Single Input Fuzzy Logic Controller Research Articles

Water level control of small-scale recirculating aquaculture system with protein skimmer using fuzzy logic controller

The recirculating aquaculture system (RAS) is a land-based aquaculture facility, either open-air or indoors, that minimizes water consumption by filtering, adapting, and reusing water. Solid organic matter from fish waste and food waste directly becomes waste that needs to be eliminated because it is a source of increasing total ammonia nitrogen (TAN), total suspended solids (TSS), total dissolved solids (TDS), and also has an impact on reducing dissolved oxygen (DO). RAS requires a water level control system so the fish tank does not experience water shortages or floods, disrupting the aquatic aquaculture ecosystem. In this study, small-scale RAS is modeled using a 3-coupled tanks system approach with a tank configuration that follows the most straightforward RAS water recirculation process (fish tank, mechanic filter, biofilter). Clean water from the reservoir flows into the fish tank through a protein skimmer. This study applies the fuzzy logic controller (FLC) to control the water level in the protein skimmer and biofilter tanks by controlling the position of several valves where the placement positions of the valves have been determined according to system requirements. The study results show that the tuned single-input FLC has the best average output response characteristics with t<sub>s</sub>=50, h<sub>1ss</sub>=49.98, e<sub>ss</sub>=0.02 in protein skimmer and t<sub>s</sub>=4700, h<sub>1ss</sub>=39.75, e<sub>ss</sub>=0.25 in the tank system.

Fuzzy Based Energy Management Strategy for Hybrid Micro Grid with Battery Storage System

By connecting it to the hybrid micro grid system, this explains the combination of wind, solar, and fuel cell power. Renewable energy is frequently used today. Distributed energy sources like wind, solar, fuel cells, etc., can operate concurrently with a larger utility. The majority of people today want to use sustainable energy sources like solar, wind, tidal, geothermal, wave, etc. A tiny grid produces the necessary electricity. In this project, energy storage and utilisation with a micro grid are demonstrated. This project serves as an example of how a micro grid can be used to store and use power. We usually allow the Micro Grid to use us by producing this energy. The system is a composite that utilises renewable resources such fuel cell, a solar array, a wind generator, and an energy storage system (ESS) that uses a battery as one of its renewable energy sources. Power Electronics converters are crucial to the system since they enhance power management and control strategies for various sources. The single-input Fuzzy logic and speed controllers are utilised to track the maximum power point for the wind and PV subsystems, respectively (MPPT). A power management method based on battery state of charge (SOC) was created and put into use to maintain the hybrid system's energy balance. A proportional integrative (PI) controller was used to supply a resistive load with a constant amplitude and frequency in order to regulate the AC output voltage was obtained. The proposed solution is deemed to be very promising for possible applications in hybrid renewable energy management systems based on the received bids. MATLAB/SIMULINK is to be used to develop the simulation.

Spiral Dive Control of Underactuated AUV Based on a Single-Input Fractional-Order Fuzzy Logic Controller

Autonomous underwater vehicles (AUVs) have broad applications owing to their ability to undertake long voyages, strong concealment, high level of intelligence and ability to replace humans in dangerous operations. AUV motion control systems can ensure stable operation in the complex ocean environment and have attracted significant research attention. In this paper, we propose a single-input fractional-order fuzzy logic controller (SIFOFLC) as an AUV motion control system. First, a single-input fuzzy logic controller (SIFLC) was proposed based on the signed distance method, whose control input is the linear combination of the error signal and its derivative. The SIFLC offers a significant reduction in the controller design and calculation process. Then, a SIFOFLC was obtained with the derivative of the error signal extending to a fractional order and offering greater flexibility and adaptability. Finally, to verify the superiority of the proposed control algorithm, comparative numerical simulations in terms of spiral dive motion control were conducted. Meanwhile, the parameters of different controllers were optimized according to the hybrid particle swarm optimization (HPSO) algorithm. The simulation results illustrate the superior stability and transient performance of the proposed control algorithm.

