FOPID Controller Research Articles

A comparative evaluation of a set of bio-inspired optimization algorithms for design of two-DOF robust FO-PID controller for magnetic levitation plant

A comparative evaluation of a set of bio-inspired optimization algorithms for design of two-DOF robust FO-PID controller for magnetic levitation plant

Internet of Things-Based Induction Motor Diagnosis Using Convolutional Neural Network

We experimented analyzing motor vibration with aid of Raspberry Pi when, at that time, the engine vibration was abnormal. The Pi signal is transmitted to a relay by the motor supply disconnection. The control unit, nevertheless, monitors and sends the data to the storage system in good form with proper temperature. A FO-PID controller is utilized to analyze the effects of IM due to harmonic current, vibration, and noise. The induction motor’s response to harmonic and current fluctuations is stabilized by a FO-PID controller. The findings can be displayed on the mobile. The tests were carried out in a static state of vibration condition, and fast Fourier transformation is used to analyze the measured vibration data signals. The results of this model were based on the convolutional neural network (CNN), which considerably monitors early diagnostics of the vibration. With a maximum delay of around 1 s, the controller can forward cloud vibration data. Using the CNN model train to analyze the performance of the classification accuracy, the stored data are collected. This article offers a novel way of building tools for measuring vibration in real time based on the schematic architecture provided by the Python mode.

Fuzzy Fractional Order PID Tuned via PSO for a Pneumatic Actuator with Ball Beam (PABB) System

This study aims to improve the performance of a pneumatic positioning system by designing a control system based on Fuzzy Fractional Order Proportional Integral Derivative (Fuzzy FOPID) controllers. The pneumatic system’s mathematical model was obtained using a system identification approach, and the Fuzzy FOPID controller was optimized using a PSO algorithm to achieve a balance between performance and robustness. The control system’s performance was compared to that of a Fuzzy PID controller through real-time experimental results, which showed that the former provided better rapidity, stability, and precision. The proposed control system was applied to a pneumatically actuated ball and beam (PABB) system, where a Fuzzy FOPID controller was used for the inner loop and another Fuzzy FOPID controller was used for the outer loop. The results demonstrated that the intelligent pneumatic actuator, when coupled with a Fuzzy FOPID controller, can accurately and robustly control the positioning of the ball and beam system.

An Optimized FO-PID Controller and Predictive Current Control of the APF Connected AWPS for Power Quality Improvement

An Optimized FO-PID Controller and Predictive Current Control of the APF Connected AWPS for Power Quality Improvement

Load Frequency Control of One and Two Areas Power System Using Grasshopper Optimization Based Fractional Order PID Controller

In this paper, grasshopper optimization based fractional order PID controller for load frequency control of single and multi-area power system is presented. It is paramount to minimize large frequency deviation in power system control. Large frequency deviation occurs when the parameter values of the various generating units of the power system like generators, turbine and governors keeps changing due to numerous on/off witching in the load side. As such, for a more realistic study, nonlinearities and boiler dynamics has been introduced into the power system design and measures also put in place to mitigate large frequency deviation. This is because large frequency deviation can damage equipment at the generation level and the consumer devices at the distribution level. Anti-windup control will then be used to compensate the effects of the nonlinearities. The gain of the FOPID controller will be optimized using grasshopper optimization algorithm and objective function for minimization is the Integral Square Error (ISE). The Errors to be minimized are the summation of frequency deviation, tie-line power deviation and the area control errors. Simulations were carried out on the designed power system using MATLAB/Simulink and results obtained show a significant improvement in mitigating frequency deviation. However, the proposed method took a longer time to balance the generated power and load demand. This is because the proposed method considers boiler dynamics and nonlinearities in the power system designed and results were compared with other designed method for power system without nonlinearities.

