Intelligent Fractional-Order Controller for SMES Systems in Renewable Energy-Based Microgrid

An autonomous microgrid that runs on renewable energy sources is presented in this article.It has a supercon-ducting magnetic energy storage(SMES)device,wind energy-producing devices,and an energy storage battery.However,because such microgrids are nonlinear and the energy they create varies with time,controlling and managing the energy inside them is a difficult issue.Fractional-order proportional integral(FOPI)controller is recommended for the current research to enhance a standalone microgrid’s energy management and performance.The suggested dedicated control for the SMES comprises two loops:the outer loop,which uses the FOPI to regulate the DC-link voltage,and the inner loop,responsible for regulating the SMES current,is constructed using the intelligent FOPI(iFOPI).The FOPI+iFOPI parameters are best developed using the dandelion optimizer(DO)approach to achieve the optimum performance.The suggested FOPI+iFOPI controller’s performance is contrasted with a conventional PI controller for variations in wind speed and microgrid load.The optimal FOPI+iFOPI controller manages the voltage and frequency of the load.The behavior of the microgrid as a reaction to step changes in load and wind speed was measured using the proposed controller.MATLAB simulations were used to evaluate the recommended system’s performance.The results of the simulations showed that throughout all interruptions,the recommended microgrid provided the load with AC power with a constant amplitude and frequency.In addition,the required load demand was accurately reduced.Furthermore,the microgrid functioned incredibly well despite SMES and varying wind speeds.Results obtained under identical conditions were compared with and without the best FOPI+iFOPI controller.When utilizing the optimal FOPI+iFOPI controller with SMES,it was found that the microgrid performed better than the microgrid without SMES.

Improved quantum bacterial foraging algorithm for tuning parameters of fractional-order PID controller

The quantum bacterial foraging optimization(QBFO)algorithm has the characteristics of strong robustness and global searching ability. In the classical QBFO algorithm, the rotation angle updated by the rotation gate is discrete and constant,which cannot affect the situation of the solution space and limit the diversity of bacterial population. In this paper, an improved QBFO(IQBFO) algorithm is proposed, which can adaptively make the quantum rotation angle continuously updated and enhance the global search ability. In the initialization process, the modified probability of the optimal rotation angle is introduced to avoid the existence of invariant solutions. The modified operator of probability amplitude is adopted to further increase the population diversity.The tests based on benchmark functions verify the effectiveness of the proposed algorithm. Moreover, compared with the integerorder PID controller, the fractional-order proportion integration differentiation(PID) controller increases the complexity of the system with better flexibility and robustness. Thus the fractional-order PID controller is applied to the servo system. The tuning results of PID parameters of the fractional-order servo system show that the proposed algorithm has a good performance in tuning the PID parameters of the fractional-order servo system.

基于改进麻雀搜索算法分数阶PI的PMSM调速策略

永磁同步电机调速系统采用传统比例积分双闭环控制结构存在抗扰性能差与响应速度慢的问题。为此,文中在建立PMSM数学模型和分析传统PI参数设计方法的基础上,提出一种基于改进麻雀搜索算法分数阶比例积分的PMSM调速优化策略,通过在常规SSA中引入佳点集初始化策略和黄金正弦更新策略,解决了SSA易陷入局部最优的问题,提高了收敛速度和精度,以进一步改善PMSM调速系统的响应性能。最后通过MATLAB仿真对比结果可知,所述ISSA-FOPI调速改进策略在4种工况下具有最短的调节时间分别为1.2、0.9、9.9与12.1 ms,和最小的超调量分别为0.16%、0.16%、0.05%与0.6%,这充分体现了所述策略的有效性与优越性。

基于虚拟电阻的双馈风机次同步振荡分数阶PI控制

针对传统方法抑制双馈风机经不同串补电容并网引发的次同步振荡效果不佳的问题,文中提出一种基于虚拟电阻的风机分数阶比例-积分(FOPI)控制策略。首先,分析风电系统次同步振荡发生机理,并以风机并网电流为输入信号设计宽频带次同步电流滤波器,构建出虚拟电阻控制器以增强系统电气阻尼;之后,利用Oustaloup算法改进分数阶积分算子,以网侧变流器控制方程为底层模型重构FOPI电流控制环,分析积分阶次对电流跟踪动态特性的影响;然后,通过引入非线性迭代权重以及学习因子改进传统灰狼优化算法,优化控制策略参数;最后,利用Matlab/Simulink搭建仿真验证模型,结果表明所提策略能有效抑制不同串补度下的次同步振荡,表现出较强的鲁棒稳定性。

