Adaptive Nonlinear Control of Wind Energy Conversion System Involving Induction Generator

This paper presents a theoretical framework for adaptive control of a wind energy conversion system (WECS), involving a squirrel cage induction generator (SIG) connected with an AC/DC/AC IGBT‐based PWM converter. A multi‐loop nonlinear controller is designed to meet two main control objectives, i.e., (i) speed reference optimization in order to extract a maximum wind energy whatever the wind speed, and (ii) power factor correction (PFC) to avoid net harmonic pollution. These objectives must be achieved despite the mechanical parameters uncertainty. First, a nonlinear model of the whole controlled system is developed within the Park coordinates. Then, a multi‐loop nonlinear controller is synthesized using the adaptive backstepping design. A formal analysis based on Lyapunov stability is carried out to describe the control system performances. In addition to closed‐loop global asymptotic stability, it is proven that all control objectives (induction generator speed tracking, rotor flux regulation, DC link voltage regulation and unitary power factor) are asymptotically achieved.     

权值自调整模糊PI在无刷直流电机中的应用

无刷直流电机是一种多变量和非线性的控制系统,模糊控制器在该控制中得到广泛的使用。针对无刷直流电机构成的速度反馈控制采用了一种新的控制方案——权值自调整模糊PI预测控制。控制器由模糊控制环节、PI控制器、权值调整环节构成,整个系统使用电流和转速双闭环控制。PI控制器和模糊控制器的权值是通过误差、误差变化率设计的模糊调整器来在线调整,速度反馈采用灰色算法来预测。通过仿真实验结果表明上述控制方法较传统的PI控制,具有更强的鲁棒性,易于实现,通用性强。     

Speed control of Brushless DC motor using bat algorithm optimized Adaptive Neuro-Fuzzy Inference System

In this paper, speed control of Brushless DC motor using Bat algorithm optimized online Adaptive Neuro-Fuzzy Inference System is presented. Learning parameters of the online ANFIS controller, i.e., Learning Rate (η), Forgetting Factor (λ) and Steepest Descent Momentum Constant (α) are optimized for different operating conditions of Brushless DC motor using Genetic Algorithm, Particle Swarm Optimization, and Bat algorithm. In addition, tuning of the gains of the Proportional Integral Derivative (PID), Fuzzy PID, and Adaptive Fuzzy Logic Controller is optimized using Genetic Algorithm, Particle Swarm Optimization and Bat Algorithm. Time domain specification of the speed response such as rise time, peak overshoot, undershoot, recovery time, settling time and steady state error is obtained and compared for the considered controllers. Also, performance indices such as Root Mean Squared Error, Integral of Absolute Error, Integral of Time Multiplied Absolute Error and Integral of Squared Error are evaluated and compared for the above controllers. In order to validate the effectiveness of the proposed controller, simulation is performed under constant load condition, varying load condition and varying set speed conditions of the Brushless DC motor. The real time experimental verification of the proposed controller is verified using an advanced DSP processor. The simulation and experimental results confirm that bat algorithm optimized online ANFIS controller outperforms the other controllers under all considered operating conditions.     

直流调速系统中常规PI 与模糊PI 控制器的比较

转速电流双闭环直流调速系统中的PI控制器直接影响其调速性能,利用MATLAB分别建立了由常规PI与模糊PI控制器组成的转速电流双闭环控制直流调速系统的仿真模型,并进行了仿真。仿真结果表明,模糊PI控制器与常规PI控制器相比具有更好的动态稳定性和跟踪性能,对外界干扰具有较强的鲁棒性。     

DC/DC升压变换器自抗扰控制

本文设计了一种线性自抗扰控制器,直接对DC/DC升压变换器的电感电流实施控制,以抑制系统非最小相位特性时控制性能的影响.在此基础上,外环采用一个PI控制器对输出电压进行控制,并把电压控制器的输出作为内环电感电流控制的参考输入.由于自抗扰控制器则是一种不依赖丁系统模型的控制方法,因此被控系统不但具有良好的动态特性,而且对...     

