Study of improved gray predictive PID control algorithm

According to these characteristics of the movement of the special platform servo,a new improved grey predictive PID control algorithm was proposed based on the grey predictive PID,and then the algorithm was simulated by MATLAB.As a result that it can improve the response speed and stability of the system,and meet the demand of the system.

Improved Bat Algorithm Based Energy Efficient Congestion Control Scheme for Wireless Sensor Networks

Energy conservation and congestion control are widely researched topics in Wireless Sensor Networks in recent years. The main objective is to develop a model to find the optimized path on the basis of distance between source and destination and the residual energy of the node. This paper shows an implementation of nature inspired improved Bat Algorithm to control congestion in Wireless Sensor Networks at transport layer. The Algorithm has been applied on the fitness function to obtain an optimum solution. Simulation results have shown improvement in parameters like network lifetime and throughput as compared with CODA (Congestion Detection and Avoidance), PSO (Particle Swarm Optimization) algorithm and ACO (Ant Colony Optimization).

A Control Strategy for Smoothing Active Power Fluctuation of Wind Farm with Flywheel Energy Storage System Based on Improved Wind Power Prediction Algorithm

The fluctuation of active power output of wind farm has many negative impacts on large-scale wind power integration into power grid. In this paper, flywheel energy storage system (FESS) was connected to AC side of the doubly-fed induction generator (DFIG) wind farm to realize smooth control of wind power output. Based on improved wind power prediction algorithm and wind speed-power curve modeling, a new smooth control strategy with the FESS was proposed. The requirement of power system dispatch for wind power prediction and flywheel rotor speed limit were taken into consideration during the process. While smoothing the wind power fluctuation, FESS can track short-term planned output of wind farm. It was demonstrated by quantitative analysis of simulation results that the proposed control strategy can smooth the active power fluctuation of wind farm effectively and thereby improve power quality of the power grid.

Improved Interleaved Single-Ended Primary Inductor-Converter forSingle-Phase Grid-Connected System

The generation of electricity based on renewable energy sources,parti-cularly Photovoltaic(PV)system has been greatly increased and it is simply insti-gated for both domestic and commercial uses.The power generated from the PV system is erratic and hence there is a need for an efficient converter to perform the extraction of maximum power.An improved interleaved Single-ended Primary Inductor-Converter(SEPIC)converter is employed in proposed work to extricate most of power from renewable source.This proposed converter minimizes ripples,reduces electromagnetic interference due tofilter elements and the contin-uous input current improves the power output of PV panel.A Crow Search Algo-rithm(CSA)based Proportional Integral(PI)controller is utilized for controlling the converter switches effectively by optimizing the parameters of PI controller.The optimized PI controller reduces ripples present in Direct Current(DC)vol-tage,maintains constant voltage at proposed converter output and reduces over-shoots with minimum settling and rise time.This voltage is given to single phase grid via 1�Voltage Source Inverter(VSI).The command pulses of 1�VSI are produced by simple PI controller.The response of the proposed converter is thus improved with less input current.After implementing CSA based PI the efficiency of proposed converter obtained is 96%and the Total Harmonic Distor-tion(THD)is found to be 2:4%.The dynamics and closed loop operation is designed and modeled using MATLAB Simulink tool and its behavior is performed.

Two-Stage Planning of Distributed Power Supply and Energy Storage Capacity Considering Hierarchical Partition Control of Distribution Network with Source-Load-Storage

Aiming at the consumption problems caused by the high proportion of renewable energy being connected to the distribution network,it also aims to improve the power supply reliability of the power system and reduce the operating costs of the power system.This paper proposes a two-stage planning method for distributed generation and energy storage systems that considers the hierarchical partitioning of source-storage-load.Firstly,an electrical distance structural index that comprehensively considers active power output and reactive power output is proposed to divide the distributed generation voltage regulation domain and determine the access location and number of distributed power sources.Secondly,a two-stage planning is carried out based on the zoning results.In the phase 1 distribution network-zoning optimization layer,the network loss is minimized so that the node voltage in the area does not exceed the limit,and the distributed generation configuration results are initially determined;in phase 2,the partition-node optimization layer is planned with the goal of economic optimization,and the distance-based improved ant lion algorithm is used to solve the problem to obtain the optimal distributed generation and energy storage systemconfiguration.Finally,the IEEE33 node systemwas used for simulation.The results showed that the voltage quality was significantly improved after optimization,and the overall revenue increased by about 20.6%,verifying the effectiveness of the two-stage planning.

