Hybrid Optimized PI Controller Design for Grid Tied PV Based Electric Vehicle

Nowadays,researchers are becoming increasingly concerned about developing a highly efficient emission free transportation and energy generation system for addressing the pressing issue of environmental crisis in the form of pollution and climate change.The introduction of Electric Vehicles(EVs)solves the challenge of emission-free transportation while the necessity for decarbonized energy production is fulfilled by the installation and expansion of solar-powered Photovoltaic(PV)systems.Hence,this paper focuses on designing an effective PV based EV charging system that aids in stepping towards the achievement of a pollution free future.For overcoming the inherent intermittency associated with PV,a novel DC-DC converter is designed by integrating both Trans Z-source con-verter and Luo converter,which offers remarkable benefits of high conversion range,lesser voltage stress and excellent efficiency.A novel robust Lion Grey Wolf Optimized Proportional Integral(LGWO-PI)controller is designed for sig-nificantly strengthening the operation of the integrated converter in terms of peak overshoot,Total Harmonic Distortion(THD)and settling time.A 3’Voltage Source Inverter(VSI)is employed to convert the stable DC output from the PV sys-tem to AC,which is then used for driving the Brushless Direct Current Motor(BLDC)motor of EV.The speed of the BLDC is regulated using a PI controller.The BLDC motor gets the power supply from the grid during the unavailability of PV based power supply.The grid is integrated with the designed EV charging system through a 1’VSI and the process of grid voltage synchronization is carried out with the application of PI controller.The simulation for evaluating the operation of the presented EV charging system is done using MATLAB and the attained out-comes have validated that this introduced methodology delivers enhanced perfor-mance with optimal efficiency of 97.6%and lesser THD of 2.1%.

DC–DC Converter with Pi Controller for BLDC Motor Fuzzy Drive System

The Brushless DC Motor drive systems are used widely with renewable energy resources.The power converter controlling technique increases the performance by novel techniques and algorithms.Conventional approaches are mostly focused on buck converter,Fuzzy logic control with various switching activity.In this proposed research work,the QPSO(Quantum Particle Swarm Optimization algorithm)is used on the switching state of converter from the generation unit of solar module.Through the duty cycle pulse from optimization function,the MOSFET(Metal-Oxide-Semiconductor Field-Effect Transistor)of the Boost converter gets switched when BLDC(Brushless Direct Current Motor)motor drive system requires power.Voltage Source three phase inverter and Boost converter is controlled by proportional-integral(PI)controller.Based on the BLDC drive,the load utilized from the solar generating module.Experimental results analyzed every module of the proposed grid system,which are solar generation utilizes the irradiance and temperature depends on this the Photovoltaics(PV)power is generated and the QPSO with Duty cycle switching state is determined.The Boost converter module is boost stage based on generation and load is obtained.Single Ended Primary Inductor Converter(SEPIC)and Zeta converter model is compared with the proposed logic;the proposed boost converter achieves the results.Three phase inverter control,PI,and BLDC motor drive results.Thus the proposed grid model is constructed to obtain the better performance results than most recent literatures.Overall design model is done by using MATLAB/Simulink 2020a.

Gaussian PI Controller Network Classifier for Grid-Connected Renewable Energy System

Multi-port converters are considered as exceeding earlier period decade owing to function in a combination of different energy sources in a single processing unit.Renewable energy sources are playing a significant role in the modern energy system with rapid development.In renewable sources like fuel combustion and solar energy,the generated voltages change due to their environmental changes.To develop energy resources,electric power generation involved huge awareness.The power and output voltages are plays important role in our work but it not considered in the existing system.For considering the power and voltage,Gaussian PI Controller-Maxpooling Deep Convolutional Neural Network Classifier(GPIC-MDCNNC)Model is introduced for the grid-connected renewable energy system.The input information is collected from two input sources.After that,input layer transfer information to hidden layer 1 fuzzy PI is employed for controlling voltage in GPIC-MDCNNC Model.Hidden layer 1 is transferred to hidden layer 2.Gaussian activation is employed for determining the output voltage with help of the controller.At last,the output layer offers the last value in GPIC-MDCNNC Model.The designed method was confirmed using one and multiple sources by stable and unpredictable input voltages.GPIC-MDCNNC Model increases the performance of grid-connected renewable energy systems by enhanced voltage value compared with state-of-the-art works.The control technique using GPIC-MDCNNC Model increases the dynamics of hybrid energy systems connected to the grid.