Compensation analysis of the active and reactive power of electric vehicles using optimized FOPID‐GA controller

AbstractRecently, the interest in using electric and environmentally friendly vehicles has risen increasingly. The most important challenge is charging these electric vehicles (EVs) at the right time based on the amount of charging demand, which if not paid attention to, can affect the network power profile. In this article, the effect of charging EVs in fast charging stations on the voltage profile and power factor in the IEEE Bus‐33 standard network is investigated. Therefore, a mathematical model is used to model the problem that the parameters of EV arrival time to charging stations, EV charging time, number of charging times, EV status of charging (SOC), distance traveled by the EV are considered as model variables. In this article, four charging stations are considered for each fast‐charging station. The power rate that each station in the fast‐charging station receives from the network is considered 200 kW. So, if all stations are charged simultaneously, the charging station will receive 800 kW of electricity from the grid. There are also 300 EVs in the network, each charging time in fast charging stations is less than 10 minutes. To control the charge and power of cars, the FOPID controller has been used to determine the optimal coefficients through the application of a genetic algorithm (GA). The simulation results showed that in the uncontrolled reactive power mode, the voltage range in the busbars to which the charging stations are connected is less than the standard value (0.95 p.u) in the interval, but using FOPID‐GA controller, we will be able to increase the voltage range and improve the power factor of the distribution system about 10.26% by controlling the reactive power of the vehicles.

Fuzzy Fractional Order Proportional Integral Derivative Controller Design for Higherorder Time Delay Processes

Process control is the interested domain of interest as the industrial high-order applications require an effective control mechanism with higher robustness. Since the conventional method of proportional integral derivative (PID) controller remains inadequate for the higher-order processes, this research concentrates on the fuzzy fractional-order controllers, that more and more attention nowadays in various research areas of science and engineering specifically, on the areas of tuning, design, implementation, and analysis of these controllers. Accordingly, this research marks a milestone for the control industry through introducing a robust controller, fuzzy fractional-order (FO) PI[Formula: see text]D[Formula: see text] (fuzzy FOPID) for higher-order applications with dead time. The fractional-order controller requires the fractional orders for the derivative term [Formula: see text] and integral term [Formula: see text]. The results of the proposed fuzzy FOPID controller is analyzed and compared with the comparative methods, such as a proportional integral derivative (PID) controller and fractional order PID controller (FOPID). Accordingly, the time-domain specifications are evaluated in the presence/absence of the disturbances is analyzed and in addition, the time domain optimal integral metrics are determined. Simulations are carried out using MATLAB/SIMULINK.

Robust Trajectory Tracking Control for Serial Robotic Manipulators Using Fractional Order-Based PTID Controller

The design of advanced robust control is crucial for serial robotic manipulators under various uncertainties and disturbances in case of the forceful performance needs of industrial robotic applications. Therefore, this work has proposed the design and implementation of a fractional order proportional tilt integral derivative (FOPTID) controller in joint space for a 3-DOF serial robotic manipulator. The proposed controller has been designed based on the fractional calculus concept to fulfill trajectory tracking with high accuracy and also reduce effects from disturbances and uncertainties. The parameters of the controller have been optimized with a GWO–PSO algorithm, which is a hybrid tuning method, by considering the time integral performance criterion. The superior and contribution of the GWO–PSO-based FOPTID controller has been demonstrated by comparing the results with those offered by PID, FOPID and PTID control strategies tuned by the GWO–PSO. The examination of the results showed that the proposed controller, which is based on the GWO–PSO algorithm, demonstrates better trajectory tracking performance and increased robustness against various trajectories, external disturbances, and joint frictions as compared to other controllers under the same operating conditions. In terms of the trajectory tracking performance for robustness, the superiority of the proposed controllers tuned by GWO–PSO has been confirmed by 20.2% to 44.5% reductions in the joint tracking errors. Moreover, for assessing the energy consumption of the tuned controllers, the total energy consumption of the proposed controller for all joints has been remarkably reduced by 2.45% as compared to others. Consequently, the results illustrated that the proposed controller is robust and stable and sustains against the continuous disturbance.