A second-order sliding mode and fuzzy logic control to optimal energy management in wind turbine with battery storage

The optimal control of large-scale wind turbine has become a critical issue for the development of renewable energy systems and their integration into the power grid to provide reliable, secure and efficient electricity, despite any possible constraints such as sudden changes in wind speed. This paper deals with the modeling and control of a hybrid system integrating a permanent magnet synchronous generator (PMSG) in variable speed wind turbine (VSWT) and batteries as energy storage system (BESS). Moreover a new supervisory control system for the optimal management and robust operation of a VSWT and a BESS is described and evaluated by simulation under wind speed variation and grid demand changes. In this way, the proposed coordinated controller has three subsystems (generator side, BESS side and grid side converters). The main function of the first one is to extract the maximum wind power through controlling the rotational speed of the PMSG, for this a maximum power point tracking algorithm based on fuzzy logic control and a second-order sliding mode control (SOSMC) theory is designed. The task of the second one is to maintain the required direct current (DC) link voltage level of the PMSG through a bidirectional DC/DC converter, whereas in the last, a (SOSMC) is investigated to achieve smooth regulation of grid active and reactive powers quantities, which provides better results in terms of attenuation of the harmonics present in the grid courant compared with the conventional first-order sliding controller. Extensive simulation studies under different conditions are carried out in MATLAB/Simulink, and the results confirm the effectiveness of the new supervisory control system.

     

基于模糊控制的双闭环直流调速系统控制器设计研究

介绍了基于模糊控制的双闭环直流调速系统控制器的设计方案,并比较分析了传统PI与模糊控制的实例。提供了对传统直流双闭环调速系统的一种改进方案。     

High‐performance high‐efficiency LED‐backlight driving system for LCD panels

Abstract— A high‐performance high‐efficiency LED‐backlight driving system for liquid‐crystal‐display panels is presented. The proposed LED‐backlight driving system is composed of a high‐efficiency DC‐DC converter capable of operating over a universal AC input voltage (75–265 V) and a high‐performance LED‐backlight sector‐dimming controller. The high efficiency of the system is achieved by using an asymmetrical half‐bridge DC‐DC converter that utilizes a new voltage‐driven synchronous rectifier and an LED‐backlight sector‐dimming controller. This controller regulates current using lossless power semiconductor switches (MOSFETs). The power semiconductor switches of the proposed DC‐DC converter, including the synchronous rectifier switch, operate with zero voltage, achieving high efficiency and low switch voltage stress using the asymmetrical‐PWM and synchronous rectifier techniques. To achieve high performance, the proposed driving system performs the sector dimming and the current regulation using low‐cost microcontrollers and MOSFET switching, resulting in high contrast and brightness. A100‐W laboratory prototype was built and tested. The experimental results verify the feasibility of the proposed system.     

Interval Type-2 Fuzzy Hierarchical Adaptive Cruise Following-Control for Intelligent Vehicles

Intelligent vehicles can effectively improve traffic congestion and road traffic safety. Adaptive cruise following-control (ACFC) is a vital part of intelligent vehicles. In this paper, a new hierarchical vehicle-following control strategy is presented by synthesizing the variable time headway model, type-2 fuzzy control, feedforward + fuzzy proportion integration (PI) feedback (F+FPIF) control, and inverse longitudinal dynamics model of vehicles. Firstly, a traditional variable time headway model is improved considering the acceleration of the lead car. Secondly, an interval type-2 fuzzy logic controller (IT2 FLC) is designed for the upper structure of the ACFC system to simulate the driver’s operating habits. To reduce the nonlinear influence and improve the tracking accuracy for the desired acceleration, the control strategy of F+FPIF is given for the lower control structure. Thirdly, the lower control method proposed in this paper is compared with the fuzzy PI control and the traditional method (no lower controller for tracking desired acceleration) separately. Meanwhile, the proportion integration differentiation (PID), linear quadratic regulator (LQR), subsection function control (SFC) and type-1 fuzzy logic control (T1 FLC) are respectively compared with the IT2 FLC in control performance under different scenes. Finally, the simulation results show the effectiveness of IT2 FLC for the upper structure and F+FPIF control for the lower structure.      