Genetic algorithm tuned PI controller on PMSM simplified vector control

A simple control structure in servo system is occasionally needed for simple industrial application which precise and high control performance is not exessively important so that the cost production can be reduced efficiently. Simplified vector control, which has simple control structure, is utilized as the permanent magnet synchronous motor control algorithm and genetic algorithm is used to tune three PI controllers used in simplified vector control. The control performance is obtained from simulation and investigated to verify the feasibility of the algorithm to be applied in the real application. Simulation results show that the speed and torque responses of the system in both continuous time and discrete time can achieve good performances. Furthermore, simplified vector control combined with genetic algorithm has a similar perfofmance with conventional field oriented control algorithm and possible to be realized into the real simple application in the future.

Optimized PI controller for 7-level inverter to aid grid interactive RES controller

With the huge rise of energy demand,the power system in the current era is moving to a new standard with increased access to renewable energy sources(RESs)integrated with distribution generation(DG)network.The RESs necessitate interfaces for controlling the power generation.The multilevel inverter(MLI)can be exploited for RESs in two diverse modes,namely,the power generation mode(stand-alone mode),and compensator mode(statcom).Few works have been carried out in optimization of controller gains with the load variations of the single type such as reactive load variation in different cases.Nevertheless,this load type may be unbalanced hence,to overcome such issues.So,a sophisticated optimization algorithm is important.This paper aims to introduce a control design via an optimization assisted PI controller for a 7-level inverter.In the present technique,the gains of the PI controller are adjusted dynamically by the adopted hybrid scheme,grey optimizer with dragon levy update(GD-LU),based on the operating conditions of the system.Here,the gains are adjusted such that the error between the reference signal and fault signal should be minimal.Thus,better dynamic performance could be attained by the present optimized PI controller.The proposed algorithm is the combined version of grey wolf optimization(GWO)and dragonfly algorithm(DA).Finally,the performance of the proposed work is compared and validated over other state-of-the-art models concerning error measures.

Synthesis of Fractional-order PI Controllers and Fractional-order Filters for Industrial Electrical Drives

This paper introduces an electrical drives control architecture combining a fractional-order controller and a setpoint pre-filter. The former is based on a fractional-order proportional-integral(PI) unit, with a non-integer order integral action, while the latter can be of integer or non-integer type. To satisfy robustness and dynamic performance specifications, the feedback controller is designed by a loop-shaping technique in the frequency domain. In particular, optimality of the feedback system is pursued to achieve input-output tracking. The setpoint pre-filter is designed by a dynamic inversion technique minimizing the difference between the ideal synthesized command signal(i.e., a smooth monotonic response) and the prefilter step response. Experimental tests validate the methodology and compare the performance of the proposed architecture with well-established control schemes that employ the classical PIbased symmetrical optimum method with a smoothing pre-filter.

BELBIC Tuned PI Controller Based Chopper Driven PMDC Motor

In orthopaedic surgeries, permanent magnet DC motors are used to drill the bone and fix the screws. The Motor drive employs an inner current and outer speed control loop with a conventional or modern controller. To enhance the performance of the drive, this paper proposes a Brain Emotional Logic Based Intelligent Controller based chopper drive. The proposed drive scheme has been simulated using Matlab/Simulink and physically realized for validation. A comparative analysis has been made between the conventional PI controller based drive and the proposed system in order to prove that the proposed scheme has an edge over the traditional PI controller scheme counterpart.

