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.

Fuzzy self-tuning PID control of the operation temperatures in a two-staged membrane separation process

A two-staged membrane separation process for hydrogen recovery from refinery gases is introduced. The principle of the gas membrane separation process and the influence of the operation temperatures are analyzed. As the conventional PID controller is difficult to make the operation temperatures steady, a fuzzy self-tuning PID control algorithm is proposed. The application shows that the algorithm is effective, the operation temperatures of both stages can be controlled steadily, and the operation flexibility and adaptability of the hydrogen recovery unit are enhanced with safety. This study lays a foundation to optimize the control of the membrane separation process and thus ensure the membrane performance.

Stabilization of CSTR w ith Self-tuning Sliding Mode Controller Using T-S Fuzzy Linearization

A self-tuning reaching law based sliding mode control(SMC)theory is proposed to stabilize the nonlinear continuous stirred tank reactor(CSTR).T-S fuzzy logic is used to build a global fuzzy state-space linear model.Combing the traits of SMC and CSTR,three fuzzy rules can meet the requirements of controlled system.The self-tuning switch control law which can drive the state variables to the sliding surface as soon as possible is designed to ensure the robustness of uncertain fuzzy system.Lyapunov equation is applied to proving the stability of the sliding surface.The simulations show that the proposed approach can achieve desired performance with less chattering problem.

A Stable Fuzzy-Based Computational Model and Control for Inductions Motors

In this paper,a stable and adaptive sliding mode control(SMC)method for induction motors is introduced.Determining the parameters of this system has been one of the existing challenges.To solve this challenge,a new self-tuning type-2 fuzzy neural network calculates and updates the control system parameters with a fast mechanism.According to the dynamic changes of the system,in addition to the parameters of the SMC,the parameters of the type-2 fuzzy neural network are also updated online.The conditions for guaranteeing the convergence and stability of the control system are provided.In the simulation part,in order to test the proposed method,several uncertain models and load torque have been applied.Also,the results have been compared to the SMC based on the type-1 fuzzy system,the traditional SMC,and the PI controller.The average RMSE in different scenarios,for type-2 fuzzy SMC,is 0.0311,for type-1 fuzzy SMC is 0.0497,for traditional SMC is 0.0778,and finally for PI controller is 0.0997.

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.

Instantaneous Active and Reactive Power and Current Strategies for Current harmonics cancellation in 3-ph 4wire SHAF With both PI and Fuzzy Controllers

Control strategies for extracting the three-phase reference currents for shunt active power filters are compared, evaluating their performance under different source conditions with PI and Fuzzy Controllers in MATLAB/Simulink environment When the supply voltages are balanced and sinusoidal, the two control strategies are converge to the same compensation characteristics;However, the supply voltages are distorted and/or un-balanced sinusoidal, these control strategies result in different degrees of compensation in harmonics. The compensation capabilities are not equivalent, with p - q control strategy unable to yield an adequate solution when source voltages are not ideal. Extensive simulations are carried out with PI controller and also with Fuzzy controller for both p-q and Id-Iq control strategies under different main voltages. Extensive Simulations are carried out with PI as well as fuzzy controller for both p-q and Id - Iq control strategies by considering different voltage conditions and adequate results were presented. On owing Id - Iq method with fuzzy logic controller gives away an out-standing performance under any voltage conditions (balanced, un-balanced, balanced and non-sinusoidal).

Fuzzy and PI Controller Based SHAF for Mitigation of Current Harmonics with P-Q Method Using Matlab and RTDS Hardware

The main objective of this paper is to develop PI and Fuzzy logic controllers to analyse the performance of instantaneous real active and reactive power (p-q) control strategy for extracting reference currents of shunt active filters under balanced, un-balanced and balanced non-sinusoidal conditions. When the supply voltages are balanced and sinusoidal, then all controllers converge to the same compensation characteristics. However, when the supply voltages are distorted and/or un-balanced sinusoidal, these control strategies result in different degrees of compensation in harmonics. The p-q control strategy with PI controller is unable to yield an adequate solution when source voltages are not ideal. Extensive simulations were carried out;simulations were performed with balance, unbalanced and non sinusoidal conditions. Simulation results validate the dynamic behaviour of Fuzzy logic controller over PI controller. The 3-ph 4-wire SHAF system is also implemented on a Real Time Digital Simulator (RTDS Hardware) to further verify its effectiveness. The detailed simulation and RTDS Hardware results are included.

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.

