Performance Of Fuzzy Logic Controller Research Articles

Control of Single Axis Magnetic Levitation System Using Fuzzy Logic Control

This paper presents a fuzzy logic controller design for the stabilization of magnetic levitation system (Maglev 's).Additionally, the investigation on Linear Quadratic Regulator Controller (LQRC) also mentioned here. This paper presents the difference between the performance of fuzzy logic control (FLC) and LQRC for the same linear model of magnetic levitation system .A magnetic levitation is a nonlinear unstable system and the fuzzy logic controller brings the magnetic levitation system to a stable region by keeping a magnetic ball suspended in the air. The modeling of the system is simulated using Matlab Simulink and connected to Hilink platform and the maglev model of Zeltom company. This paper presents a comparison for both LQRC and FLC to control a ball suspended on the air. The performance results of simulation shows that the fuzzy logic controller had better performance than the LQR control.

A New Control and Design of PEM Fuel Cell System Powered Diffused Air Aeration System

The goal of aquaculture ponds is to maximize production and profits while holding labor and management efforts to the minimum. Poor water quality in most ponds causes risk of fish kills, disease outbreaks which lead to minimization of pond production. Dissolved Oxygen (DO) is considered to be among the most important water quality parameters in fish culture. Fish ponds in aquaculture farms are usually located in remote areas where grid lines are at far distance. Aeration of ponds is required to prevent mortality and to intensify production, especially when feeding is practical, and in warm regions. To increase pond production it is necessary to control dissolved oxygen. Aeration offers the most immediate and practical solution to water quality problems encountered at higher stocking and feeding rates. Many units of aeration system are electrical units so using a continuous, high reliability, affordable, and environmentally friendly power sources is necessary. Fuel cells have become one of the major areas of research in the academia and the industry. Aeration of water by using PEM fuel cell power is not only a new application of the renewable energy, but also, it provides an affordable method to promote biodiversity in stagnant ponds and lakes. This paper presents a new design and control of PEM fuel cell powered a diffused air aeration system for a shrimp farm in Mersa Matruh in Egypt. Also Artificial intelligence (AI) control techniques are used to control the fuel cell output power by controlling its input gases flow rate. Moreover the mathematical modeling and simulation of PEM fuel cell is introduced. A comparative study is applied between the performance of fuzzy logic controller (FLC) and neural network controller (NNC). The results show the effectiveness of NNC over FLC.

A New Control and Design of PEM Fuel Cell Powered Air Diffused Aeration System

Aeration of water by using PEM fuel cell power is not only a new application of the renewable energy, but also, it provides an affordable method to promote biodiversity in stagnant ponds and lakes. This paper presents a new design and control of PEM fuel cell powered by diffused air aeration system for a shrimp farm in Mersa Matruh in Egypt. Also Artificial intelligence (AI) techniques control is used to control the fuel cell output power by controlling input gases flow rate. Moreover the mathematical modeling and simulation of PEM fuel cell is introduced. A comparison study is applied between the performance of fuzzy logic control (FLC) and neural network control (NNC). The results show the effectiveness of NNC over FLC.

Synthesized design of a fuzzy logic controller for an underactuated unicycle

In this paper, we propose synthesized design of a fuzzy logic controller (FLC) for control of an underactuated unicycle system. The FLC objective is velocity control of the wheel while keeping the pendulum upright, which is an unstable equilibrium. The synthesized design consists of three phases. First, the FLC structures including the number of rules, membership functions, inference and parametric relations are chosen based on heuristic knowledge about the unicycle. Second, on the basis of a linearized model and linear feedback, the FLC output parameters are determined quantitatively for stabilization of the unicycle. Third, the FLC output parameters are tuned using an iterative learning tuning (ILT) algorithm, which minimizes an objective function that specifies the desired unicycle performance. The rationale for the synthesized FLC design is full utilization of the available information, which is achieved by combining model-based and model-free designs, and hence improves the FLC performance. We minimize the number of FLC rules and fuzzy labels. Six rules are used for regulation or setpoint tasks, whereas 10 rules are used with extra integral control to eliminate steady-state errors induced by system uncertainties and disturbances. Only two fuzzy labels are adopted for each fuzzy variable. The ILT process consists of two phases, exploration for stabilization and exploitation for better performance. The effectiveness of the proposed FLC is validated using intensive simulations and comparisons.

