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.

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%.

Performance of the Boost Chopper, Comparative Study between PI Control and Neural Control to Regulate Its Output Voltage

In this study, we investigate the performance of a boost converter regulating its output voltage using two control methods: Proportional-Integral (PI) control and neural control. Both methods are implemented on a simulation platform (Matlab/Simulink) and evaluated in terms of accuracy, response speed, and robustness to disturbances. Indeed, the output voltage of converters exhibits imperfections that require a control method to optimize efficiency when applying a variable load. Results show that neural control offers superior performance in terms of accuracy and response time, with faster and more precise regulation of the output voltage. On the other hand, PI control proves to be more robust against disturbances. These findings can help guide the selection of the appropriate control method for a boost converter based on the specific requirements of each application.

Multivariable PI Type Generalized Predictive Control

This paper presents a multivariable generalized predictive controller with proportion and integration structure by modifying the quadratic criterion of the usual MGPC. The control performance has been improved greatly. The effectiveness of the controller is demonstrated by the simulation result.

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.

PI force feedback control for large flexible structure vibration with active tendons

Active tendon, consisting of a displacement actuator and a collocated force sensor, was first presented by Preumont and his co-workers to attenuate the vibration of large flexible space structures, and the control algorithm adopted by them was integral force feedback. This paper presents a new proportional-integral （PI） force feedback algorithm to achieve larger damping ratios for the structure without the requirement of structure model. Stability of the control system is shown, and simulations of a structure similar to JPL-MPI demonstrate the effectiveness of the proposed algorithm for vibration control of space structures.

Performance Analysis of PI and Fuzzy Control for Modified LCC Resonant Converter Incorporating Boost Converter

In this paper, the modified LCC type of series-parallel Resonant Converter (RC) was designed and state-space modeling analysis was implemented. In this proposed converter, one leg of full bridge diode rectifier is replaced with Synchronous Rectifier (SR) switches. The proposed LCC converter is controlled using frequency modulation in the nominal state. During hold-up time, the SRswitches control is changed from in-phase to phase-shifted gate signal to obtain high DC voltage conversion ratio. Furthermore, the closed loop PI and fuzzy provide control on the output side without decreasing the switching frequency. The parameter such as conduction loss on primary and secondary side, switching loss, core and copper also reduced. Simultaneously, the efficiency is increased about 94.79 is realized by this scheme. The proposed converter with an input of 40 V is built to produce an output of 235 V with the help of ZVS boost converter [1] even under line and load disturbances. As a comparison, the closed loop fuzzy controller performance is feasible and less sensitive than PI controller.

PI tuning for large dead-time processes with a new robustness specification

A simple PI controller tuning method for large dead-time processes is presented. First, a first-order plus dead-time model is identified on the basis of relay feedback experiments, which Nyquist curve is very close to that of large dead-time processes over a wide frequency range. With the model available, PI controller is designed with a new robust specification. Simulation examples show the effectiveness and feasibility of the presented PI tuning method for large dead-time processes.

PI control based on fuzzy set-point weighting tracking for hydraulic crane boom system

A PI control strategy based on fuzzy set-point weighting following was proposed for the active damping control of a hydraulic crane boom system （HCBS）. Two valve-controlled PI controllers, which include a proportional feedforward controller based on fuzzy set-point weighting following and a limited semi-integrator（LSI）, are designed respectively. LSI is used to limit output signal and to prevent wind up at the low frequency of the spectrum. By using a range camera and an electronic feedback control, the tip damping on the HCBS can be adjusted artificially. A collaborative control simulation technique of HOPSAN and MATLAB/SIMULINK is applied to the controller design. Simulation results show that the proposed PI control system has less overshoot as well as faster response. The tip damping on the HCBS during operation is improved.

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.

Pressure Gradient Control Strategies Based on Disturbance Rejection for Typical Pharmaceutical Cleanrooms

Keeping pressure gradient is an excellent approach to prevent the reveal of airflow direction and cross infection in manufacturing circumstances of pharmaceutical cleanrooms, thus how to keep cleanroom’s pressure is critical. In the paper, we study a positive pressure pharmaceutical cleanroom system which is composed by a cleanroom and an airlock. We divide the system’s disturbances into step disturbance, ramp disturbance and sine wave disturbance. We design its pressure gradient control strategies, including CAV control, PID control and active-disturbance-rejection-control. We build the system’s model and make simulations based on Matlab/Simulink software platform. Results show that active-disturbance-rejection-control algorithm has good capabilities for shorter responding time and lower overshot of the pressure gradient. The results reveal that active-disturbance-rejection-control method has good control performances in responding time, accuracy and disturbance rejection.

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.

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.

Sliding Mode Control Approach with Integrated Disturbance Observer for PMSM Speed System

The research on high-performance vector control of permanent magnet synchronous motor(PMSM)drive system plays an extremely important role in electrical drive system.To further improve the speed control performance of the system,a fast non-singular end sliding mode(FNTSM)surface function based on traditional NTSM control is developed.The theoretical analysis proves that the FNTSM surface function has a faster dynamic response and more finite-time convergence.In addition,for the self-vibration problem caused by high sliding mode switching gain,an FNTSM control method with anti-disturbance capability was designed based on the linear disturbance observer(DO),i.e.the FNTSMDO method was employed to devise the PMSM speed regulator.The comparative simulation and experiment results with traditional PI control and NTSM control methods indicate that the FNTSMDO method could improve the dynamic performance and anti-interference of the system.