Aggressive maneuvering of a quadcopter via differential flatness-based fuzzy controllers: From tuning to experiments

In recent years, the rapid development in contemporary technology has brought nano quadcopters with high agility. This paper presents a new differential flatness-based Single Input Fuzzy Logic Controller (SFLC) structure for aggressive maneuvering control alongside its real-world application on Crazyflie 2.1 nano quadcopter. We propose both Type-1 and Interval Type-2 SFLCs as the primary controllers in the flight control system, which are built on the concept of differential flatness. We investigate how the design parameters of SFLCs shape the characteristics of the fuzzy mapping through a geometric approach by analyzing the region and level of aggressiveness/smoothness. Based on the analysis, we present simple tuning guidelines and then design fuzzy logic-based flight control systems, which were implemented as onboard real-time controllers. Finally, we evaluate the performance of SFLCs in comparison with their crisp differential flatness-based nonlinear counterparts for four trajectories with distinct dynamics and shapes in the real world. The presented comparative experimental results clearly show the performance improvements when the proposed T1 and IT2 SFLCs are deployed for real-time aggressive maneuvering.

New lambda tuning approach of single input fuzzy logic using gradient descent algorithm and particle swarm optimization

<span>Underwater remotely operated vehicle (ROV) is important in underwater industries as well as for safety purposes. It can dive deeper than humans and can replace humans in a hazardous underwater environment. ROV depth control is difficult due to the hydrodynamic of the ROV itself and the underwater environment. Overshoot in the depth control may cause damage to the ROV and its investigated location. This paper presenting a new tuning approach of single input fuzzy logic controller (SIFLC) with gradient descent algorithm (GDA) and particle swarm optimization (PSO) implementation for ROV depth control. The ROV was modeled using system identification to simulate the depth system. Proportional integral derivative (PID) controller was applied to the model as a basic controller. SIFLC was then implemented in three tuning approaches which are heuristic, GDA, and PSO. The output transient was simulated using MATLAB Simulink and the percent overshoot (OS), time rise (Tr), and settling time (Ts) of the systems without and with controllers were compared and analyzed. The result shows that SIFLC GDA output has the best transient result at 0.1021% (OS), 0.7992s (Tr), and 0.9790s (Ts).</span>

A new tuning approach of Single Input Fuzzy Logic Controller (SIFLC) for Remotely Operated Vehicle (ROV) Depth Control

A new tuning approach of Single Input Fuzzy Logic Controller (SIFLC) for Remotely Operated Vehicle (ROV) Depth Control

Experimental investigation of power management and control of a PV/wind/fuel cell/battery hybrid energy system microgrid

This paper presents an experimental study of a standalone hybrid microgrid system. The latter is dedicated to remote area applications. The system is a compound that utilizes renewable sources that are Wind Generator (WG), Solar Array (SA), Fuel Cell (FC) and Energy Storage System (ESS) using a battery. The power electronic converters play a very important role in the system; they optimize the control and energy management techniques of the various sources. For wind and solar subsystem, the speed and Single Input Fuzzy Logic (SIFL) controllers are used respectively to harvest the maximum power point tracking (MPPT). To maintain a balance of energy in the hybrid system, an energy management strategy based on the battery state of charge (SOC) has been developed and implemented experimentally. The AC output voltage regulation was achieved using a Proportional Integral (PI) controller to supply a resistive load with constant amplitude and frequency. According to the obtained performances, it was concluded that the proposed system is very promising for potential applications in hybrid renewable energy management systems.

Adaptation mechanism techniques for improving a model reference adaptive speed observer in wind energy conversion systems

Rotational speed sensor is one of the most important components used in wind energy conversion system control strategies. The latter is very expensive and may be faulty due to the harsh environment working, causing by that a low efficiency operation of the system. The use of a speed estimator or an observer may be a good alternative solution for the use either in sensorless control or detecting the sensor failure or degradation (FDI and FTC), provided that the observer is robust and ensures high rotational speed estimation accuracy. This paper presents a comprehensive study to solve the optimization problem of a model reference adaptive speed (MRAS) observer in a typical wind energy generation system based on permanent magnet synchronous generator using five adaptation mechanisms: The first one is the classical MRAS observer; it is based on proportional–integral (PI) controller. The second one uses a fuzzy logic controller (FLC) with two inputs. The third one uses the single-input fuzzy logic controller which represents the simplification of the conventional FLC. The fourth one uses the sliding mode controller, and the last one uses the super-twisting algorithm. A detailed comparison between the five adaptation mechanisms is carried out. The obtained results show a good estimation stability as well as a fast speed estimation at dynamic regime for the improved adaptation mechanisms compared with the conventional PI controller.

