An Adaptive Neuro-Fuzzy Inference System to Improve Fractional Order Controller Performance

The design and analysis of a fractional order proportional integral deri-vate(FOPID)controller integrated with an adaptive neuro-fuzzy inference system(ANFIS)is proposed in this study.Afirst order plus delay time plant model has been used to validate the ANFIS combined FOPID control scheme.In the pro-posed adaptive control structure,the intelligent ANFIS was designed such that it will dynamically adjust the fractional order factors(λandµ)of the FOPID(also known as PIλDµ)controller to achieve better control performance.When the plant experiences uncertainties like external load disturbances or sudden changes in the input parameters,the stability and robustness of the system can be achieved effec-tively with the proposed control scheme.Also,a modified structure of the FOPID controller has been used in the present system to enhance the dynamic perfor-mance of the controller.An extensive MATLAB software simulation study was made to verify the usefulness of the proposed control scheme.The study has been carried out under different operating conditions such as external disturbances and sudden changes in input parameters.The results obtained using the ANFIS-FOPID control scheme are also compared to the classical fractional order PIλDµand conventional PID control schemes to validate the advantages of the control-lers.The simulation results confirm the effectiveness of the ANFIS combined FOPID controller for the chosen plant model.Also,the proposed control scheme outperformed traditional control methods in various performance metrics such as rise time,settling time and error criteria.

A Novel ANFIS Based SMC with Fractional Order PID Controller

Interacting The highest storage capacity of a circular tank makes it pop-ular in process industries.Because of the varying surface area of the cross-sec-tions of the tank,this two-tank level system has nonlinear characteristics.Controlling theflow rate of liquid is one of the most difficult challenges in the production process.This proposed effort is critical in preventing time delays and errors by managing thefluid level.Several scholars have explored and explored ways to reduce the problem of nonlinearity,but their techniques have not yielded better results.Different types of controllers with various techniques are implemented by the proposed system.Sliding Mode Controller(SMC)with Fractional Order PID Controller based on Intelligent Adaptive Neuro-Fuzzy Infer-ence System(ANFIS)is a novel technique for liquid level regulation in an inter-connected spherical tank system to avoid interferences and achieve better performance in comparison of rise time,settling time,and overshoot decrease.Evaluating the simulated results acquired by the controller yields the efficiency of the proposed system.The simulated results were produced using MATLAB 2018 and the FOMCON toolbox.Finally,the performance of the conventional controller(FOPID,PID-SMC)and proposed ANFIS based SMC-FOPID control-lers are compared and analyzed the performance indices.

Fractional-Order Control of a Wind Turbine Using Manta Ray Foraging Optimization

In this research paper,an improved strategy to enhance the performance of the DC-link voltage loop regulation in a Doubly Fed Induction Generator(DFIG)based wind energy system has been proposed.The proposed strategy used the robust Fractional-Order(FO)Proportional-Integral(PI)control technique.The FOPI control contains a non-integer order which is preferred over the integer-order control owing to its benefits.It offers extra flexibility in design and demonstrates superior outcomes such as high robustness and effectiveness.The optimal gains of the FOPI controller have been determined using a recent Manta Ray Foraging Optimization(MRFO)algorithm.During the optimization process,the FOPI controller’s parameters are assigned to be the decision variables whereas the objective function is the error racking that to be minimized.To prove the superiority of the MRFO algorithm,an empirical comparison study with the homologous particle swarm optimization and genetic algorithm is achieved.The obtained results proved the superiority of the introduced strategy in tracking and control performances against various conditions such as voltage dips and wind speed variation.

A novel fractional order controller design algorithm for a class of linear systems

In this paper,a novel fractional order controller design algorithm is proposed for a class of linear systems.The proposed control algorithm is developed by employing Riemann principal sheet stability criterion.Oustaloup recursive approximation(ORA)method is used to implement the controller.The proposed controller is implemented in simulation.The results show that the proposed fractional order controller provides better results than the existing controllers in the literature work.

Design and Implementation of Digital Fractional Order PID Controller Using Optimal Pole-Zero Approximation Method for Magnetic Levitation System

The aim of this paper is to employ fractional order proportional integral derivative(FO-PID)controller and integer order PID controller to control the position of the levitated object in a magnetic levitation system(MLS),which is inherently nonlinear and unstable system.The proposal is to deploy discrete optimal pole-zero approximation method for realization of digital fractional order controller.An approach of phase shaping by slope cancellation of asymptotic phase plots for zeros and poles within given bandwidth is explored.The controller parameters are tuned using dynamic particle swarm optimization(d PSO)technique.Effectiveness of the proposed control scheme is verified by simulation and experimental results.The performance of realized digital FO-PID controller has been compared with that of the integer order PID controllers.It is observed that effort required in fractional order control is smaller as compared with its integer counterpart for obtaining the same system performance.