Performance Improvement of Fuel Cells Using Perturbation‐Based Extremum Seeking and Model Reference Adaptive Control

Nowadays, fuel cells (FCs) are considered suitable alternative sources for electrical energy applications. One major challenge encountered in FCs is relevant to the performance of the maximum power point tracking (MPPT) under FC parameter changes and load variations. This challenge is due to the nonlinearity and time‐varying dynamics of FC systems. In this paper, the MPPT is studied in a system composed of a FC and a DC‐DC converter. To improve the performance of the MPPT, application of perturbation‐based extremum seeking (PES) and model reference adaptive control (MRAC) is proposed. This control scheme can efficiently handle the uncertainties in the FC as well as the load, through two control levels. The first level is PES utilized to adjust the duty cycle of the DC‐DC converter; and the second level is MRAC employed to achieve the desired dynamic response. Using the proposed control strategy, design and analysis of the control levels can be realized independently, which results in easy implementation. This is achieved due to considerable differences between the time constants of the control levels. The simulation results are utilized to confirm the effectiveness of the proposed scheme in response to the variations of FC parameters and load. Also, comparative studies with a combination of PES and PID controller are provided in the simulation.     

Maximum power tracking of a generic photovoltaic system via a fuzzy controller and a two-stage DC–DC converter

This study presents a new two-stage DC–DC converter for maximum power point tracking (MPPT) and a voltage boost of a generic photovoltaic (PV) system. An intelligent MPPT of PV system based on fuzzy logic control (FLC) is presented to adaptively design the proposed fuzzy controlled MPPT controller (FC-MPPTC) while a voltage boost controller (VBC) is used to fix the output voltage to a voltage level that is higher than the required operating voltage to the back-end grid impedance. Modeling and simulation on the PV system and the DC–DC converter circuit are achieved by state-space and the software Powersim. The PV string considered has the rated power around 600?VA under varied partial shadings. The FC-MPPTC and VBC are designed and realized by a DSP module (TMS320F2812) to adjust the duty cycle in the two-stage DC–DC converter. A special FLC algorithm is forged to render an MPPT faster and more accurate than conventional MPPT technique, perturb and observe (P&O). The simulations are intended to validate the performance of the proposed FC-MPPTC. Experiments are conducted and results show that MPPT can be achieved in a fast pace and the efficiency reaches over 90?%, even up to 96?%. It is also found that the optimized tracking speed of the proposed FC-MPPTC is in fact more stable and faster than the general P&O method with the boost voltage capable of offering a stable DC output.     

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.     

基于模糊与自校正技术的超声电机伺服控制

通过电机的工作原理和速度特性分析,选定驱动频率为其控制变量;为实现电机快速而高精度位置控制,引入模糊和自校正复合控制技术,其中,模糊逻辑控制技术意在实现控制的快速性,自校正技术用以提高控制精度;组建了控制系统,完成了相应的控制实验;结果表明:在超声电机上采用这种复合控制技术上可以得到较好的控制效果。     

Stability analysis and a hybrid controller design of grid‐connected offshore wind farm through a VSC‐HVDC transmission link

This paper proposes a hybrid controller which is a combination sliding mode control and PI control techniques for AC grid integrated offshore wind farm (OSWF) with voltage source converter ‐ high voltage direct current system. The controller must be capable of controlling AC voltage, DC‐link voltage, reactive power and effective power transfer. To examine the FRT capability, a symmetrical fault is applied at onshore AC grid side and compared the performances of the studied system based on the hybrid and PI controllers. The dynamic modelling and linearized system by state‐space modelling for the studied system are explained in detail. The small signal stability analysis and controller stability are observed with the help of the eigenvalue analysis. The analysis of the studied system with a hybrid and conventional controllers are conducted in the software environment of the MATLAB/SIMULINK . The effect of parameter uncertainty on total system stability is examined with the help of eigenmatrix of the studied system.     

PI controller design using ABC algorithm for MPPT of PV system supplying DC motor pump load

Maximum power point tracking (MPPT) is used in photovoltaic (PV) systems to maximize its output power. A new MPPT system has been suggested for PV–DC motor pump system by designing two PI controllers. The first one is used to reach MPPT by monitoring the voltage and current of the PV array and adjusting the duty cycle of the DC/DC converter. The second PI controller is designed for speed control of DC series motor by setting the voltage fed to the DC series motor through another DC/DC converter. The suggested design problem of MPPT and speed controller is formulated as an optimization task which is solved by artificial bee colony (ABC) to search for optimal parameters of PI controllers. Simulation results have shown the validity of the developed technique in delivering MPPT to DC series motor pump system under atmospheric conditions and tracking the reference speed of motor. Moreover, the performance of the ABC algorithm is compared with genetic algorithm for various disturbances to prove its robustness.