Optimised trajectory tracking control for quadrotors based on an improved beetle antennae search algorithm

This paper focuses on the trajectory tracking of quadrotors under bounded external disturbances.An optimised robust controller is proposed to drive the position and attitude ofa quadrotor converge to their references quickly. At first, nonsingular fast terminal slidingmode control is developed, which can guarantee not only the stability but also finite-timeconvergence of the closed-loop system. As the parameters of the designed controllers playa vital role for control performance, an improved beetle antennae search algorithm is proposedto optimise them. By employing the historical information of the beetle’s antennaeand dynamically updating the step size as well as the range of its searching, the optimisingis accelerated considerably to ensure the efficiency of the quadrotor control. The superiorityof the proposed control scheme is demonstrated by simulation experiments, from whichone can see that both the error and the overshooting of the trajectory tracking are reducedeffectively.

Cluster voltage control method for “Whole County” distributed photovoltaics based on improved differential evolution algorithm

China is vigorously promoting the “whole county promotion” of distributed photovoltaics (DPVs). However, the high penetration rate of DPVs has brought problems such as voltage violation and power quality degradation to the distribution network, seriously affecting the safety and reliability of the power system. The traditional centralized control method of the distribution network has the problem of low efficiency, which is not practical enough in engineering practice. To address the problems, this paper proposes a cluster voltage control method for distributed photovoltaic grid-connected distribution network. First, it partitions the distribution network into clusters, and different clusters exchange terminal voltage information through a “virtual slack bus.” Then, in each cluster, based on the control strategy of “reactive power compensation first, active power curtailment later,” it employs an improved differential evolution (IDE) algorithm based on Cauchy disturbance to control the voltage. Simulation results in two different distribution systems show that the proposed method not only greatly improves the operational efficiency of the algorithm but also effectively controls the voltage of the distribution network, and maximizes the consumption capacity of DPVs based on qualified voltage.

采用改进遗传算法优化LS-SVM逆系统的外转子无铁心无轴承永磁同步发电机解耦控制

为了实现外转子无铁心无轴承永磁同步发电机(outer rotor coreless bearingless permanent magnet synchronous generator,ORC-BPMSG)的精确控制,提出一种基于改进遗传算法(improved genetic algorithm,IGA)优化最小二乘支持向量机(least square support vector machine,LS-SVM)逆系统的解耦控制策略。首先,基于ORC-BPMSG的结构及工作原理,推导其数学模型,并分析其可逆性。其次,建立LS-SVM回归方程,并采用IGA优化LS-SVM的性能参数,从而训练得到逆系统。然后,将逆系统与原系统串接,形成伪线性系统,实现了ORC-BPMSG的线性化和解耦。最后,将提出的控制方法与传统LS-SVM逆系统控制方法进行对比仿真和实验。仿真和实验结果表明:所提出的控制策略可以较好地实现ORC-BPMSG输出电压和悬浮力、以及悬浮力之间的解耦控制。

数控压机伺服控制系统复合控制器I-ABC与PID优化

为了提高数控压机伺服控制系统的控制精度,针对伺服控制系统运行控制过程构建数学模型,在人工蜂群算法基础上融入了云分析模型,之后采用改进人工蜂群算法(Improved Artificial Bee Colony,I-ABC)调节比例-积分-微分(Proportional Integral Differential,PID)参数,建立了一种复合控制方法。研究结果表明:以I-ABC进行PID控制时,可以使幅度差降低到0.4%,相位差基本在-0.54°之内,系统加载精度也获得了明显提升,表现出了更优的跟踪性能。以I-ABC进行PID控制时,能够对多余力起到明显抑制作用,响应速度也获得明显提升,可以有效满足系统的准确控制要求。在系统内加入干扰信号,引入I-ABC实施PID调节可以减小系统超调量,还可以获得更短调节时间,使系统获得更强抗干扰性能。

