Quantum control based on three forms of Lyapunov functions

This paper introduces the quantum control of Lyapunov functions based on the state distance, the mean of imaginary quantities and state errors.In this paper, the specific control laws under the three forms are given.Stability is analyzed by the La Salle invariance principle and the numerical simulation is carried out in a 2D test system.The calculation process for the Lyapunov function is based on a combination of the average of virtual mechanical quantities, the particle swarm algorithm and a simulated annealing algorithm.Finally, a unified form of the control laws under the three forms is given.

Formation mechanism and organizational controlling of ultra-fine-grain copper processed by asymmetrical accumulative rolling-bond and annealing

The initial copper with large grain sizes of 60-100 μm was processed by six passes asymmetrical accumulative rolling-bond （AARB） and annealing, the ultra-fine-grained （UFG） copper with grain size of 200 nm was obtained, and the microstructures and properties were studied. The results show that there are large sub-structures and also texture component C for the UFG copper obtained by six passes AARB, possessing high strength and microhardness in company with poor elongation and conductivity. Thereafter, the UFG copper was annealed at 220 °C for 35 min, in which the sub-structures disappear, the grain boundaries are composed of big angle grain boundaries, and the textures are composed of a variety of texture components and parts of twins. Compared with the UFG copper obtained by six passes AARB, the tensile strength and yield strength for the UFG copper obtained by six passes AARB and annealing at 220 °C for 35 min are decreased slightly, the elongation and conductivity are improved obviously.

Control parameter optimal tuning method based on annealing-genetic algorithm for complex electromechanical system

A new searching algorithm named the annealing-genetic algorithm(AGA) was proposed by skillfully merging GA with SAA. It draws on merits of both GA and SAA ,and offsets their shortcomings.The difference from GA is that AGA takes objective function as adaptability function directly,so it cuts down some unnecessary time expense because of float-point calculation of function conversion.The difference from SAA is that AGA need not execute a very long Markov chain iteration at each point of temperature, so it speeds up the convergence of solution and makes no assumption on the search space,so it is simple and easy to be implemented.It can be applied to a wide class of problems.The optimizing principle and the implementing steps of AGA were expounded. The example of the parameter optimization of a typical complex electromechanical system named temper mill shows that AGA is effective and superior to the conventional GA and SAA.The control system of temper mill optimized by AGA has the optimal performance in the adjustable ranges of its parameters.

Hybrid Optimization Based PID Controller Design for Unstable System

PID controllers play an important function in determining tuning para-meters in any process sector to deliver optimal and resilient performance for non-linear,stable and unstable processes.The effectiveness of the presented hybrid metaheuristic algorithms for a class of time-delayed unstable systems is described in this study when applicable to the problems of PID controller and Smith PID controller.The Direct Multi Search(DMS)algorithm is utilised in this research to combine the local search ability of global heuristic algorithms to tune a PID controller for a time-delayed unstable process model.A Metaheuristics Algorithm such as,SA(Simulated Annealing),MBBO(Modified Biogeography Based Opti-mization),BBO(Biogeography Based Optimization),PBIL(Population Based Incremental Learning),ES(Evolution Strategy),StudGA(Stud Genetic Algo-rithms),PSO(Particle Swarm Optimization),StudGA(Stud Genetic Algorithms),ES(Evolution Strategy),PSO(Particle Swarm Optimization)and ACO(Ant Col-ony Optimization)are used to tune the PID controller and Smith predictor design.The effectiveness of the suggested algorithms DMS-SA,DMS-BBO,DMS-MBBO,DMS-PBIL,DMS-StudGA,DMS-ES,DMS-ACO,and DMS-PSO for a class of dead-time structures employing PID controller and Smith predictor design controllers is illustrated using unit step set point response.When compared to other optimizations,the suggested hybrid metaheuristics approach improves the time response analysis when extended to the problem of smith predictor and PID controller designed tuning.

Erratum to “Adaptive Control of DC-DC Converter Using Simulated Annealing Optimization Method” [Journal of Signal and Information Processing, (2014), 5, 198-207]

The purpose of this paper is to present a new adaptive control method used to adjust the output voltage and current of a DC-DC (DC: Direct Current) power converter under different sudden changes in load. The controller used is a PID controller (Proportional, Integrator, and Differentiator). The gains of the PID controller (KP, KI and KD) tuned using Simulated Annealing (SA) algorithm which is part of Generic Probabilistic Metaheuristic family. The new control system is expected to have a fast transient response feature, with less undershoot of the output voltage and less overshoot of the reactor current. Pulse Width Modulation (PWM) will be utilized to switch the power electronic devices.

Adaptive Control of DC-DC Converter Using Simulated Annealing Optimization Method

The purpose of this paper is to present a new adaptive control method used to adjust the output voltage and current of DC-DC (DC: Direct Current) power converter under different sudden changes in load. The controller is a PID controller (Proportional, Integrator, and Differentiator). The gains of the PID controller (KP, KI and KD) tuned using Simulated Annealing (SA) algorithm which is part of Generic Probabilistic Metaheuristic family. The new control system is expected to have a fast transient response feature, with less undershoot of the output voltage and less overshoot of the reactor current. Pulse Width Modulation (PWM) will be utilized to switch the power electronic devices.