A New Control and Design of PEM Fuel Cell System Powered Diffused Air Aeration System

The goal of aquaculture ponds is to maximize production and profits while holding labor and management efforts to the minimum. Poor water quality in most ponds causes risk of fish kills, disease outbreaks which lead to minimization of pond production. Dissolved Oxygen (DO) is considered to be among the most important water quality parameters in fish culture. Fish ponds in aquaculture farms are usually located in remote areas where grid lines are at far distance. Aeration of ponds is required to prevent mortality and to intensify production, especially when feeding is practical, and in warm regions. To increase pond production it is necessary to control dissolved oxygen. Aeration offers the most immediate and practical solution to water quality problems encountered at higher stocking and feeding rates. Many units of aeration system are electrical units so using a continuous, high reliability, affordable, and environmentally friendly power sources is necessary. Fuel cells have become one of the major areas of research in the academia and the industry. Aeration of water by using PEM fuel cell power is not only a new application of the renewable energy, but also, it provides an affordable method to promote biodiversity in stagnant ponds and lakes. This paper presents a new design and control of PEM fuel cell powered a diffused air aeration system for a shrimp farm in Mersa Matruh in Egypt. Also Artificial intelligence (AI) control techniques are used to control the fuel cell output power by controlling its input gases flow rate. Moreover the mathematical modeling and simulation of PEM fuel cell is introduced. A comparative study is applied between the performance of fuzzy logic controller (FLC) and neural network controller (NNC). The results show the effectiveness of NNC over FLC.

Fuzzy control with amplitude/pulse-width modulation of nerve electrical stimulation for muscle force control

The main goal of this study was to study the performance of fuzzy logic controllers combined with simplified hybrid amplitude/pulse-width (AM/PW) modulation to regulate muscle force via nerve electrical stimulation. The recruitment curves with AM/PW and AM modulations were constructed for the calf muscles of rabbits. Integrated with the modulation methods, a proportional-integral-derivative (PID) and three fuzzy logic controllers were designed and applied for the electrical stimulation of tibial nerves to control the ankle torque under isometric conditions. The performance of the two modulation methods combined with the four controllers was compared when the ankle was fixed at three positions for both in vivo experiments and model simulations using a nonlinear muscle model. For the animal experiments, AM/PW modulation performed better than AM modulation alone. The fuzzy PI controller performed marginally better and was resistant to external noises, though it tended to have a larger overshoot. The performance of the controllers had a similar trend in the three different joint positions, and the simulation results with the nonlinear model matched the experimental results well. In conclusion, AM/PW modulation improved controller performance, while the contribution of fuzzy logic was only marginal.

Simulation and experimental evaluation on a skyhook policy-based fuzzy logic control for semi-active suspension system

This paper focuses on performance evaluation of several outer loop controller designs employed in a quarter car suspension featuring a magnetorheological fluid damper. A Magne-Ride damper was employed and its behaviour was investigated in the form of force-displacement and force-velocity characteristics. The non-linear hysteretic behaviour of the damper was modelled using a sixth order polynomial model. Force tracking control was performed to check the force tracking ability of the damper using a PI control. The governing equations of motions were formulated and integrated with skyhook control. Skyhook policy was then adapted in the development of a fuzzy logic control to enhance the ride performance. The performance of fuzzy logic control was compared with the on-off and continuous skyhook control in time domain. The results show that skyhook algorithm-based fuzzy logic control gives better performances than its counterparts.

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.

Design of a New Market Structure and Robust Controller for the Frequency Regulation Service in the Deregulated Power System

Part I of this article focuses on the frequency regulation ancillary service and proposes a competitive way to provide this service through price-based and bilateral contracts between Gencos and Discos. The dynamic performance of the charged-bilateral structure is analyzed through a simulation of a step-load disturbance to examine its regulation capabilities for normal operating load and contract violation issues. Part II reports the design of the effective and robust controller for the Part I model and investigates for the integral, dual, and fuzzy controllers with an area control error (ACE)-linked pricing scheme. The simulation results show that fuzzy logic controller performance is better and more robust than the other controllers.

Design of Controller for Nonlinear Process Using Soft Computing

This paper aims at exploring the use of designing a Fuzzy Logic Controller (FLC) tuned using a Genetic Algorithm (GA) which is proposed for a spherical tank to control its level. System identification of this nonlinear process is done using a black box model, which is approximated to be a First Order Plus Dead Time (FOPDT) model. Then, the controller tuning strategy has been applied using Skogestad's PI tuning method. A FLC performance depends on membership functions and its rule base. Genetic algorithms are powerful stochastic search algorithms used for optimization and general problem solving. In this paper, genetic algorithms are used to tune the rule base of the FLC designed for the spherical tank system. The comparison is made with the Skogestad's PI method for the nonlinear process using cost effective data acquisition ADAM's module in real time. The controller design based on GA tuned FLC shows soft computing methods perform better than a conventional controller on performance indices like Integral Squared Error (ISE) and Integral Absolute Error (IAE).