Fractional order PID control for steer-by-wire system of emergency rescue vehicle based on genetic algorithm

Aiming at dealing with the difficulty for traditional emergency rescue vehicle(ECV)to enter into limited rescue scenes,the electro-hydraulic steer-by-wire(SBW)system is introduced to achieve the multi-mode steering of the ECV.The overall structure and mathematical model of the SBW system are described at length.The fractional order proportional-integral-derivative(FOPID)controller based on fractional calculus theory is designed to control the steering cylinder’s movement in SBW system.The anti-windup problem is considered in the FOPID controller design to reduce the bad influence of saturation.Five parameters of the FOPID controller are optimized using the genetic algorithm by maximizing the fitness function which involves integral of time by absolute value error(ITAE),peak overshoot,as well as settling time.The time-domain simulations are implemented to identify the performance of the raised FOPID controller.The simulation results indicate the presented FOPID controller possesses more effective control properties than classical proportional-integral-derivative(PID)controller on the part of transient response,tracking capability and robustness.

Digital implementation of fractional order PID controller and its application

A new discretization scheme is proposed for the design of a fractional order PID controller. In the design of a fractional order controller the interest is mainly focused on the s-domain, but there exists a difficult problem in the s-domain that needs to be solved, i.e. how to calculate fractional derivatives and integrals efficiently and quickly. Our scheme adopts the time domain that is well suited for Z-transform analysis and digital implementation. The main idea of the scheme is based on the definition of Grünwald-Letnicov fractional calculus. In this case some limited terms of the definition are taken so that it is much easier and faster to calculate fractional derivatives and integrals in the time domain or z-domain without loss much of the precision. Its effectiveness is illustrated by discretization of half-order fractional differential and integral operators compared with that of the analytical scheme. An example of designing fractional order digital controllers is included for illustration, in which different fractional order PID controllers are designed for the control of a nonlinear dynamic system containing one of the four different kinds of nonlinear blocks: saturation, deadzone, hysteresis, and relay.

Guest Editorial for Special Issue on Fractional Order Systems and Controls

I.INTRODUCTION FRACTIONAL calculus has been applied in all MAD(modeling,analysis and design)aspects of control systems engineering since Shunji Manabe’s pioneering work in early 1960s.The 2016 International Conference on Fractional Differentiation and Its Applications(ICFDA)was held in Novi Sad,Serbia,July 18-20.Quoting from the

Fractional Order Proportional Integral Derivative Controller Design and Simulation for Bioengineering Systems

This paper deals with the study of fractional order system tuning method based on Factional Order Proportional Integral Derivative( FOPID) controller in allusion to the nonlinear characteristics and fractional order mathematical model of bioengineering systems. The main contents include the design of FOPID controller and the simulation for bioengineering systems. The simulation results show that the tuning method of fractional order system based on the FOPID controller outperforms the fractional order system based on Fractional Order Proportional Integral( FOPI) controller. As it can enhance control character and improve the robustness of the system.

Guest Editorial for Special Issue on Fractional Order Systems and Controls

I.INTRODUCTION FRACTIONAL calculus is about differentiation and integration of non-integer orders.Using integer-order models and controllers for complex natural or man-made systems is simply for our own convenience while the nature runs in a fractional order dynamical way.Using integer order traditiona tools for modelling and control of dynamic systems may resul in suboptimum performance,that is,using fractional order calculus tools,we could be'more optimal'as already doc-

Model Identification and Control of Electromagnetic Actuation in Continuous Casting Process With Improved Quality

This paper presents an original theoretical framework to model steel material properties in continuous casting line process. Specific properties arising from non-Newtonian dynamics are herein used to indicate the natural convergence of distributed parameter systems to fractional order transfer function models. Data driven identification from a real continuous casting line is used to identify model of the electromagnetic actuator device to control flow velocity of liquid steel. To ensure product specifications, a fractional order control is designed and validated on the system. A projection of the closed loop performance onto the quality assessment at end production line is also given in this paper.

Maximum Power Extraction Control Algorithm for Hybrid Renewable Energy System

In this research,a modified fractional order proportional integral derivate(FOPID)control method is proposed for the photovoltaic(PV)and thermoelectric generator(TEG)combined hybrid renewable energy system.The faster tracking and steady-state output are aimed at the suggested maximum power point tracking(MPPT)control technique.The derivative order number(μ)value in the improved FOPID(also known as PIλDμ)control structure will be dynamically updated utilizing the value of change in PV array voltage output.During the transient,the value ofμis changeable;it’s one at the start and after reaching the maximum power point(MPP),allowing for strong tracking characteristics.TEG will use the freely available waste thermal energy created surrounding the PVarray for additional power generation,increasing the system’s energy conversion efficiency.A high-gain DC-DC converter circuit is included in the system to maintain a high amplitude DC input voltage to the inverter circuit.The proposed approach’s performance was investigated using an extensive MATLAB software simulation and validated by comparing findings with the perturbation and observation(P&O)type MPPT control method.The study results demonstrate that the FOPID controller-based MPPT control outperforms the P&O method in harvesting the maximum power achievable from the PV-TEG hybrid source.There is also a better control action and a faster response.