Sliding Mode & Single Input Fuzzy Logic Controllers for Voltage Regulation Of an Asynchronous Wind Turbine Using STATCOM

This paper demonstrate the fiability and the efficiency of a proposed control law based on a combination of sliding mode and single input fuzzy logic controllers, used to command a static synchronous compensator in order to improve voltage profile and stability of an asynchronous wind turbine despite wind speed and load variation. All simulation results as well as the modeling of the wind power system and the design of the proper controllers are described in detail in this document.

A simplify fuzzy logic controller design based safe experimentation dynamics for pantograph-catenary system

Contact force between catenary and pantograph of high speed train is a crucial system to deliver power to the train. The inconsistence force between them can cause the contact wire oscillate a lot and it can damage the mechanical structure of system and produce electric arc that can reduce the performance of system. This project proposes a single-input fuzzy logic controller (SIFLC) to control the contact force between the pantograph-catenary by implement Safe Experimentation Dynamics (SED) method to tune the SIFLC parameters. The essential feature of SIFLC is that it is model-free type controller design with less pre-defined variables as compared to other existing model-based controllers. The performance of the SIFLC is analyzed in terms of input tracking of contact force of pantograph-catenary and time response specifications. A simplified model of three degree of freedom (3-DOF) pantograph-catenary system is considered. In this study, the simulation result shows that the SIFLC successfully track the given contact force with less overshoot with percentage different of peak to peak response from actual force 2% and fast response within 5.27s

A Fast Recovery Technique for Grid-Connected Converters After Short Dips Using a Hybrid Structure PLL

Repeated faults in an industrial grid have affected a steel manufacturing plant and resulted in frequent tripping of all medium voltage converters. The reason for the trips was a synchronization fault due to a severe short duration voltage dip. Converters need a relatively long time to resume its normal operation after dip recovery due to the capacitors precharging process. If the capacitor's discharging is prevented, the converter can resume its normal operation after being synchronized. The synchronization process is performed by a phase locked loop type SRF-PLL with a very low bandwidth and low-pass in-loop filter, which delays the recovery process. In this paper, a solution for the aforementioned trip is presented by proposing two different synchronization hybrid schemes. The first scheme is assuming the converter already lost the synchronization, and a ride-through sequence is implemented to prevent the capacitor from discharging. The second scheme is proposed to prevent the synchronization fault and to recover the converter quickly after dip ends. Both schemes are implemented using a single-input fuzzy logic controller to obtain a very fast response. The performance of the proposed schemes is validated through simulation and a prototype experimental setup.

Task Space Control of an Autonomous Underwater Vehicle Manipulator System by Robust Single-Input Fuzzy Logic Control Scheme

In this paper, a robust single-input fuzzy logic control Robust Single Input Fuzzy Logic Controller (RSIFLC) scheme is proposed and applied for task-space trajectory control of an autonomous underwater vehicle manipulator system (AUVMS) employed for underwater manipulation tasks. The effectiveness of the proposed control scheme is numerically demonstrated on a planar underwater vehicle manipulator system [consisting of an underwater vehicle and a two link rotary (2R) serial planar manipulator]. The actuator and sensor dynamics of the system are also incorporated in the dynamical model of an AUVMS. The proposed control law consists of a feedforward term to exaggerate the control activity with immoderation from the known desired acceleration vector and an estimated perturbed term to compensate for the unknown effects namely external disturbances and unmodeled dynamics as a first part and a single-input fuzzy logic control as a feedback portion to enhance the overall closed-loop stability of the system as a second part. The primary objective of the proposed control scheme is to track the given end-effector task space trajectory despite of external disturbances, system uncertainties, and internal noises associated with the AUVMS. To show the efficacy of the proposed control scheme, comparison is made with conventional fuzzy logic control (CFLC), sliding mode control (SMC), and proportional–integral–derivative (PID) controllers. Simulation results confirmed that with the proposed control scheme, the AUVMS can successfully track the given desired spatial trajectory and gives better and robust control performance.