Speed Regulation Method Using Genetic Algorithm for Dual Three-phase Permanent Magnet Synchronous Motors

Dual three-phase Permanent Magnet Synchronous Motor(DTP-PMSM)is a nonlinear,strongly coupled,high-order multivariable system.In today’s application scenarios,it is difficult for traditional PI controllers to meet the requirements of fast response,high accuracy and good robustness.In order to improve the performance of DTP-PMSM speed regulation system,a control strategy of PI controller based on genetic algorithm is proposed.Firstly,the basic mathematical model of DTP-PMSM is established,and the PI parameters of DTP-PMSM speed regulation system are optimized by genetic algorithm,and the modeling and simulation experiments of DTP-PMSM control system are carried out by MATLAB/SIMULINK.The simulation results show that,compared with the traditional PI control,the proposed algorithm significantly improves the performance of the control system,and the speed output overshoot of the GA-PI speed control system is smaller.The anti-interference ability is stronger,and the torque and double three-phase current output fluctuations are smaller.

Modeling, Analysis and Simulation of a High-Efficiency Battery Control System

This paper explains step-by-step modeling and simulation of the full circuits of a battery control system and connected together starting from the AC input source to the battery control and storage system.The three-phase half-controlled rectifier has been designed to control and convert the AC power into DC power.In addition,two types of direct current converters have been used in this paper which are a buck and bidirectional DC/DC converters.These systems adjust the output voltage to be lower or higher than the input voltage.In the buck converters,the main switch operates in conduction or cut-off mode and is triggered by a Pulse-Width Modulated(PWM)signal.The output and input voltage levels ratio are used to calculate thePWMsignal’s duty cycle.Therefore,the duty cycle indicates the operation mode of the converter in steady-state operation.In this study,we analyze and control of a buck converter with the PWM signal.Besides,the bidirectional DC/DC converter has been achieved and optimized by PI control methods to control the battery charging and discharging modes.The simulation has been applied via the Matlab/Simulink environment.The results show the activity of each part of the designed circuits starting from the converters and the battery control system in charge and discharge modes.

Harmonics Mitigation Using MMC Based UPFC and Particle Swarm Optimization

The application of non-linear loads in the power electronic device causes serious harmonic issues in the power system since it has the intrinsic prop-erty of retrieving harmonic current and reactive power from Alternating Current(AC)supply that leads to voltage instability.To maintain a reliable powerflow in the power system,an innovative Unified Power Flow Converter(UPFC)is uti-lized in this proposed approach.The conventional series converter is replaced with the Modular Multilevel Converter(MMC)that improves the power handling capability and achieves higher modular level with minimized distortions.The shunt compensator assists in minimizing the voltagefluctuations and maximizing the voltage stability under different load constraints.The Direct Quadrature(DQ)theory is utilized in this study to separate the harmonic components by generating reference frame current.The Proportional Integral(PI)controller aids in maintain-ing the direct current potential difference in the constant mode whereas the Pulse Width Modulation(PWM)generator helps in delivering optimized output to the MMC.The gain parameters of PI controller are optimized with the aid of employ-ing Particle Swarm Optimization(PSO).The entire work is validated using MATLAB simulink and the obtained outcomes proves that this new UPFC is highly beneficial in minimizing the distortions with reduced Total Harmonic Distortion(THD)of 2.21%.

Optimized Power Factor Correction for High Speed Switched Reluctance Motor

The Power Factor Correction(PFC)in Switched Reluctance(SR)motor is discussed in this article.The SR motors are applicable for multiple applications like electric vehicles,wind mills,machineries etc.The doubly salient structure of SR motor causes the occurrence of torque ripples,which affects the power factor of the motor.To improve the power quality,the power factor has to be corrected and the ripples have to be minimized.In order to achieve these objectives,a novel power factor correction(PFC)method is proposed in this work.Here,the conventional Diode Bridge Rectifier(DBR)is replaced by a Bridgeless Hybrid Resonant(HR)converter,which assists in improvising the output in a wider range.The converter is chosen because of having variety of beneficial measures including high gain.The converter’s output is fed to the SR motor by means of an asymmetric Bridge Resonant(BR)converter.The proposed converter operates in continuous mode of conduction with the switching frequency of 10 KHz.A hysteresis current controller and Proportional Integral(PI)controller are utilized for reducing the harmonics in the source current along with the regulation of output voltage.In addition,the speed control of SR motor is accomplished by means of the Whale Optimization Algorithm(WOA)assisted PI controller.The proposed methodology is effective for the control of unity power factor,torque and current ripples.The Total Harmonic Distortion(THD)of the source current is also minimized,which suits the standard of International Electrotechnical Comission IEC 61000-3-2.By this methodology,the power factor of 0.99 is achieved with 97%efficiency and 3.92%THD.The proposed methodology is validated in simulation by MATLAB and in hardware by FPGA Spartan 6E.