Genetic based sensorless hybrid intelligent controller for strip loop formation control between inter-stands in hot steel rolling mills

Safe operating environment is essential for all complex industrial processes. The safety issues in steel rolling mill when the hot strip passes through consecutive mill stands have been considered in this paper. Formation of sag in strip is a common problem in the rolling process. The excessive sag can lead to scrap runs and damage to machinery. Conventional controllers for mill actuation system are based on a rolling model. The factors like rise in temperature, aging, wear and tear are not taken into account while designing a conventional controller. Therefore, the conventional controller cannot yield a requisite controlled output. In this paper, a new Genetic-neuro-fuzzy hybrid controller without tension sensor has been proposed to optimize the quantum of excessive sag and reduce it. The performance of the proposed controller has been compared with the performance of fuzzy logic controller, Neuro-fuzzy controller and conventional controller with the help of data collected from the plant. The simulation results depict that the proposed controller has superior performance than the other controllers.

Automatic generation control of multi‐area power system using fuzzy logic controller

AbstractThis paper presents an application of Fuzzy Logic Controller (FLC) with triangular and gauss membership functions to study Automatic Generation Control (AGC) of a four‐area interconnected power system. Out of the four areas three have steam turbines and one has hydro turbine. All steam turbines in the system contain the reheat effect of non‐linearity and hydro turbine contains upper and lower constraints for generation rate. The result proves that the performance of FLC with Gaussian membership function is better than that of conventional controller. Copyright © 2007 John Wiley & Sons, Ltd.

Application of kaolin to improve citric acid production by a thermophilic Aspergillus niger

Citric acid production by a thermophilic strain of the filamentous fungus Aspergillus niger IIB-6 in a medium containing blackstrap cane molasses was improved by the addition of kaolin to the fermentation medium. The fermentation was run in a 7.5-l stirred bioreactor (60% working volume). The optimal sugar concentration was found to be 150 g/l. Kaolin (1.0 ml) was added to the fermentation medium to enhance volumetric production. The best results in terms of product formation were observed when 15 parts per million (ppm) kaolin was added 24 h after inoculation. With added kaolin, citric acid production was enhanced 2.34-fold, compared to a control fermentation without added kaolin. The length of incubation to attain this product yield was shortened from 168 to 96 h. The comparison of kinetic parameters showed improved citrate synthase activity of the culture (Y (p/x)=7.046 g/g). When the culture grown at various kaolin concentrations was monitored for Q (p), Q (s), and q (p), there was significant improvement in these variables over the control. Specific production by the culture (q (p)=0.073 g/g cells/h) was improved several fold. The addition of kaolin substantially improved the enthalpy (DeltaH (D)=74.5 kJ/mol) and entropy of activation (DeltaS=-174 J/mol/K) for citric acid production, free energies for transition state formation, and substrate binding for sucrose hydrolysis. The performance of fuzzy logic control of the bioreactor was found to be very promising for an improvement ( approximately 4.2-fold) in the production of citric acid (96.88 g/l), which is of value in commercial applications.

On-line stable gait generation of a two-legged robot using a genetic–fuzzy system

Gait generation for legged vehicles has since long been considered as an area of keen interest by the researchers. Soft computing is an emerging technique, whose utility is more stressed, when the problems are ill-defined, difficult to model and exhibit large scale solution spaces. Gait generation for legged vehicles is a complex task. Therefore, soft computing can be applied to solve it. In this work, gait generation problem of a two-legged robot is modeled using a fuzzy logic controller (FLC), whose rule base is optimized offline, using a genetic algorithm (GA). Two different GA-based approaches (to improve the performance of FLC) are developed and their performances are compared to that of manually constructed FLC. Once optimized, the FLCs will be able to generate dynamically stable gait of the biped. As the CPU-time of the algorithm is found to be only 0.002 s in a P-III PC, the algorithm is suitable for on-line (real-time) implementations.