Design of Soft Computing Based Optimal PI Controller for Greenhouse System

Greenhouse system (GHS) is the worldwide fastest growing phenomenon in agricultural sector. Greenhouse models are essential for improving control efficiencies. The Relative Gain Analysis (RGA) reveals that the GHS control is complex due to 1) high nonlinear interactions between the biological subsystem and the physical subsystem and 2) strong coupling between the process variables such as temperature and humidity. In this paper, a decoupled linear cooling model has been developed using a feedback-feed forward linearization technique. Further, based on the model developed Internal Model Control (IMC) based Proportional Integrator (PI) controller parameters are optimized using Genetic Algorithm (GA) and Particle Swarm Optimization (PSO) to achieve minimum Integral Square Error (ISE). The closed loop control is carried out using the above control schemes for set-point change and disturbance rejection. Finally, closed loop servo and servo-regulatory responses of GHS are compared quantitatively as well as qualitatively. The results implicate that IMC based PI controller using PSO provides better performance than the IMC based PI controller using GA. Also, it is observed that the disturbance introduced in one loop will not affect the other loop due to feedback-feed forward linearization and decoupling. Such a control scheme used for GHS would result in better yield in production of crops such as tomato, lettuce and broccoli.

Comparative Study of Different Decoupling Schemes for TITO Binary Distillation Column via PI Controller

This paper presents a comparative study of different decoupling control schemes for a two-input, two-output(TITO) binary distillation column via proportional-integral(PI)controller. The key idea behind this paper is designing two novel fuzzy decoupling schemes that depend on human knowledge,instead of the system mathematical model used in conventional decoupling schemes. Based on conventional and inverted decoupling schemes, fuzzy and inverted fuzzy decoupling schemes are developed. The control effect is compared using simulation results for the proposed two schemes with conventional decoupling and inverted decoupling. The proposed fuzzy decoupling schemes are easy to realize and simple to design, besides they have a good decoupling capability. Two methods are used to prove asymptotic stability of each loop and the entire closed-loop system by applying the proposed fuzzy decoupling-based PI controller.The Wood and Berry model of a binary distillation column is used to illustrate the applicability of the proposed schemes.

Age-of-information-aware PI controller for load frequency control

Open communication system in modern power systems brings concern about information staleness which may cause power system frequency instability.The information staleness is often characterized by communication delay.However,communication delay is a packet-centered metric and cannot reflect the requirement of information freshness for load frequency control(LFC).This paper introduces the age of information(AoI),which is more compre-hensive and informative than the conventional communication delay modeling method.An LFC controller and com-munication are integrated into the design for LFC performance improvement.An AoI-aware LFC model is formulated first,and considering each allowable update period of the smart sensor,different AoI-aware PI controllers are then designed according to the exponential decay rate.The right AoI-aware controller and update period are selected according to the degree of frequency fluctuation of the power system.Case studies are carried out on one-area and two-area power systems.The results show the superior performance of the AoI-aware controllers in comparison to the delay-dependent controllers.

Consensus Analysis of Fractional Multi-Agent Systems with Delayed Distributed PI Controller

The consensus problem for fractional multi-agent systems(MASs)with time delay is considered.The distributed fractional proportional-integral(PI)-type controller is designed so that the consensus of the proposed systems is achieved.Moreover,explicit condition to determine the crossing directions is developed.The results show that with the increase of time delay,the closed-loop system has two different dynamic characteristics:From consensus to nonconsensus and consensus switching.Furthermore,delay margin within which consensus of MASs will always hold is determined.The results should provide useful guidelines in the consensus analysis and in the analytical design of the distributed controllers.

Grid power quality enhancement using an ANFIS optimized PI controller for DG

Grid frequency variation causes phase angle deviation in current with respect to voltage.This is sensed at the phase-locked loop in the controller.In past studies the effect of grid frequency variation is neglected while designing the controller for power quality restoration.When modern grids are connected to large numbers of non-linear loads and various types of distributed generation(DG),it results in continuous variation in grid frequency.Thus it is necessary to consider the grid frequency variation for effective power quality restoration.However,tuning of conventional PI controller gains considering frequency variation is very difficult.Thus it is necessary to develop an adaptive intelligent nonlinear controller to tackle the effects of frequency variation,voltage distortion and non-linear load simultaneously.This paper presents the importance of considering the effects of the frequency variation,grid voltage distortion and non-linear load,while designing and deploying a controller for power quality restoration.The proposed controller supplies power to local load as well as transferring surplus power to the grid from DG along with the additional ben-efit of improving grid power quality.A DG with an ANFIS optimized PI current controller for power quality enhance-ment is proposed.The method is economical as it requires no additional hardware.Results are compared with PI,PI-RC and fuzzy current controllers to validate the effectiveness of the proposed controller.

