulation results show that the proposed STPIFLC for DTC IM drive gives remarkably improved performance and high robustness compared with those obtained by the application of a conventional controller (PI).

Optimal gain tuning of PI speed controller in induction motor drives using particle swarm optimization

This article presents particle swarm optimization (PSO)-based optimal gain tuning of proportional integral (PI) speed controller in an induction motor (IM) drive (30 hp) with mine hoist load diagram. Optimization considers the load and speed variations, and provides appropriate gains to the speed controller to obtain good dynamic performance of the motor. IM performance is checked with the optimal gains through the simulation studies in MATLAB/SIMULINK environment. Results are compared with hand tuning (fixed gains) and fuzzy logic (FL) speed controller. Hybrid of FL and PSO-based PI controller for the speed control of given motor is also performed to eliminate the drawbacks of PI controller (overshoot and undershoot) and FL controller (steady-state error). From the simulation studies, hybrid controller produces better performance in terms of rise time, overshoot and settling time.

Performance Analysis of Double Inverter Fed Wound Rotor Induction Motor using Fuzzy and PI Controller

This paper proposes some design approaches combining PI control technique and fuzzy logic. This system has been designed to have two controllers, one Fuzzy based controller for stator and another one PID based for rotor. Such a mixed implementation leads to a more effective control design objectives such as steady state and transient characteristics of the closed loop system. Fuzzy logic is integrated to overcome the problems with uncertainties in the motor parameters. Induction motors are characterized by complex, highly non%linear and time varying dynamics. The advent of vector control techniques has partially solved induction motor control problems. Also they are sensitive to drive parameter variations such as the rotor time constant and an incorrect flux measurement or estimation at low speeds. If the conventional controllers are used the performance may deteriorate. Fuzzy logic based controller deal such variations more effectively. A simulation study of Fuzzy/PID based Stator/Rotor vector control is presented. The effectiveness of these controllers is demonstrated for different operating conditions of the drive system.

A type-2 fuzzy logic controller design for buck and boost DC–DC converters

Conventional (type-1) fuzzy logic controllers have been commonly used in various power converter applications. Generally, in these controllers, the experience and knowledge of human experts are needed to decide parameters associated with the rule base and membership functions. The rule base and the membership function parameters may often mean different things to different experts. This may cause rule uncertainty problems. Consequently, the performance of the controlled system, which is controlled with type-1 fuzzy logic controller, is undesirably affected. In this study, a type-2 fuzzy logic controller is proposed for the control of buck and boost DC–DC converters. To examine and analysis the effects of the proposed controller on the system performance, both converters are also controlled using the PI controller and conventional fuzzy logic controller. The settling time, the overshoot, the steady state error and the transient response of the converters under the load and input voltage changes are used as the performance criteria for the evaluation of the controller performance. Simulation results show that buck and boost converters controlled by type-2 fuzzy logic controller have better performance than the buck and boost converters controlled by type-1 fuzzy logic controller and PI controller.

Automatic generation control of TCPS based hydrothermal system under open market scenario: A fuzzy logic approach

This paper presents the analysis of automatic generation control of a two-area interconnected thyristor controlled phase shifter based hydrothermal system in the continuous mode using fuzzy logic controller under open market scenario. Open transmission access and the evolving of more socialized companies for generation, transmission and distribution affects the formulation of AGC problem. So the traditional AGC two-area system is modified to take into account the effect of bilateral contracts on the dynamics. It is possible to stabilize the system frequency and tie-power oscillations by controlling the phase angle of TCPS which is expected to provide a new ancillary service for the future power systems. A control strategy using TCPS is proposed to provide active control of system frequency. Further dynamic responses for small perturbation considering fuzzy logic controller and PI controller (dual mode controller) have been observed and the superior performance of fuzzy logic controller has been reported analytically and also through simulation.

Recent Patents on Induction Motor And DTFC Based Fuzzy Logic

This paper presents the sensorless speed control performance of an improved direct torque and flux control (DTFC) for induction motor. The proposed DTFC is based on fuzzy logic technique to replace switching table and hysteresis regulator, in order to reduce torque and flux ripples in comparison with the conventional DTFC. We estimated the rotor speed by using the Model Reference Adaptive Systems (MRAS). Several strategies of speed control are presented and tested: Proportional Integral regulator (PI) anti-windup, PI with and without saturation and PI fuzzy logic. The validity of proposed technique is verified by simulation results using Matlab/Simulink. In this article recent patented strategies are also discussed. Keywords: Induction motor, DTFC, MRAS, sensorless control, fuzzy logic

Online Identification and Control of pH in a Neutralization System

pH control of a neutralization system for wastewater, where the input waste stream has variable properties in terms of acid concentration and flow rate, is investigated with different control algorithms utilizing an online identification technique. Performances of the designed controllers (model predictive (MPC), fuzzy logic (FLC), and conventional PI controller) are tested and compared mainly for disturbance rejection, set-point tracking, and robustness issues theoretically and experimentally on a laboratory-scale pH neutralization system. Additional experiments are done with original wastewater samples taken from an electronic-circuits manufacturing plant. All controllers' performances are found to be close, while adaptive MPC can be considered better compared to others due its constraint handling capabilities and FLC can be preferred because it can be used without an identification step.

Speed control of SR motor by self-tuning fuzzy PI controller with artificial neural network

In this work, the dynamic model, flux-current-rotor position and torque-current-rotor position values of the switched reluctance motor (SRM) are obtained in MATLAB/Simulink. Motor control speed is achieved by self-tuning fuzzy PI (Proportional Integral) controller with artificial neural network tuning (NSTFPI). Performance of NSTFPI controller is compared with performance of fuzzy logic (FL) and fuzzy logic PI (FLPI) controllers in respect of rise time, settling time, overshoot and steady state error.