Damping controller design based on FO-PID-EMA in VSC HVDC system to improve stability of hybrid power system

Wind energy sources have different structures and functions from conventional power plants in the power system.These resources can affect the exchange of active and reactive power of the network.Therefore,power system stability will be affected by the performance of wind power plants,especially in the event of a fault.In this paper,the improvement of the dynamic stability in power system equipped by wind farm is examined through the supplementary controller design in the high voltage direct current(HVDC)based on voltage source converter(VSC)transmission system.In this regard,impacts of the VSC HVDC system and wind farm on the improvement of system stability are considered.Also,an algorithm based on controllability(observability)concept is proposed to select most appropriate and effective coupling between inputs-outputs(IO)signals of system in different work conditions.The selected coupling is used to apply damping controller signal.Finally,a fractional order PID controller(FO-PID)based on exchange market algorithm(EMA)is designed as damping controller.The analysis of the results shows that the wind farm does not directly contribute to the improvement of the dynamic stability of power system.However,it can increase the controllability of the oscillatory mode and improve the performance of the supplementary controller.

Optimal FOPID Controllers for LFC Including Renewables by Bald Eagle Optimizer

In this study,a bald eagle optimizer(BEO)is used to get optimal parameters of the fractional-order proportional-integral-derivative(FOPID)controller for load frequency control(LFC).SinceBEOtakes only a very short time in finding the optimal solution,it is selected for designing the FOPID controller that improves the system stability and maintains the frequency within a satisfactory range at different loads.Simulations and demonstrations are carried out using MATLAB-R2020b.The performance of the BEOFOPID controller is evaluated using a two-zone interlinked power system at different loads and under uncertainty of wind and solar energies.The robustness of the BEO-FOPID controller is examined by testing its performance under varying system time constants.The results obtained by the BEOFOPID controller are compared with those obtained by BEO-PID and PID controllers based on recent metaheuristics optimization algorithms,namely the sine-cosine approach,Jaya approach,grey wolf optimizer,genetic algorithm,bacteria foraging optimizer,and equilibrium optimization algorithm.The results confirm that the BEO-FOPID controller obtains the finest result,with the lowest frequency deviation.The results also confirm that the BEOFOPID controller is stable and robust at different loads,under varying system time constants,and under uncertainty of wind and solar energies.

Fractional order modeling and control of dissimilar redundant actuating system used in large passenger aircraft

In this paper, a methodology has been developed to address the issue of force fighting and to achieve precise position tracking of control surface driven by two dissimilar actuators.The nonlinear dynamics of both actuators are first approximated as fractional order models. Based on the identified models, three fractional order controllers are proposed for the whole system. Two Fractional Order PID（FOPID） controllers are dedicated to improving transient response and are designed in a position feedback configuration. In order to synchronize the actuator dynamics, a third fractional order PI controller is designed, which feeds the force compensation signal in position feedback loop of both actuators. Nelder-Mead（N-M） optimization technique is employed in order to optimally tune controller parameters based on the proposed performance criteria. To test the proposed controllers according to real flight condition, an external disturbance of higher amplitude that acts as airload is applied directly on the control surface. In addition, a disturbance signal function of system states is applied to check the robustness of proposed controller. Simulation results on nonlinear system model validated the performance of the proposed scheme as compared to optimal PID and high gain PID controllers.

Fractional order adaptive robust formation control of multiple quad-rotor UAVs with parametric uncertainties and wind disturbances

In recent times,multiple Unmanned Aerial Vehicles(UAVs)are being widely utilized in several areas of applications such as agriculture,surveillance,disaster management,search and rescue operations.Degree of robustness of applied control schemes determines how accurate a swarm of UAVs accomplish group tasks.Formation and trajectory tracking controllers are required for the swarm of multiple UAVs.Factors like external environmental effects,parametric uncertainties and wind gusts make the controller design process as a challenging task.This article proposes fractional order formation and trajectory tacking controllers for multiple quad-rotors using Super Twisting Sliding Mode Control(STSMC)technique.To compensate the effects of the disturbances due to parametric uncertainties and wind gusts,Lyapunov function based adaptive controllers are formulated.Moreover,Lyapunov theorem is used to guarantee the stability of the proposed controllers.Three types of controllers,namely fixed gain STSMC and fractional order Adaptive Super Twisting Sliding Mode Control(ASTSMC)methods are tested for the swarm of UAVs by performing the numerical simulations in MATLAB/Simulink environment.From the presented results,it is verified that in presence of wind disturbances and parametric uncertainties,the proposed fractional order ASTSMC technique showed improved robustness as compared to the fixed gain STSMC and integer order ASTSMC.

