Fuzzy Logic Control Technique Research Articles

Performance Review of Fuzzy Logic Based Controllers Employed in Brushless DC Motor

The paper presents a performance review of Fuzzy Logic Control technique when applied to Brushless DC motor (BLDC). These type of motors are non-linear in nature therefore classical PID control scheme fail to achieve desired steady state performance. To achieve the control objective, Fuzzy Logic Control scheme in arrangement with various other control techniques were investigated by several researcher. These techniques differ in various aspect such as control architecture, controller tuning method, dynamic and steady state performance. The paper presents a comprehensive performance review of such Fuzzy Logic Based Controllers.

Fuzzy Control of a Robotic Finger Actuated by Shape Memory Alloy Wires

This paper presents the development of a robotic finger driven by nonconventional actuators, consisting of thin shape memory alloy (SMA) wires. In order to monitor and control the angles formed by each phalanx, a specific system for capturing and interpreting digital images was implemented. By image processing, this system is capable to determine the angles without the need for installation of phalanx rotation sensors, leading to weight and volume reduction of the prototype. For this artificial vision system, a simple camera with a fuzzy logic control technique was used, which was very effective in monitoring the position of the robotic finger.

VHDL Based Maximum Power Point Tracking of Photovoltaic Using Fuzzy Logic Control

It is important to have an efficient maximum power point tracking (MPPT) technique to increase the<em> </em>photovoltaic (PV) generation system output efficiency. This paper presents a design of MPPT techniques for<em> </em>PV module to increase its efficiency. Perturb and Observe method (P&O), incremental conductance method (IC), and Fuzzy logic controller (FLC) techniques are designed to be used for MPPT. Also FLC is built using<em> </em>MATLAB/ SIMULINK and compared with the FLC toolbox existed in the MATLAB library. FLC does not<em> </em>need knowledge of the exact model of the system so it is easy to implement. A comparison between different<em> </em>techniques shows the effectiveness of the fuzzy logic controller techniques. Finally, the proposed FLC is<em> </em>built in very high speed integrated circuit description language (VHDL). The simulation results obtained with<em> </em>ISE Design Suite 14.6 software show a satisfactory performance with a good agreement compared to obtained values from MATLAB/SIMULINK. The good tracking efficiency and rapid response to environmental parameters changes are adopted by the simulation results.

Robust Fuzzy Control for 2-DOF Manipulator System

Robot manipulators have become increasingly important in the field of automation. So modelling and control of robots in automation will be very important. This paper presents a study of robust control approach employing fuzzy logic control technique for two degree of freedom (2-DOF) manipulator robot. A learning control system is designed so that its “learning mechanism” has the ability to improve the performance of the closed-loop system by generating command inputs to the plant and utilizing feedback information from the plant. It is well known that robotic manipulators are highly nonlinear coupling dynamic systems. A fuzzy logic rule base is designed, using the knowledge obtained from the operator. Simulation is performed to demonstrate the effectiveness of control strategy. Furthermore, the parameters of the controllers were optimized using MATLAB and simulations' result reveals that control scheme is working satisfactorily.

Fuzzy Model Predictive Direct Torque Control of IPMSMs for Electric Vehicle Applications

This paper proposes a fuzzy model predictive direct torque control (FMP-DTC) strategy of interior permanent magnet synchronous motors (IPMSMs) for electric vehicle (EV) applications. The fuzzy logic control technique incorporated into the proposed FMP-DTC scheme dynamically determines the appropriate values of the weighting factors, and then generates the optimal switching states that minimize the electromagnetic torque and stator flux errors. Unlike the conventional model predictive (MP)-DTC strategy, the optimal switching states of the proposed FMP-DTC are selected without retuning the weighting factors. It means that they are updated depending on the specific operating conditions. Therefore, the proposed FMP-DTC is effective in various operating conditions that make it suitable for the EV-traction operating environment. Hence, the proposed FMP-DTC method has a simple control structure and can explicitly handle the system constraints. The performance evaluation is carried out via both MATLAB/Simulink and a prototype IPMSM test-bed with a TMS320F28335 digital signal processor (DSP). Comparative simulation and experimental results present the evidence of the performance improvements based on the proposed FMP-DTC strategy compared with the conventional MP-DTC strategy by indicating a fast transient torque response, low ripples, and an accurate speed tracking even under rapid climbing or emergency braking situations.