A simplified yet effective fuzzy logic controller for chemical ship tanker

This paper proposes a simplified yet effective control scheme to design a fuzzy logic controller (FLC) for the ship tanker. The proposed method exploits the feature of signed distance method for reducing the conventional two-input FLC (CFLC) into a piecewise linear single input FLC (PWL-FLC). It has been shown that the proposed FLC has a similar structure to the CFLC, exhibiting analogous control performance. However, the main features of the proposed method are the absence of fuzzification, rule inference and defuzzification processes that are essential for CFLC implementation. The proposed PWL-FLC could be easily programmed into a low cost microcontroller using just a look-up table. To authenticate its effectiveness, the control algorithm has been implemented using the marine system simulator in Matlab/Simulink ® platform. The result signifies that both the PWL-FLC and CFLC results in identical functioning performance; however, the former requires least possible tuning effort and its execution time is in the orders of three magnitudes less than its conventional counterpart.

Design of Single Input Fuzzy Logic Controller for Shunt Active Power Filter

ABSTRACTThis paper describes the application of single input fuzzy logic controller (SIFLC) for three-phase shunt active power filter. The advantage of the fuzzy logic controller is that it does not require mathematical modelling of the system. The application of two-input fuzzy logic controller to three-phase shunt active power filter is reported in literature. But the two-input fuzzy logic controller needs large set of rules for optimum performance. The SIFLC reduces conventional two-input fuzzy logic controller to single input fuzzy logic controller. The SIFLC offers a significant reduction in rule inferences and simplifies the tuning of control parameters. An SIFLC is designed for three-phase two-level active power filter. A shunt active power filter with SIFLC is simulated for nonlinear load in the MATLAB Simulink environment. The hysteresis controller is used to generate the switching pulses. The simulated response with SIFLC is found to be better than conventional fuzzy logic controller (CFLC). Also the execution time of SIFLC found to be lesser than CFLC. A prototype model of the active power filter is developed in the laboratory to validate the simulated response. An 1104 dSPACE is used to generate the appropriate pulses for the switches of active power filter.

Feed-Forward Control Algorithm for Hybrid Energy Systems

Abstract The paper presents a comparative analysis of the control strategies that can be used for hybrid energy systems. In the system considered, solar energy and battery are the two input sources to the DC-DC converter. Due to the intermittent availability of solar energy, a control circuit needs to be designed for the voltage regulation of the hybrid energy system. A single input fuzzy logic controller can maintain the output voltage constant for variations in either Photovoltaic (PV) or battery voltage only. Hence a control strategy is proposed in this paper to accomplish output voltage regulation for variations in both PV and battery voltages. The comparison of the two control techniques is presented along with the simulation results.

Design of Single-Input Fuzzy Logic Controller for Spatial Control of Advanced Heavy Water Reactor

In large nuclear reactors, such as the Advanced Heavy Water Reactor (AHWR), the spatial oscillations in the neutron flux distribution due to xenon reactivity feedback need to be properly controlled; otherwise, power density and rate of change of power at some locations in the reactor core may exceed limits of fuel failure due to “flux tilting.” Further, situations, such as online refueling, might cause transient variations in the flux shape from the nominal flux shape. For analysis and control of spatial oscillations in AHWR, it is necessary to design a suitable control strategy, which will be able to stabilize these oscillations. In this paper, a simplified scheme to design a fuzzy logic controller for spatial control of AHWR, known as the single-input fuzzy logic controller (SIFLC) is proposed. The SIFLC reduces the conventional two-input fuzzy logic controller (CFLC) to a single-input FLC. The SIFLC offers a significant reduction in rule inferences and simplifies the tuning of control parameters. The SIFLC requires less execution time compared to CFLC for the control of spatial oscillations in AHWR. Through the dynamic simulations, it is observed that the designed SIFLC is able to suppress spatial oscillations developed in AHWR and the performance is found to be better compared to the recently proposed approach in the literature.

Tuning process of single input fuzzy logic controller based on linear control surface approximation method for depth control of underwater remotely operated vehicle

This study investigates the linear approximation or piecewise linear approximation control surface method for tuning variable parameter of Single Input Fuzzy Logic Controller (SIFLC) for depth control of the underwater Remotely Operated Vehicle (ROV). This method will focus on slope of a linear equation to give optimum performances of depth control without overshoot in system response and faster rise time and settling time. The variable parameter for signed distance method in SIFLC tuning by Particle Swarm Optimization (PSO) algorithm. The optimum parameter will be obtained and approximately no more variable parameter can be tuned because the PSO algorithm will yield optimum parameter. This linear control surface approximation method represents an inference engine of fuzzy logic. The investigation also done based on slope of linear equation either in positive and negative values and come up from conventional FLC that will simplify into SIFLC. The results obtained the slope of linear equation will be affecting the results of system performances.