MPCVD设备样品台温控系统的设计

由于传统MPCVD设备样品台温度控制需要使用手动调节样品台距等离子源的距离,且调节精度差,为此设计一种样品台温控系统,同时设计了样品台温控系统硬件控制器。该控制器以STM32F407单片机为核心,步进电机、丝杠、金属波纹管为执行机构,通过控制样品台在腔体内距等离子源的距离,实现温度控制。并提出一种将改进鲸鱼算法(WOA)与神经网络PID控制算法结合的控制方法,实现PID参数的自适应调整。仿真和实验结果表明:相对于传统PID算法,使用该温控系统进行温度控制时,超调量更小,控制精度更高,控制效果有很大提升。

基于多策略麻雀搜索算法的径向基神经网络时延预测方法

网络诱导时延序列存在随机性和不稳定性,单一的预测算法难以准确预测,针对该问题,提出一种基于多策略麻雀搜索算法(ISSA)的径向基神经网络(RBF)时延预测方法来准确预测网络时延。首先,为了应对麻雀种群初始分布不均匀的问题,增加改进Tent混沌映射来提高种群早期的分布质量,并引入新的惯性权重因子改进发现者位置更新策略,扩大麻雀早期寻优范围;随后引入正余弦优化算法(SCA)更新跟随者位置,避免种群后期陷入局部最优。其次,考虑到RBF隐含层节点中心,幅值以及输出层权值不确定的问题,提出利用ISSA算法寻优求取。最后,搭建改进的时延预测模型并输入实测时延数据得到预测时延值。实验研究结果表明:相较于传统SSA-RBF模型,文中提出的ISSA-RBF时延预测模型的MSE、MAE和MAPE分别提高了69.46%、32.83%、34.43%,可有效预测网络时延,为之后的时延补偿提供基础。

基于改进LSSVM算法的柔性飞机起落架智能半主动控制技术

提出了基于改进LSSVM算法的柔性飞机起落架智能半主动控制技术。充分考虑柔性飞机结构振动模态,构建飞机起落架智能半主动控制力学模型。根据半主动控制起落架结构,采用剪枝算法构造最小二乘支持向量机优化函数,使控制过程具有稀疏性。计算双气室缓冲器的气体弹力、油孔液压阻尼力和轮胎压力,分析飞机落下、滑跑在动力学模型中的非线性动力学特征。构造起落架二次型性能指标函数,用线性二次型调节器设计起落架最优控制结构,导出最优控制律。由实验结果可知:该技术在缓冲距离为0.25 m时功量达到最大为0.9×10^(5)N,与实际着陆功量控制效果一致;最大位移为0.47 m,仅与实际存在最大为0.01 m的误差,使飞机在平衡位置减少振动响应,保持飞机起落稳定。

孤网模式下水电机组智能鲁棒控制

针对孤网模式下水电机组PID控制策略鲁棒性差的缺点,设计了适用于非线性水轮机调节系统(hydraulic turbine regulating system,HTRS)的基于状态动态测量、反馈线性化和改进黏菌算法(improved slime mold algorithm,ISMA)的智能鲁棒控制器(intelligentrobustcontroller,IRC),以实现对水电站全工况实时最优控制。首先,充分考虑水轮机非线性、随动系统限速环节和高阶发电机特性,构建非线性、复杂HTRS数值仿真模型,并引入系统跟踪偏差的积分,推导出了孤网模式下考虑系统跟踪偏差的HTRS高阶状态空间方程模型。然后,结合高阶状态空间方程和H∞控制实现了HTRS鲁棒控制。进一步,基于ISMA对H∞控制器参数进行智能寻优。最后,结合某电站真实数据构建非线性、复杂HTRS仿真平台,验证了所提控制策略对系统参数和工况的敏感性、频率扰动下的强鲁棒性。

含夹层流体的双板主、被动控制理论分析和试验研究

为了对含夹层流体的双板结构的振动进行控制,基于改进的傅里叶级数法对此双板结构进行理论建模,采取等效方法考虑涂敷阻尼层的影响,并运用有限元方法验证理论模型的正确性。同时介绍FxLMS算法并将其运用于双板的主动控制中,以前述理论方法为基础,得到各通道的传递函数,并基于MATLAB进行算法仿真,取得较好控制效果,可为算法的控制效果验证提供参考。对双板的振动进行控制试验,对比控制前后双板振动加速度级,发现敷设阻尼层较为明显减弱中高频振动,在135Hz频率点处主动控制单通道的控制效果良好,主、被动一体化控制前后下板的振动加速度总级(10~3000Hz)相比降低6.61dB,验证了控制措施的有效性。