TCSC based automatic generation control of deregulated power system using quasi-oppositional harmony search algorithm

In present aspect, automatic generation control (AGC) of deregulated power system with thyristor controlled series compensator (TCSC) device is investigated. The objective is to discuss bilateral power transaction issue with the TCSC effect. A deregulated two-area power system model having two thermal units in each control area is considered for this act. A quasi-oppositional harmony search (QOHS) algorithm is being applied for the constrained optimization problem. Three cases, commonly studied in deregulation, are discussed for the effectiveness of the proposed technique. Further, sensitivity analysis is studied by varying the test system parameters up to ±25% from their rated values. The obtained simulation plots are analytically discussed with the calculation of oscillatory modes, transient details and the studied performance indices. Sugeno fuzzy logic control technique is also investigated to the studied test system. The simulation results show that the proposed QOHS based TCSC controller is quite effective in deregulated environment.

Implementation of modified incremental conductance and fuzzy logic MPPT techniques using MCUK converter under various environmental conditions

Incremental Conductance (IC) technique is a cheap, and easy algorithm to implement for Maximum Power Point Tracking (MPPT). However, the IC technique usually takes time and suffers some delay to approach the MPP if the voltage is not near to the MPP or when subjected to rapid change in irradiance. In this paper, IC technique was implemented and compared to the modified Incremental Conductance technique (MIC) under various environmental conditions such as standard test conditions (STC) and partial shading conditions. Also the MIC method was compared to a Fuzzy Logic Controller (FLC) MPPT technique in order to evaluate the best and the accurate controller for the MPPT for different weather conditions. Results show that using FLC and MIC techniques are efficient for MPPT and may increase the PV system stability.

Local model networks based mixed-sensitivity H-infinity control of CE-150 helicopters

In this paper, a local model network H-infinity control is proposed for CE-150 helicopter stabilization. The proposed strategy capitalizes on recent developments on H-infinity control and its promising results in robust stabilization of plants under unstructured uncertainties. CE-150 helicopters are known for their varying operating conditions along with external disturbances. Therefore, local model networks are introduced for their adaptive feature and since they provide a powerful combination of fuzzy logic and conventional linear control techniques to control nonlinear systems without the added computational burden of soft-computing techniques. Using the fact that the system can be linearized at different operating points, a mixed sensitivity H-infinity controller is designed for the linearized system, and combined within a network to make transitions between them. The proposed control structure ensures robustness, decoupling of the system dynamics while achieving good performance. A comparison is carried-out against the well-known proportional-integral-derivative (PID) control technique. Results are presented to illustrate the controller’s performance in various operating conditions.

Design of Type-2 Fuzzy Logic Controller for Fluid Catalytic Cracking Unit

Modelling and controlling of fluid catalytic cracking unit (FCCU) is a challenging problem since it is a highly nonlinear and interacting process. Model of FCCU that describes the dynamic behaviour of reactor and regenerator has been developed by considering energy and material balance equations. Fuzzy logic control technique in the field of intelligent control has been used in this paper since it handles uncertainty very well. In this work, centralised Mamdani types T1-FLC and T2-FLC have been designed for FCCU to control the reactor and regenerator temperature (RT). The closed-loop simulation study for servo and servo with regulatory performance has been carried out for the two controllers and the performances have been analysed. The comparative study of these two control schemes reveals that the type-2 FLC gives better performance than type-1 FLC.

Energy Management Strategy of a PV/Fuel Cell/Supercapacitor Hybrid Source Feeding an off-Grid Pumping Station

This work aims to develop an accurate energy management strategy for a hybrid renewable energy system feeding a pumping station. A developed model under Simulink environment is used to compare the performance of the pumping system when it is only fed by a photovoltaic generator, by a hybrid photovoltaic and fuel cell system and finally by a hybrid photovoltaic, fuel cell and a supercapacitor system. The developed control strategy is based on Fuzzy Logic control technique. Several simulations in different dramatic scenarios of working conditions show that the developed control strategy brought major enhancements in system performance and that the use of the supercapacitor makes economic profits by reducing the fuel cell production during critical solar irradiation periods.