A recursive rule base adjustment algorithm for a fuzzy logic controller

This paper introduces a recursive rule base adjustment to enhance the performance of fuzzy logic controllers. Here the fuzzy controller is constructed on the basis of a decision table (DT), relying on membership functions and fuzzy rules that incorporate heuristic knowledge and operator experience. If the controller performance is not satisfactory, it has previously been suggested that the rule base be altered by combined tuning of membership functions and controller scaling factors. The alternative approach proposed here entails alteration of the fuzzy rule base. The recursive rule base adjustment algorithm proposed in this paper has the benefit that it is computationally more efficient for the generation of a DT, and advantage for online realization. Simulation results are presented to support this thesis.

Effect of Sampling Rate on the Performance of Fuzzy Logic Controller for the Speed Control of DC Motor

The effect of sampling rate on the performance of Fuzzy Logic Controller (FLC) for the speed control of DC motor has been studied in this paper. A seven number triangular membership function for fuzzification, IF-THEN rules for decision-making logic and Center of Gravity (COG) for defuzzification have been used for the FLC. Experimental setup has been made up of DC micro-motor, LabVIEW software package, Signal Conditioning extension for Instrumentation (SCXI) cards, Data Acquisition (DAQ) board and Fuzzy logic toolkit. The speed control of DC motor was done for a sampling time of 1 second, 3 seconds, 5 seconds. For slower sampling rate the response of DC motor becomes sluggish and oscillations are observed at the set point.

The Effect of Temperature Rise of the Fuzzy Logic-Controlled Braking Resistors on Transient Stability

Braking resistor is a very powerful tool to improve transient stability in a power system. Usually, a fixed value of the braking resistor is considered for the transient stability analysis. However, when the braking resistor is in operation, temperature of the resistor material rises above ambient temperature which ultimately causes the resistance value to increase. This paper analyzes the effect of the temperature rise of the fuzzy logic-controlled braking resistor on the transient stability in a multimachine power system. The performance of the braking resistor scheme with fuzzy controller is compared to that of with conventional proportional-integral-derivative (PID) controller. Simulation results of both balanced and unbalanced faults at different points in the system indicate that the temperature rise of the fuzzy logic-controlled braking resistors has little or almost no effect on the transient stability of the multimachine power system. Moreover, it is found that the performance of fuzzy logic controller is better than that of conventional PID controller. Thus, the proposed fuzzy control strategy provides a simple and effective method of transient stability enhancement.

Remote fuzzy logic control of networked control system via profibus-dp

This paper focuses on the feasibility of fuzzy logic control for networked control systems (NCSs). In order to evaluate its feasibility, a networked control system for servo motor control is implemented on a Profibus-DP network. The NCS consists of several independent, but interacting, processes running on two separate stations. By using this NCS, the network-induced delay is analyzed to find the cause of the delay. Furthermore, the fuzzy logic controller's performance is compared with that of conventional proportional-integral-derivative controllers. Based on the experimental results, it is found that the fuzzy logic controller can be a viable choice for an NCS due to its robustness against parameter uncertainty.

Profibus-DP를 이용한 네트워크 기반 제어 시스템의 원격 퍼지 제어

This paper investigates on the feasibility of fuzzy logic control for networked control systems. In order to evaluate its feasibility, a networked control system for motor speed control is implemented on a Profibus-DP network. The NCS consists of several inde-pendent, but interacting processes running on two separate stations. By using this NCS, the network-induced delay is analyzed to find the cause and effect of the delay. Furthermore, in order to prove the feasibility, the fuzzy logic controller's performance is compared with those of conventional PID controllers. Based on the experimental results, the fuzzy logic controller can be a viable choice far NCS due to its robustness against parameter uncertainty.

Comparison of Quasi Bang-Bang and Sliding Mode Controls for a DC Shunt Motor with Time Delay

We propose a hybrid fuzzy-linear controller for a nonlinearterminal voltage-controlled DC motor. The nonlinearity includes theeffect of magnetization saturation and a nonlinear fan load. The inputto the proposed Fuzzy Logic Controller (FLC) is an 'aggregate' errorbetween the required and the actual rpm and its time derivatives. TheFLC is designed to approximate a bang-bang controller and itscoefficients are chosen as a tradeoff between short rise time, smallsteady-state errors, and control chattering. The FLC performance wascompared to that of a well-known design; namely a sliding modecontroller with a boundary layer. Although the FLC design procedure iseasier, the performance of the two controllers are quite similar.Unfortunately, the FLC design was not robust enough to counter theeffect of large time delays introduced by the power electronicsinterface.