Design of internal model control based fractional order PID controller

This article presents a design of the internal model control （IMC） based single degree of freedom （SDF） fractional order （FO） PID controller with a desired bandwidth specification for a class of fractional order system （FOS）. The drawbacks of the SDF FO-IMC are eliminated with the help of the two-degree of freedom （TDF） FO PID controller. The robust stability and robust performance of the designed controller are analyzed using an example.

Improved Clamped Diode Based Z-Source Network for Three Phase Induction Motor

The 3Φinduction motor is a broadly used electric machine in industrial applications,which plays a vital role in industries because of having plenty of beneficial impacts like low cost and easiness but the problems like decrease in motor speed due to load,high consumption of current and high ripple occurrence of ripples have reduced its preferences.The ultimate objective of this study is to control change in motor speed due to load variations.An improved Trans Z Source Inverter(ΓZSI)with a clamping diode is employed to maintain constant input voltage,reduce ripples and voltage overshoot.To operate induction motor at rated speed,different controllers are used.The conventional Proportional-Inte-gral(PI)controller suffers from high settling time and maximum peak overshoot.To overcome these limitations,Fractional Order Proportional Integral Derivative(FOPID)controller optimized by Gray Wolf Optimization(GWO)technique is employed to provide better performance by eliminating maximum peak overshoot pro-blems.The proposed speed controller provides good dynamic response and controls the induction motor more effectively.The complete setup is implemented in MATLAB Simulation to verify the simulation results.The proposed approach provides optimal performance with high torque and speed along with less steady state error.

Research on Stick-Slip Vibration Suppression Method of Drill String Based on Machine Learning Optimization

During the drilling process,stick-slip vibration of the drill string is mainly caused by the nonlinear friction gen-erated by the contact between the drill bit and the rock.To eliminate the fatigue wear of downhole drilling tools caused by stick-slip vibrations,the Fractional-Order Proportional-Integral-Derivative(FOPID)controller is used to suppress stick-slip vibrations in the drill string.Although the FOPID controller can effectively suppress the drill string stick-slip vibration,its structure isflexible and parameter setting is complicated,so it needs to use the cor-responding machine learning algorithm for parameter optimization.Based on the principle of torsional vibration,a simplified model of multi-degree-of-freedom drill string is established and its block diagram is designed.The continuous nonlinear friction generated by cutting rock is described by the LuGre friction model.The adaptive learning strategy of genetic algorithm(GA),particle swarm optimization(PSO)and particle swarm optimization improved(IPSO)by arithmetic optimization(AOA)is used to optimize and adjust the controller parameters,and the drill string stick-slip vibration is suppressed to the greatest extent.The results show that:When slight drill string stick-slip vibration occurs,the FOPID controller optimized by machine learning algorithm has a good effect on suppressing drill string stick-slip vibration.However,the FOPID controller cannot get the drill string system which has fallen into serious stick-slip vibration(stuck pipe)out of trouble,and the machine learning algorithm is required to mark a large amount of data on adjacent Wells to train the model.Set a reasonable range of drilling parameters(weight on bit/drive torque)in advance to avoid severe stick-slip vibration(stuck pipe)in the drill string system.

Control of a 3-RRR Planar Parallel Robot Using Fractional Order PID Controller

3-RRR planar parallel robots are utilized for solving precise material-handling problems in industrial automation applications.Thus,robust and stable control is required to deliver high accuracy in comparison to the state of the art.The operation of the mechanism is achieved based on three revolute(3-RRR)joints which are geometrically designed using an open-loop spatial robotic platform.The inverse kinematic model of the system is derived and analyzed by using the geometric structure with three revolute joints.The main variables in our design are the platform base positions,the geometry of the joint angles,and links of the 3-RRR planar parallel robot.These variables are calcula ted based on Cayley-Menger determinants and bilateration to det ermine the final position of the platform when moving and placing objects.Additionally,a proposed fractional order proportional integral derivative(FOPID)is optimized using the bat optimization algorithm to control the path tracking of the center of the 3-RRR planar parallel robot.The design is compared with the state of the art and simulated using the Matlab environment to validate the effectiveness of the proposed controller.Furthermore,real-time implementation has been tested to prove that the design performance is practical.