Analysis of finite-time regulation property of biomolecular PI controller

In practical applications of dynamic DNA nanotechnology,a biomolecular controller is required for maintaining the operation of the molecular actuator at a desired condition based on the information from molecular sensors.By making use of the DNA strand displacement mechanism as a"programming language"in the controller design,a biomolecular PI controller has been proposed.However,this PI control system has been verified only at the simulation level,and a theoretical regulation analysis is still required.Accordingly,in this study,we perform a rigorous regulation analysis of the biomolecular PI control system.Specifically,we theoretically prove that the output signal approaches the target level at a quasi-steady state.To this end,we apply the concept of finite-time regulation property to the biomolecular PI control system.

Comparative Analysis between Conventional PI, Fuzzy Logic and Artificial Neural Network Based Speed Controllers of Induction Motor with Considering Core Loss and Stray Load Loss

Most of the controllers of IM （induction motor） for industrial applications have been designed based on PI controller without consideration of CL （core loss） and SLL （stray load loss）. To get the precise performances of torque as well as rotor speed and flux, the above mentioned losses should be considered. Conventional PI controller has overshoot effect at the transient period of the speed response curve. On the other hand, fuzzy logic and ANN （artificial neural network） based controllers can minimize the overshoot effect at the transient period because they have the abilities to deal with the nonlinear systems. In this paper, a comparative analysis is done between PI, fuzzy logic and ANN based speed controllers to find the suitable control strategy for IM with consideration of CL and SLL. The simulation analysis is done by using Matlab/Simulink software. The simulation results show that the fuzzy logic based speed controller gives better responses than ANN and conventional PI based speed controllers in terms of rotor speed, electromagnetic torque and rotor flux of IM.

IMC based robust PID controller tuning for disturbance rejection

It is well-known that the IMC-PID controller tuning gives fast and improved set point response but slow disturbance rejection. A modification has been proposed in IMC-PID tuning rule for the improved disturbance rejection. For the modified IMC-PID tuning rule, a method has been developed to obtain the IMC-PID setting in closed-loop mode without acquiring detailed information of the process. The proposed method is based on the closed-loop step set point experiment using a proportional only controller with gain K_(c0). It is the direct approach to find the PID controller setting similar to classical Ziegler-Nichols closed-loop method. Based on simulations of a wide range of first-order with delay processes, a simple correlation has been derived to obtain the modified IMC-PID controller settings from closed-loop experiment. In this method, controller gain is a function of the overshoot obtained in the closed loop set point experiment. The integral and derivative time is mainly a function of the time to reach the first peak(overshoot). Simulation has been conducted for the broad class of processes and the controllers were tuned to have the same degree of robustness by measuring the maximum sensitivity, Ms, in order to obtain a reasonable comparison. The PID controller settings obtained in the proposed tuning method show better performance and robustness with other two-step tuning methods for the broad class of processes. It has also been applied to temperature control loop in distillation column model. The result has been compared to the open loop tuning method where it gives robust and fast response.

Robust PID controller design for time delay processes with peak of maximum sensitivity criteria

The motivation of this work is to obtain single PI/PID tuning formula for different types of processes with enhanced disturbance rejection performance. The proposed tuning formula consistently gives better performance in comparison to several well-known methods at the same degree of robustness for stable, integrating and unstable processes. For the selection of the closed-loop time constant(τc), a guideline is provided over a broad range of time-delay/time-constant ratios on the basis of the peak of maximum sensitivity(Ms). An analysis has been performed for the uncertainty margin with the different process parameters for the robust controller design. It gives the guideline of the Ms-value settings for the PI controller designs based on the process parameters uncertainty. Furthermore, a relationship has been developed between Ms-value and uncertainty margin with the different process parameters(k, τ and θ). Simulation study has been conducted for the broad class of processes and the controllers are tuned to have the same degree of robustness by measuring the maximum sensitivity, Ms, in order to obtain a reasonable comparison.

