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.

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.

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.

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.

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.

Analysis of the effect on control systems of order variation for fractional-orderPI~λD~μcontrollers

This paper is concerned with fractional-order PI^λ D^u controllers. The definitions and properties of fractional calculus are introdueed. The mathematical descriptions of a fraetional-order controller and fractionalorder control systems are outlined. The effects on control systems of order variation for fractional-order PI^λ D^u controllers are investigated by qualitative analysis and simulation. The conclusions and simulation examples are given. The results show the fraetional-order PI^λ D^u controller is not sensitive to variation of its order.

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.

无人驾驶农机装备的模糊PI-LQR转向控制算法

无人驾驶农机装备转向系统处于小流量、小角度控制时会出现非线性和时滞,这会导致转向控制超调或者控制时滞,进而导致无法快速准确地跟踪到路径预瞄点。针对这个问题,本文提出了一种模糊比例积分-线性二次型调节器(PI-LQR)数据融合的内外环控制算法。该算法以模糊PI控制为内环,基于转角误差和转角误差变化率,通过模糊逻辑运算自适应调节PI参数,进行转向角度的闭环控制。以LQR控制为外环,基于农机装备XY-横摆角控制,融合内环的转角误差,进一步提升无人驾驶农机装备转向的精准控制。Carsim和Matlab/Simulink联合仿真表明:通过100 m长的双移线路径下,最大横向误差为0.18 m,最大横向摆角误差为0.067 rad。实车测试表明:通过100 m长的双移线路径下,最大横向误差0.26 m,相较于PID纯跟踪控制算法,最大横向误差减少了0.19 m。

Satisfactory PI-P Controller Design for High-order Servo System

The paper presents an output feedback controller design method for high-order servo system with the constraints of multiple indices by using satisfactory control theory. The control strategy is to convert transfer-function form of two-loop servo system into state-space form and assign the system poles in the specified region and H_∞ attenuation degree in the given range with the Riccati matrix inequality so that the closed-loop system has good dynamics and robust quality. A numeric example is given to show the effectiveness of the proposed approach.

Adjusting the Parameters of PI Regulator in All-electrical Tank Gun Control System by Computer Program

Both the traverse subsystem and the elevation subsystem of the all-electrical tank gun control system are composed of electrical drive control system respectively. The parameters of PI regulator in these electrical drive control systems affect the performance of the control system seriously. Up to now, there is not a simple and practical method for choosing regulator parameters, which are usually determined by repeated and continual readjustment. This method is low efficient, and the parameters got are not always optimal. A method for on-line adjusting the parameters of PI regulator in the electrical drive control system by computer program is introduced in this paper. The function of adjusting PI parameters of the electrical drive control system is realized by PC program written by VC++ and controlling program written by assemble language and by the communication between PC and DSP completed by the control MSCOMM in VC++6.0. The method as mentioned above which is applied for an all-electrical tank gun control system under development is proved very available, a better performance might be obtained for the all-electrical tank gun control system easily.

基于PI控制的内燃动车组柴油机恒功率控制技术

柴油机在非恒功率输出时,不仅燃料效率低,而且可能会产生较大的机械应力,导致机械部件的磨损和破坏。为确保内燃动车组柴油机高效运行,基于内燃动车组柴油发电机组恒功率输出的运行模式,文章提出了一种比例-积分控制方法,实现了负载侧牵引系统功率稳定跟随柴油发电机组的输出功率目标值,通过负载侧恒功率运行保障发电机组的恒功率稳定输出,从而提高柴油机燃油经济性。经过仿真及试验测试验证,采用此控制方法,负载功率稳态波动在±2%以内,实现了内燃动车组柴油机恒功率运行及负载功率对目标值的实时跟随。

基于预见与PI补偿的不确定非线性系统鲁棒滑模控制

针对一类匹配不确定非线性连续时间系统,本文提出一种具有预见与PI补偿的鲁棒滑模控制设计方法.首先,为提高系统的跟踪性能和鲁棒性,在常规的滑模控制基础上,引入前馈预见与PI控制器.然后,通过增加扩展系统状态变量方法,构造一个包含可预见的目标信号的不确定增广系统,并将控制器的设计问题转化为增广系统的稳定性问题.在此基础上,针对标称增广系统,应用最优控制原理,设计最优预见PI控制器;针对不确定增广系统,应用变结构控制方法,设计最优预见PI滑模控制器,实现不确定系统的鲁棒调节.所得结果推广和包含了已有文献中的一些结果.最后,数值仿真验证所提方法的有效性.

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.

Application of Diagonal Recurrent Neural Network toDC Motor Speed Control Systems

A new kind of dynamic neural network--diagonal recurrent neural network (DRNN) and its learning method and architecture are presented. A direct adaptive control scheme is also developed that is applied to a DC (Direct Current) speed control system with the ability to auto-tune PI (Proportion Integral) parameters based on combining DRNN with PI controller. The simulation results of DRNN show better control performances and potential practical use in comparison with PI controller.

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.