Fuzzy Logic Energy Management Strategy of a Hybrid Renewable Energy System Feeding a Typical Tunisian House

This paper proposes an energy management strategy for hybrid power system HPS which is composed of a photovoltaic generator, wind turbine, fuel cell generator and NaS battery storage device, feeding a type house. This strategy is based on Fuzzy Logic Control technique. The hybrid power system is sized to provide the energy demand of the inhabitants of the house and if there is an extra power generation, it would be sold to the grid. Using Simulink, we develop the different scenarios in order to use the fuel cell or battery during critical periods. The methodology developed was applied under the climatic conditions (wind speed, solar irradiation and temperature) measured at a site located in the northeast of Tunisia.

Electric Vehicle Longitudinal Stability Control Based on a New Multimachine Nonlinear Model Predictive Direct Torque Control

In order to improve the driving performance and the stability of electric vehicles (EVs), a new multimachine robust control, which realizes the acceleration slip regulation (ASR) and antilock braking system (ABS) functions, based on nonlinear model predictive (NMP) direct torque control (DTC), is proposed for four permanent magnet synchronous in-wheel motors. The in-wheel motor provides more possibilities of wheel control. One of its advantages is that it has low response time and almost instantaneous torque generation. Moreover, it can be independently controlled, enhancing the limits of vehicular control. For an EV equipped with four in-wheel electric motors, an advanced control may be envisaged. Taking advantage of the fast and accurate torque of in-wheel electric motors which is directly transmitted to the wheels, a new approach for longitudinal control realized by ASR and ABS is presented in this paper. In order to achieve a high-performance torque control for EVs, the NMP-DTC strategy is proposed. It uses the fuzzy logic control technique that determines online the accurate values of the weighting factors and generates the optimal switching states that optimize the EV drives’ decision. The simulation results built in Matlab/Simulink indicate that the EV can achieve high-performance vehicle longitudinal stability control.

Improving the Control Strategy of a Standalone PV Pumping System by Fuzzy Logic Technique

This work aims to develop an accurate model of an existing Photovoltaic Pumping System (PvPS) which is composed of an Ebara Pra-0.50T Asynchronous Moto-Pump (AMP) fed by Kaneka GSA-60 photovoltaic panels via a Moeller DV-51 speed drive. The developed model is then used to compare the performance of the system with its original control strategy based on classical indirect vector control strategy using PI speed controller and the proposed new control strategy based on Fuzzy Logic control technique for speed control and MPPT system. The obtained results of comparative simulations, induced in different dramatic variation of working conditions, show that the developed control strategy brought major enhancements in system performance.

Greenhouse Environmental Control Using Optimized, Modeled and Simulated Fuzzy Logic Controller Technique in MATLAB SIMULINK

Greenhouse Environmental Control Using Optimized, Modeled and Simulated Fuzzy Logic Controller Technique in MATLAB SIMULINK

DC-Link Capacitor Voltage Regulation for Three-Phase Three-Level Inverter-Based Shunt Active Power Filter with Inverted Error Deviation Control

A new control technique known as inverted error deviation (IED) control is incorporated into the main DC-link capacitor voltage regulation algorithm of a three-level neutral-point diode clamped (NPC) inverter-based shunt active power filter (SAPF) to enhance its performance in overall DC-link voltage regulation so as to improve its harmonics mitigation performances. In the SAPF controller, DC-link capacitor voltage regulation algorithms with either the proportional-integral (PI) or fuzzy logic control (FLC) technique have played a significant role in maintaining a constant DC-link voltage across the DC-link capacitors. However, both techniques are mostly operated based on a direct voltage error manipulation approach which is insufficient to address the severe DC-link voltage deviation that occurs during dynamic-state conditions. As a result, the conventional algorithms perform poorly with large overshoot, undershoot, and slow response time. Therefore, the IED control technique is proposed to precisely address the DC-link voltage deviation. To validate effectiveness and feasibility of the proposed algorithm, simulation work in MATLAB-Simulink and experimental implementation utilizing a TMS320F28335 Digital Signal Processor (DSP) are performed. Moreover, conventional algorithms with PI and FLC techniques are tested too for comparison purposes. Both simulation and experimental results are presented, confirming the improvement achieved by the proposed algorithm in terms of accuracy and dynamic response in comparison to the conventional algorithms.