     

Robust Wind Speed Estimation and Control of Variable Speed Wind Turbines

In this work, a robust control scheme for variable speed wind turbine system that incorporates a doubly feed induction generator is described. The sliding mode controller is designed in order to track the optimum wind turbine speed value that produces the maximum power extraction for different wind speed values. A robust sliding mode observer for the aerodynamic torque is also proposed in order to avoid the wind speed sensors in the control scheme. The controller uses the estimated aerodynamic torque in order to calculate the reference value for the wind turbine speed. Another sliding mode control is also proposed in order to maintain the dc‐link voltage constant regardless of the direction of the rotor power flow. The stability analysis of the proposed controller under disturbances and parameter uncertainties is provided using the Lyapunov stability theory. Finally, the simulation results show that the proposed control scheme provides a high‐performance turbine speed control, in order to obtain the maximum wind power generation, and a high‐performance dc‐link regulation in the presence of system uncertainties.     

基于DSP前馈模糊PI的舵机控制算法

针对负载转矩对舵机转速的影响,建立负载力矩的数学模型,提出带前馈模糊自整定比例积分参数的速度环控制算法,利用前馈控制器补偿负载变化对电机转速的影响。当直流无刷电机特性和力矩变化时,通过动态调整控制参数使系统具有良好的鲁棒性和控制精度。设计以数字信号处理器为核心的模糊控制器,采用高精度的绝对编码器作为位置环反馈。实验结果表明,该控制器具有较强鲁棒性,且响应速度快、超调小、控制精度高。     

兆瓦级直驱式风力发电机组控制系统设计

为了降低系统控制难度、提高机组转化效率,提出了一种以复合励磁同步发电机作为发电机的兆瓦级直驱式复合励磁同步风力发电系统,该系统由不可控二极管 直流环节 并联SPWM逆变器组成的交/直/交变流器将风能转化为电能送入电网.该机组控制系统由机组主控制器、复合励磁控制器、逆变器控制单元、变桨距机构、偏航机构等构成.对机组控制系统中各个部件的功能和结构进行了分析和设计,并通过Profibus现场总线将这些部件构成了一个集散控制系统.     

Design of low cost universal artificial neuron controller for chopper fed embedded DC drives

Artificial neural network (ANN) has become very popular in many control applications due to their high computation rate and ability to handle nonlinear functions. This paper proposes an artificial neuron controller for closed loop speed control of DC drive fed by DC chopper. Neuron control is used to reduce the steady state error, overshoot and settling time. The signal corresponding to the motor speed error and change in speed error are used as inputs to ANN Controller. The controller outputs the required change in duty cycle of pulse width modulated gating signal applied to DC chopper. Thus the voltage fed to the armature of the DC motor is adjusted for achieving the desired speed response. The training patterns for the neuron controller are obtained from the conventional PI controller and the effectiveness of the proposed neuron controller is studied using simulation studies.The designed controller was implemented in a low cost 8051-based embedded system and the results are documented. Two-loop control system was implemented with an inner ON/OFF current controller and an outer ANN speed controller.A conventional controller has heavy computation burden whereas a trained neural network requires less computation time. The artificial neural network has the ability to generalize and can interpolate in between the training data. This advantage of ANN makes the ANN controller universal. The ANN controller designed was tested on two different motors and found to work effectively on driving both of them.     

基于模糊分数阶PIλDμ控制的AC/DC变换器

作为AC/DC电力变换装置的核心,控制系统控制效果的好坏直接影响电压输出波形的质量.为了进一步提高AC/DC电力变换装置的控制性能,增强系统的鲁棒性和稳态性,提出一种模糊控制与分数阶PIλ Dμ控制相结合的复合控制策略,并将其用于十二脉波整流电路的控制系统中.采用模糊控制器可以很好地实现对控制参数的自适应调整,分数阶PIλDμ控制器在非线性系统的控制过程中能够取得比整数阶PID控制器更好的控制效果.仿真和实验结果表明,改进后的控制器具有较强的灵活性和鲁棒性,稳态性和自适应能力得到增强,适用于非线性时变系统.