Intelligent FOPID and LQR Control for Adaptive a Quarter Vehicle Suspension System

Intelligent FOPID and LQR Control for Adaptive a Quarter Vehicle Suspension System

Intelligent FOPID and LQR Control for Adaptive a Quarter Vehicle Suspension System

Intelligent FOPID and LQR Control for Adaptive a Quarter Vehicle Suspension System

Stability Enhancement of DFIG Wind Farm Using SSSC With FOPID Controller

The wind power generation has become more important nowadays to meet the increase in power demand. DFIG based wind power generation is the recent and used in many countries due to its better power controllability. The controllers like Proportional Integral (PI) are used for the stabilization of the waveforms of the supply system. The change in controllers produces better oscillation damping in recent days. The effect of varying the wind input to generate power using the wind turbine resulting in instability in the power system because of the control is done on a grid supply. This paper aims to proposes an optimum FOPID controller for damping power system instability using a Static Synchronous Series Compensator (SSSC) system that takes into account the dynamics of wind energy conversion systems (WECS) connected to a infinite grid. The WECS model, which includes variations in wind supply to the wind turbine, has been developed to test the durability of the optimized controller that was developed to damping power system oscillations. The controller used to take the power system dynamics into account. A new controller is being designed to include a corrective measure for the damping the oscillations to adjust the instability caused by wind supply variations. The controller helps to tune the controller settings that lead to the achievement of the power oscillation damping objectives. These results are compared with conventional PMSM based wind turbine system.

Improvement of LVRT Capability for DFIG based WECS by Optimal Design of FoPID Controller using SLnO + GWO Algorithm

Improvement of LVRT Capability for DFIG based WECS by Optimal Design of FoPID Controller using SLnO + GWO Algorithm

Analytical Fractional-Order PID Controller Design With Bode’s Ideal Cutoff Filter for PMSM Speed Servo System

In this article, a speed control scheme based on an analytically designed fractional-order PID with Bode’s ideal cutoff (FOPID-BICO) filter is proposed. The FOPID controller is designed to track the speed references and the BICO suppress is applied to filter the high-frequency noise. Considering the difficulty of parameters tuning of the FOPID controller, a comprehensive analytical design method based on frequency specifications-defined loop-shaping for the FOPID-BICO controller is first proposed for the permanent magnet synchronous motor speed control. The designed speed servo system satisfies five frequency-domain specifications: gain crossover frequency, phase margin, phase crossover frequency, gain margin, and a “flat phase” constraint. Moreover, the influence of phase crossover frequency on control system is fully exposed through the frequency-domain analysis. The proposed designed method ensures that the control system is robust to loop gain variations and guarantees the optimal performance on rejecting noise in high-frequency and disturbance in low-frequency. The effectiveness of the proposed FOPID-BICO controller has been verified by experimental results.

A Software Realization of Disturbance Rejection Optimal FOPID Controller Design Methodology by Using Soft Computing Techniques

This study presents a soft computing tool for the computer-aided design of disturbance rejection FOPID controllers based on the maximization of Reference to Disturbance Ratio (RDR) index. The study illustrates the utilization of software routines to implement a soft computing scheme in order to solve a closed loop disturbance rejection FOPID control system design problem for a target gain margin specification. Authors demonstrate that the complex design efforts, which involve a high level of mathematical knowledge, can be easily performed by using basic software routines when soft computing techniques are employed effectively in the computation processes. Illustrative design examples are shown to show effectiveness of the proposed design method.

Dimension Synthesis and Optimized FOPID Control of the Delta Robot with Moth Swarm Algorithm

Dimension Synthesis and Optimized FOPID Control of the Delta Robot with Moth Swarm Algorithm

Gaussian Rbfnn Method for Solving Fpk and Bk Equations in Stochastic Dynamical System with Fopid Controller

Gaussian Rbfnn Method for Solving Fpk and Bk Equations in Stochastic Dynamical System with Fopid Controller

Asynchronous Machine Controlled by A Series Multi-Cells Converter Using FOPID Controller Tuning with GWO

Asynchronous Machine Controlled by A Series Multi-Cells Converter Using FOPID Controller Tuning with GWO

An adaptive neuro-fuzzy based on a fractional-order proportional integral derivative design for a two-legged robot with an improved swarm algorithm