基于Levant微分器的磁浮球控制算法研究

针对永磁电磁混合悬浮系统控制中因信号突变和噪声干扰引起的控制效果不理想等问题,提出一种改进型Levant微分器和PID相结合的控制方法(improve Levant-PID,ILevant-PID)。融合PID控制适应性强和Levant微分器对输入噪声的鲁棒特性优势,解决系统输出抖振问题,利用模拟退火-粒子群优化解决ILevant-PID控制器参数多、关联性强等制约问题。仿真实验表明:与传统PID控制方法相比,ILevant-PID控制方法在阶跃输入下,启动更为平缓,调节时间减小了41.19%,超调量减小了40.36%。ILevant-PID控制器在阶跃输入时有无噪声条件下的稳态误差分别为±0.37 mm及±0.23 mm,相对于PID降低了87%以上。在跟踪方波输入时,ILevant-PID可实现PID无法对8 mm给定信号无超调跟踪,较好地改善PEMS(permanent magnet electro magnetic hybrid suspension)系统控制性能。

基于智能预测控制的鱼雷状小型无人艇轨迹跟踪研究

[目的]针对无人艇(USV)在狭窄湖泊、涵洞作业时存在精度保持难和航迹控制难的问题,以自主研制的一款鱼雷状小型USV为对象,提出一种轨迹跟踪智能预测控制方法。[方法]首先,构建自主研制的欠驱动USV非线性状态空间模型;然后,设计智能预测控制器,该控制器基于模型预测控制的设计思想并结合改进的粒子群算法,在线决策、优化每一时刻的性能指标并纠正预测状态;最后,开展仿真和湖试试验测试系统对参考轨迹的跟踪性能,并与线性模型预测控制器的跟踪性能进行比较。[结果]结果表明,所设计的智能预测控制器超调小、抗干扰性好。[结论]所提方法不仅能运用于鱼雷状小型USV跟踪系统,也能对其他USV跟踪系统起到很好的借鉴作用。

基于改进鲸鱼算法的收卷张力PID控制的性能优化

PID控制器的参数决定张力控制系统的稳定性和速度,因此研究收卷张力控制中经典PID控制器参数整定优化问题具有重要意义。以卷绕张力系统为切入点,结合PID和改进的鲸鱼优化算法,设计了基于改进鲸鱼算法(L-WOA)的PID张力控制器;为了提高PID整定参数方法的收敛精度和速度,在进行整定时结合了改进鲸鱼算法;建立数学模型和动态转矩平衡方程,分析了线速度和卷径对卷材张力的影响;分别使用改进鲸鱼算法和其他多种算法进行了参数优化。仿真结果表明,采用改进鲸鱼算法优化PID的控制策略具有响应速度快、控制输出稳定、抗干扰能力强、鲁棒性好等优点。

基于退火PSO-PI与重复PR的图腾柱PFC

功率因数校正(power factor correction,PFC)被广泛应用于车载充电机以提高充电效率、减小对电网产生的谐波污染。本文常用的双闭环比例积分(proportional integration,PI)控制的基础上,研究了退火粒子群算法(particle swarm optimization,PSO-PI)和改进重复比例谐振(proportional resonance,PR)控制,通过退火PSO算法对电压环的PI控制器参数进行优化,提高了响应速度;将电流环由PI控制变为改进重复PR控制,以解决PI控制对高频信号跟踪能力弱的缺点,并选用了近几年比较热门的图腾柱PFC拓扑结构,最终提高了响应速度,降低总谐波畸变率(total harmonic distortion rate,THD)。最后通过Matlab/Simulink仿真验证了控制策略的正确性,相比传统的图腾柱PFC,响应速度得到一定提高,THD值降低了2.07%。

基于改进鲸鱼优化PID的无刷直流电机转速控制算法

针对鲸鱼优化算法易陷入局部最优以及无刷直流电机(brushless DC motor,BLDCM)速度控制响应慢、超调量大等缺点,提出一种改进鲸鱼优化算法(improve whale optimization algorithm,IWOA)优化PID(proportional integral derivative)参数的无刷直流电机速度控制算法.该算法采用高斯变异因子、自适应权重因子和动态阈值相结合对鲸鱼优化算法进行优化.仿真实验结果表明,改进鲸鱼优化PID的无刷直流电机转速控制算法具有更快的收敛速度以及较小的超调现象,鲁棒性也更好.