PI controller relay auto-tuning using delay and phase margin in PMSM drives

This paper presents an auto-tuning method for a proportion plus integral（PI） controller for permanent magnet synchronous motor（PMSM） drives, which is supposed to be embedded in electro-mechanical actuator（EMA） control module in aircraft. The method, based on a relay feedback with variable delay time, explores different critical points of the system frequency response.The Nyquist points of the plant can then be derived from the delay time and filter time constant.The coefficients of the PI controller can then be obtained by calculation while shifting the Nyquist point to a specific position to obtain the required phase margin. The major advantage of the autotuning method is that it can provide a series of tuning results for different system bandwidths and damping ratios, corresponding to the specification for delay time and phase margin. Simulation and experimental results for the PMSM controller verify the performance of both the current loop and the speed loop auto-tuning.

Sliding Mode and PI Controllers for Uncertain Flexible Joint Manipulator

This paper is dealing with the problem of tracking control for uncertain flexible joint manipulator robots driven by brushless direct current motor(BDCM). Flexibility of joint in the manipulator constitutes one of the most important sources of uncertainties. In order to achieve high performance, all parts of the manipulator including actuator have been modeled. To cancel the tracking error, a hysteresis current controller and speed controllers have been developed. To evaluate the effectiveness of speed controllers, a comparative study between proportional integral(PI) and sliding mode controllers has been performed. Finally, simulation results carried out in the Matlab simulink environment demonstrate the high precision of sliding mode controller compared with PI controller in the presence of uncertainties of joint flexibility.

Analytical design of PI controller for AQM with robustness adjustability

Based on a linearized TCP/AQM model,a new proportional integral(PI)controller design approach is proposed.This analytical approach applies H_(∞) optimization and internal model control(IMC)theory to design active queue management(AQM)routers that support transmission control protocol(TCP)flows.The most important feature of the proposed scheme lies in that it can be explicitly tuned with a single parameter for the trade-off between performance and stability of the AQM control system.It is thus flexible and easy to use in design.The proposed method and the designed PI controller are verified and compared with other existing AQM schemes using ns-2 simulator.The results show the advantages of the new PI controller design approach for AQM routers supporting TCP flows.

A Novel Asymmetric Three-Phase Cascaded 21 Level Inverter Fed Induction Motor Using Multicarrier PWM with PI and Fuzzy Controller

Multilevel inverters are gaining popularity in high power applications. This paper proposes a new ladder type structure of cascaded three-phase multilevel inverter with reduced number of power semiconductor devices which is used to drive the induction motor. The ultimate aim of the paper is to produce multiple output levels with minimum number of semiconductor devices. This paper uses only 11 switches along with 3 diodes and 4 asymmetrical sources to produce an output voltage of 21 levels. The modulation technique plays a major role in commutation of the switches. Here we implement the multicarrier level shifting pulse width modulation technique to produce the commutation signals for the inverter. The proposed multilevel inverter is used to drive the three-phase induction motor. The mathematical modeling of three-phase induction motor is done using Simulink. Furthermore the PI and fuzzy logic controllers are also used to produce the reference waveform of the level shifting technique which in turn produces the commutation signals of the proposed multilevel converter. The controllers are used to control the speed of the induction motor. The effectiveness of the proposed system is proved with the help of simulation. The simulation is performed in MATLAB/Simulink. From the simulation results, it shows that the proposed multilevel inverter works properly to generate the multilevel output waveform with minimum number of semiconductor devices. The PI and fuzzy logic controller performances are evaluated using the results which indicate that with the help of controllers the harmonics has been reduced and the speed control of induction motor is achieved under different loading conditions.