In this paper, an adaptive neuro-fuzzy based on fractional-order proportional-integral-derivative (ANFFOPID) controller with an improved slime mould algorithm (ISMA) for the two-legged robot (TLR) is proposed to achieve the minimum angular displacement error of the joint motors. Achieving such error is considered a challenging and time-consuming process due to the gain values set for the FOPID controller. Thus the neural-fuzzy network is used to provide the FOPID input signals by the adaptive magnitude gains. The adaptive mechanism depends on the ISMA to train the neural network weights. The outstanding properties of the ANFFOPID controller are evaluated by comparing the proposed controller with other existing work that is modified chaotic invasive weed optimization based on neural network (MCIWO-NN) for various walking terrains that are flat surface, stair ascending, and stair descending. Finally, the results obtained show the effectiveness of the ANFFOPID controller.

SMES-GCSC Coordination for Frequency and Voltage Regulation in a Multi-Area and Multi-Source Power System with Penetration of Electric Vehicles and Renewable Energy Sources

Frequency, tie-line power, and the terminal voltages of synchronized generators must all be kept within prescribed limits to ensure the stability of an interconnected power grid through combined automatic generation control (AGC) and automatic voltage regulator (AVR) loops. Thermal power plants, electric vehicles, and renewable energy sources—including solar and wind, geothermal, and solar thermal power plants—form the two-area integrated power system in present research. A new cascade controller named the cascaded proportional integral derivative (PID) and fractional-order PID (CPID-FOPID) controller is proposed for the first time, whose performance is compared with the PID and FOPID controller. The results show that the proposed cascade controller outperforms PID and FOPID in delivering superior dynamic characteristics, including short settling times and low oscillation amplitudes. A new metaheuristic algorithm named the coot algorithm was applied to optimize the parameters of these controllers. The suggested controller outperforms FOPID in the combined AGC and AVR problem under uncertain conditions (random load disturbance, variable input of solar irradiation, and wind power). Robustness of the controller is tested with significant variation in the turbine time constant of the thermal and geothermal power plant. In this study, authors also investigated the best possible coordination between the superconducting magnetic energy storage (SMES) and gate-controlled series capacitor (GCSC) devices to control both voltage and frequency simultaneously. The effect of communication time to the power system is analyzed in this study. Additionally, the obtained results are satisfactorily validated using OPAL-RT real-time digital simulator.

Modified Frequency Regulator Based on TIλ-TDμFF Controller for Interconnected Microgrids with Incorporating Hybrid Renewable Energy Sources

Reducing the emissions of greenhouse gases has directed energy sectors toward using renewable energy sources (RESs) and decreasing the dependency on conventional energy sources. Recently, developing efficient load frequency control (LFC) schemes has become essential to face the reduced inertia due to RESs installations. This paper presents a modified tilt fractional order (FO) integral–tilt FO derivative with a fractional filter (TFOI-TFODFF or namely TIλ-TDμFF) LFC method. Although the proposed controller uses the same elements of standard controllers, it adopts FO control capabilities and flexibilities, including the tilt, FO integral, FO derivative, and FO filter. Thence, a new control structure is obtained, merging the advantages of both controllers. Moreover, the proposed TFOI-TFODFF controller employs two control loops to be able to mitigate low-frequency as well as high-frequency disturbances in power grids. Additionally, a new modified marine predator algorithm (MMPA) is proposed for optimally tuning the parameters of the proposed TFOI-TFODFF LFC method. The performance of the MMPA is enhanced in terms of initialization and exploitation phases using the chaotic maps and weighting factor. A two-area interconnected power system case study is implemented with wind and photovoltaic RESs and electric vehicles (EVs) contribution. The proposed TFOI-TFODFF LFC is compared with the FOPID, TID, TI-DF, and FOTPID controllers, wherein the proposed TFOI-TFODFF has offered superior performance of the proposed controller. Moreover, the proposed modified MPA is compared with the original MPA and other competitive optimization algorithms, and statistical analyses are carried out through parametric and nonparametric tests.