基于麻雀搜索优化算法分数阶PI的PMSM矢量控制

永磁同步电机(Permanent Magnet Synchronous Motor,PMSM)矢量控制系统转速环采用PI控制器难以满足系统动态响应速度快、鲁棒性强等要求,采用分数阶比例积分(Fractional Order Proportional Integral,FOPI)控制器,并利用麻雀搜索算法(Sparrow Search Algorithm,SSA)优化FOPI控制器参数.通过搜索最优适应度的麻雀所在位置,得到控制器最优组合参数,选择时间乘以误差绝对值积分作为其目标适应度函数.对SSA整定FOPI、粒子群算法(Particle Swarm Optimization,PSO)整定PI参数的电机调速性能进行试验对比.结果表明,SSA优化的FOPI具有增强鲁棒性和减小超调量的优势.

Effects of fractional-order PI controller on delay margin in single-area delayed load frequency control systems

This study aims to determine the improvement effect on the delay margin if fractional-order proportional integral(PI) controller is used in the control of a singlearea delayed load frequency control(LFC) system. The delay margin of the system with fractional-order PI control has been obtained for various fractional integral orders and the effect of them has been shown on the delay margin as a third controller parameter. Furthermore,the stability of the system that is either under or over the delay margin is examined by generalized modified Mikhailov criterion.The stability results obtained have been confirmed numerically in time domain. It is demonstrated that the proposed controller for delayed LFC system provides more flexibility on delay margin according to integer-order PI controller.

Robust Stabilizing Regions of Fractional-order PI~λ Controllers for Fractional-order Systems with Time-delays

This study focuses on a graphical approach to determine the robust stabilizing regions of fractional-order PIλ（proportional integration） controllers for fractional-order systems with time-delays. By D-decomposition technique, the existence conditions and calculating method of the real root boundary（RRB） curves, complex root boundary（CRB） curves and infinite root boundary（IRB）lines are investigated for a given stability degree. The robust stabilizing regions in terms of the RRB curves, CRB curves and IRB lines are identified by the proposed criteria in this paper. Finally, two illustrative examples are given to verify the effectiveness of this graphical approach for different stability degrees.

Design of FOPI Controller for Time Delay Systems and Its Experimental Validation

In this paper,we report on the identification and modeling of unknown and higher order processes into first order plus dead time(FOPDT)plants based on the limit cycle information obtained from a single relay feedback test with an online fractional order proportional integral(FOPI)controller.The parameters of the test processes are accurately determined by the state space method while the FOPI controller settings are re-tuned to achieve enhanced performance based on the identified model parameters based on the balancedtuning method.A new performance index,integral time fractional order absolute error(ITFIAE)is introduced in this paper for balanced tuning of fractional order(FO)controllers.It requires minimum design specifications without a-priori knowledge of gain and phase crossover frequencies and is done non-iteratively without disrupting the closed loop.Four test processes and experimental analysis on a coupled tank system(CTS)validate the theory proposed.

Auto-tuning of FOPI Controllers for TITO Processes with Experimental Validation

In this paper, the auto-tuning of a fractional order proportional and integral(FOPI) controller is proposed and experimentally validated for two-input two-output(TITO) processes. The proposed method first identifies an unknown TITO plant into fractional order TITO model with time delay. Furthermore, decoupling the TITO process into two fractional order single-input single-output(SISO) transfer function models makes it easier for designing the decentralized FOPI controllers. The proposed control method is a generalization of both integer order and fractional order TITO systems depending on the value of the order of the model. One advantage of this method is the non-requirement of a-priori information of gain and phase crossover frequencies of the system while tuning the controllers. The proposed algorithm is validated both by simulation of a class of TITO process models as well as by experimental analysis of a coupled tank system(CTS).