基于Fuzzy-PI的直驱永磁风力发电系统MPPT控制

通过对模糊PI控制算法、MPPT算法分析,并对变流器的控制策略进行推导,提出基于Fuzzy-PI控制策略,确定机侧以转速的偏差及其微分为输入,交轴电流为输出,风机达到最大功率跟踪效果;网侧变流器采用电压外环、电流内环双闭环控制策略。通过Simulink系统仿真,结果表明模糊PI控制系统能实现发电机的最大功率跟踪和单位功率因数运行,控制效果优于传统的PI控制策略。

模糊整定PI参数的双柔性机械臂振动抑制

机械臂伺服驱动系统中柔性因素的存在易导致机械臂输出转速波动,甚至引发系统谐振.为抑制系统转速波动,使机械臂传动系统性能稳定,使用模糊理论整定PI控制器参数的控制策略.根据假设模态法和拉格朗日动力学方程建立了考虑LuGre摩擦模型的双柔性机械臂传动系统动力学方程,并分析了动力学方程中耦合非线性项对系统传动特性的影响.使用极点配置策略确定PI控制器参数的取值范围,后根据模糊规则实时调整控制器参数,以减小伺服系统输出转速的波动,进而抑制系统谐振.最后,借助数值仿真分析和机械臂控制实验,与传统PI控制策略对比,发现本文所述控制策略可使电机端转角跟踪误差绝对值的平均值降低43.066%,柔性负载转角误差的标准差降低46.506%,更加验证了所提模糊规则整定PI控制器参数抑振方法的有效性.

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。

基于模糊解耦策略的小型注塑机料筒温度F-PI复合控制器

在塑料产品的生产过程中,注塑机料筒温度的响应速度和稳定性对最终塑料产品的质量具有重要影响。为了提高小型注塑机料筒温度的控制精度,针对料筒具有的惯性大、非线性、大滞后、强耦合等温度特性,在模糊控制不能满足控制要求的背景下,提出了基于相邻加热段之间温差的模糊解耦策略,通过利用相邻加热段之间的温差信息,建立模糊解耦控制器,对各段料筒之间的温度耦合进行解耦控制。实验结果表明,该控制方法效果良好,达到目标温度所用时间为1092 s,最大超调量只有3%,但稳态性能较差。为解决稳态性能较差的问题,在模糊解耦的基础上建立F-PI复合控制器,通过引入积分环节消除系统在稳态下的偏差。在Matlab/Simulink环境下进行仿真并在注塑机上进行验证,结果表明,F-PI复合控制方法不仅具有良好的动态响应,还具有更高的稳态精度,稳态偏差仅为±1℃。因此基于模糊解耦策略的F-PI复合控制方法不仅能对料筒的温度耦合进行解耦控制,还有效提高了系统的稳定性和控制精度,具有良好的鲁棒性。

基于模糊自适应PI的伺服控制系统设计

本文分析了伺服控制三闭环调速的特点,介绍了模糊控制和PI控制系统。主要依据天线当前位置和速度采样反馈值,利用模糊控制原理对传统PI控制的比例、积分和微分参数进行在线整定,组成智能PI控制器,最后利用Matlab对控制系统进行仿真,得出仿真结果,并对仿真结果进行时域特性分析。

Motion Control of Omnidirectional Mobile Platform based on Fuzzy PID

The omnidirectional mobile platform has three degrees of freedom that make it widely applicable to all areas of industry, while the Mecanum wheel has the disadvantages wheel omnidirectional mobile platform is always difficult in of large vibration, the trajectory precision of Mecanum the omnidirectional mobile platform. To control the trajectory of the omnidirectional mobile platform better, this paper proposes a fuzzy self-tuning PID control model, through establishing the motion model of omnidirectional mobile platform in Adams software, then combined with Simulink simulation, analysis of fuzzy PID controller to improve the accuracy of the speed control of omnidirectional mobile platform, improve the control method of a precise trajectory of the omnidirectional mobile platform motion.

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.

TYPICAL ARCHITECTURES FOR FUZZY CONTROL

Some typical structural schemes of Fuzzy control have been surveyed. Besides general structure of fuzzy logic controller (FLC), the structural schemes include PID fuzzy controller, self-organizing fuzzy controller, selftuning fuzzy controller, self-learning fuzzy controller, and expect fuzzy controller, etc. This survey focuses on the control principle, and provides a basis for potential applications. Most of the structures have been used in various control fields, one of application areas is in the metallurgy industry, e. g., the temperature control of the electric furnace, the control of the aluminum smelting process, etc. According to the application requirements, one can choose a structural scheme for special use.

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.

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.

APF直流侧电压自适应PI控制

三相三线制有源滤波器(APF)大多采用传统的PI控制策略来控制直流侧的电容电压。为了提高有源滤波器的性能指标,在传统的PI控制基础上,结合最小隶属度模糊控制理论,提出模糊PI的直流侧电压自适应控制。模糊PI控制可以根据实时情况改变比例和积分参数,解决了传统PI控制器在非线性系统中的缺点。MATLAB仿真表明,模糊PI自适应控制与传统PI控制相比,跟踪性能更强,直流侧电压超调量更低,动态性能更好,并且有效地降低了电网谐波的畸变量。