Analysis of an improved Single Input Fuzzy Logic Controller designed for depth control using Microbox 2000/2000c interfacing

This paper describes an analysis of an improved designed of Single Input Fuzzy Logic Controller (SIFLC) for depth control using Microbox 2000/2000C interfacing. The analysis based on the model of an unmanned underwater platform that called Remotely Operated Vehicle (ROV). This ROV modeling obtained using a MATLAB system identification toolbox on open loop depth control experiment by Underwater Technology Research Group (UTeRG). Microbox 2000/2000C is an XPC target machine device used to interface between an ROV with the MATLAB 2009 software. An improved design for SIFLC based on two parameters that is a distance, d, and its control surface for SIFLC using the linear equation technique will be discussed. Newly technique called An improved Single Input Fuzzy Logic Controller (an improved SIFLC) design for underwater Remotely Operated Vehicle (ROV) also described and will be implemented to simplify the complexity of the system in real time. The optimum parameter for SIFLC tuned using optimization technique. The implementation phase will be verified through MATLAB SIMULINK platform and real time experiment.

A Comparison Study between Two Algorithms Particle Swarm Optimization for Depth Control of Underwater Remotely Operated Vehicle

This paper investigates two algorithms based on particle swarm optimization (PSO) to obtain optimum parameter. In this research, an improved PSO algorithm using a priority-based fitness PSO (PFPSO) and priority-based fitness binary PSO (PFBPSO) approach. This comparison study between two algorithms applied on underwater Remotely Operated Vehicle for depth control. Two parameters in Single Input Fuzzy Logic Controller will tune using two algorithms to obtain optimum parameter. There are two parameters to be tuned namely the break point and slope for the piecewise linear or slope for the linear approximation. The study also covered a comparison for time execution for every time the parameter tuning was done. Based on the results the PFBPSO gives a consistent value of optimum parameter and time execution very fast. The best optimum parameter of SIFLC determined using 2 methods such that average of optimum parameter and intersection of y-axis. The PFBPSO gives comparative results in term of two parameters and time execution very fast compared with improved PSO.

LQR-퍼지논리제어기에 의한 2중 차량 구조 역진자 시스템의 제어

임의의 비선형 시스템을 제어하기 위한 새로운 방법의 제어 알고리즘이 널리 보고되고 있으며, 그 유용성을 입증하기 위한 제어 대상 시스템으로 역진자 시스템이 널리 활용되고 있다. 본 논문에서는 스프링으로 연결된 2개의 차량에 장착된 역진자를 제어하는 알고리즘을 제시한다. 여기서 두 개의 차량 중 하나는 구동용, 다른 하나는 역진자를 장착한 무구동용이다. 이를 위한 시스템 모델링을 제시하고, 퍼지논리제어 시스템 기반의 양질의 제어기 설계를 제안한다. 본 논문에서는 퍼지논리제어기의 입력변수로 사용될 6개의 변수를 2개로 축소하기 위하여 LQR(Linar Quadratic Regulator) 기법을 도입하며, 이를 통하여 퍼지논리제어기 설계의 복잡성을 줄일 수 있음을 보인다. 더욱이 개선된 2-입력 퍼지논리제어기의 제어 규칙표가 skew-symmetric의 특성을 가지는 성질로부터 다시 단일입력 퍼지논리제어기 설계를 제안한다. 제안한 방법의 유용성을 입증하기 위하여 시뮬레이션을 수행하며, 이를 통하여 제안한 방법의 우수성을 입증한다. Any new method for controlling a nonlinear system has widely been reported. An inverted pendulum system has typically been used as a target system for demonstrating its usefulness. In this paper, we propose an algorithm to control a flexible joint cart based inverted pendulum system. Two carts are connected with a spring and one is a driving cart and the other is no driving cart with a pole. We here present a system modeling and a good fuzzy logic based control algorithm. We also introduce LQR (Linar Quadratic Regulator) technique for reducing the number of control variables. By using this technique, the number of input variables for a fuzzy logic controller is become only two not six. So the computational complexity is largely reduced. Moreover, a two-input fuzzy logic controller has a control rule table with a skew-symmetric property. And it will lead the design of a single-input fuzzy logic controller. In order to demonstrate the usefulness of the proposed method and prove the superiority of the proposed method, some computer simulations are presented.