Contribution to the Control of the Heliostat Motor of a Solar Tower Power Plant Using Intelligence Controller

This paper describes the use of an adaptive controller (F-PI) to control a DC motor for the orientation of a heliostat in a solar tower power plant using a fuzzy logic controller technique using Matlab/Simulink. In addition, this work aims to identify the strengths and weaknesses of each of the two pilots for the fuzzy logic controller and adaptive method (F-PI). The system performance is evaluated by comparing it with a conventional system of PI control. The simulation and experimental results showed the goodness of the proposed method.

Effective MPPT technique and robust power control of the PMSG wind turbine

Wind generator performance improvement requires sophisticated and robust control techniques to overcome various constraints and achieve optimal aerodynamic energy conversion. Because of the continuously changing nature of the wind, the output power of a wind energy conversion system (WECS) can be maximized if the wind rotor is driven at an optimal rotational speed for a particular wind speed. This is achieved with a maximum power point tracking (MPPT) controller. Over the years, a variety of MPPT studies have been made, but very few provide guidelines to single out the most suited MPPT technique. In this paper, a comprehensive comparison of the four most used schemes has been made in relation to a permanent magnet synchronous generator (PMSG) wind turbine system. These techniques can be classified into various categories. The obtained results show clearly the superiority of the fuzzy logic control (FLC) technique. Using this MPPT approach, the generated power by the turbine is considered to be, in terms of power control, an auxiliary source feeding a grid. To achieve smooth regulation of the active and reactive power exchange between the PMSG and the grid, direct power control, using space vector modulation DPC‐SVM strategy combined with sliding mode control (SMC) is applied in the grid‐side converter. Simulation results show the efficiency and reliability of the control strategy proposed in this paper. © 2015 Institute of Electrical Engineers of Japan. Published by John Wiley & Sons, Inc.

Performance of smart maximum power point tracker under partial shading conditions of photovoltaic systems

Partial shading on photovoltaic (PV) modules reduces the generated power of the PV system than the maximum power generated from each module separately. The shaded PV module acts as a load to unshaded ones which can lead to hot-spot. To alleviate the effect of partial shading, bypass diodes should be connected across each PV modules. Connecting several PV modules together produces multiple peaks (one global peak (GP) and multiple local peaks (LPs)) on partial shading conditions. Maximum power point tracker conventional techniques are designed to follow the GP but they stuck around LPs such as fuzzy logic controller (FLC). In this paper, modified particle swarm optimization (MPSO) using genetic algorism has been used to follow the GP under any operating conditions. MPSO has been studied and compared with the FLC technique to show the superiority of this technique under all operating conditions. Co-simulation between Matlab/Simulink and PSIM has been used to model the PV system under partial shading conditions. The simulation results show that the MPSO technique is more effective than FLC in following the GP. The generated power increases considerably with the MPSO than the FLC technique in shading conditions.

PARAMETER CONTROLLING OF BOILER IN POWER PLANTS USING FUZZY LOGIC CONTROLLER

Boilers are used industrially both for electric power generation and for supplying process stream in thermal power plants and its control is very important in many field applications. In some situation conventional PID control technique is being used for control purpose. These conventional controllers are not well suitable for some unusual conditions like load disturbances. Fuzzy logic control technique is being used to overcome these problems. A closed loop control system incorporating fuzzy logic has been developed for a class of industrial control systems. A unique fuzzy logic controller (FLC) structured with an efficient realization and a small rule base that can be easily implemented in existing industrial controllers. Fuzzy logic control system is much closer to human thinking and natural language than traditional control systems. This paper describes a fuzzy control technique and its implementation in boiler controls. Here a PIC microcontroller is being used where fuzzy control algorithm is implemented.

A Comparative Study between Dual Fuzzy Logic and Sliding Mode Control MPPT Techniques Applied to PV Pumping System

The aim of this paper is to present a comparison investigation of the performance characteristics of two different Maximum Power Point Tracking (MPPT) techniques applied to photovoltaic (PV) pumping system. A dual fuzzy logic control technique and slide mode control command are developed and simulated by Matlab/Simulnk environment, the comparison is done to identifying the advantages and drawbacks of each technique for different values of radiation and temperature. The studied system consists of photovoltaic panel, dc-dc boost converter, a group motor-pump, and a storage tank. Simulation results obtained show the variation of the accuracy and speed response time with variation of condition atmospheric for each method, and verify their influence in the efficiency of the PV pumping system.