Research on the Applications of Cyclic Water Quality Model and Simulated Annealing Algorithm for Water Pollution Control and Planning

With the progress of computer technology, water pollution control and planning has been a hot topic in the scientific community. This paper discusses corresponding research on the applications of cyclic water quality model and simulated annealing algorithm for water pollution control and planning. Environmental engineering education has been the focus of much attention in recent years. Teaching methods of water pollution control and sustainable teaching innovation and creation was explored by many scholars, and the majority of workers engaged in teaching the course. The simulation result proves the effectiveness of the method. We plan to conduct more research in the future research to obtain better research result.

THD Reduction for Permanent Magnet Synchronous Motor Using Simulated Annealing

Any nonlinear behavior of the system is analyzed by a useful way of Total Harmonic Distortion(THD)technique.Reduced THD achieves lower peak current,higher efficiency and longer equipment life span.Simulated annealing(SA)is applied due to the effectiveness of locating solutions that are close to ideal and to challenge large-scale combinatorial optimization for Permanent Magnet Synchronous Machine(PMSM).The parameters of direct torque controllers(DTC)for the drive are automatically adjusted by the optimization algorithm.Advantages of the PI-Fuzzy-SA algorithm are retained when used together.It also improves the rate of system convergence.Speed response improvement and har-monic reduction is achieved with SA-based DTC for PMSM.This mechanism is known to be faster than other algorithms.Also,it is observed that as compared to other algorithms,the projected algorithm yields a reduced total harmonic distor-tion.As a result of the employment of Space Vector Modulation(SVM)techni-que,the system is resistant to changes in motor specifications and load torque.Through MATLAB&Simulink simulation,the experiment is done and the per-formance is calculated for the controller.

安钢冷轧1550 mm连退炉内张力控制与分析

结合安钢冷轧连退机组实际工艺流程,以安钢冷轧1 550 mm连退机组退火炉为研究平台,分析与研究了其炉内带钢张力,这对于薄带钢高速运行低张控制优化具有一定指导意义,可实现冷轧连退薄带钢高效化生产。

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。

基于改进灰狼优化模糊PI的退火炉流量控制系统研究

为解决铝退火炉燃烧过程中空气和燃气流量控制效果不佳,导致空燃比不稳定的问题,提出一种以双交叉限幅、模糊PI控制器及Smith预估器相结合的控制模型,并引入改进灰狼优化算法对双交叉限幅中偏置因子和模糊控制器中的量化因子、比例因子进行寻优的控制方法。首先,通过对双交叉限幅的控制来降低空燃比变化幅度,从而稳定燃烧过程;其次,结合铝退火炉流量系统模型的特点,通过Smith预估器提高系统响应速度,并结合PI和模糊控制的优点,建立模糊PI控制系统模型;然后,利用改进灰狼优化算法的迭代寻优能力,对双交叉限幅偏置因子以及模糊PI量化和比例因子进行优化;最后,以铝退火炉常用的燃气流量30 m3·h-1为例,在Simulink中对所设计的控制模型进行仿真。仿真结果表明,所提出的控制方法无超调量、无振荡,相较于传统的PI控制流量,调节时间有所减少,并且提高了铝退火炉燃烧过程中流量的控制精度。

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ESP32的激光器控制系统设计

阐述针对激光退火设备中对多种类型激光器控制需求及安全保护,设计一套激光器控制系统。设计基于ESP32主控芯片,集成2.4GHz Wi-Fi和蓝牙双模的单芯片方案,采用台积电超低功耗的40nm工艺,具有超高的射频性能、稳定性、通用性和可靠性。Wi-Fi和蓝牙等通信传输功能,更加适配未来的工业互联网模式,同时主控芯片具有丰富的数字模拟输入输出接口资源以及丰富的I2C/SPI等总线通讯方式,适用于各种应用场景。

基于节点移动性的水下动态拓扑控制方法

针对水下传感器节点随洋流移动导致的网络覆盖率和连通率较低的问题,提出一种新的水下动态拓扑控制方法。节点部署阶段,利用模拟退火算法计算节点的期望部署位置,并采用蜿蜒洋流移动模型预测节点的实际部署位置,节点无须消耗额外能量调节自身位置即可保持网络的全连通和高覆盖率;拓扑优化阶段,以最大化延长网络寿命为目标,自主水下航行器根据节点实时情况执行高效的拓扑优化策略。仿真结果表明,与现有的CDA、SLO及随机部署方案相比,提出的新方法在保持全连通性的前提下具有更好的覆盖率和平均节点度;节点存活率和数据包传输成功率分别提升了11.6%和11.53%,有效提高了网络寿命。

基于多目标优化的采煤机截割最优运动参数匹配策略

为避免采煤机电机过载损伤,使其持续可靠高效运行,提出一种基于多目标优化的采煤机截割最优运动学参数匹配控制策略,根据采煤机滚筒的生产率和块煤率等性能指标建立数学模型,构建总的目标函数,采用模拟退火的粒子群算法对其进行寻优,通过构建最优运动学参数匹配模块,仿真分析采煤机截割-牵引协同控制系统。结果表明,与传统采煤机控制方法相比,系统能随着实时工况的变化较好地跟踪最优牵引电机转速和滚筒转速,采煤机生产率降低了3.2%,但块煤率提高了138.5%,截割比能耗总体降低了30.8%,装煤率提高了40%,采煤机的综合性能指标达到最优。

一种工业退火炉保护气切换控制策略的优化

某工业退火炉保护气切换控制由于其炉况特性,其温度数据传输极易造成滞后或中断,而温度数据是切换控制条件的重要组成部分,原DCS系统中的切换控制策略对此也缺乏应对措施,这将极易造成误切换。针对工业退火炉保护气切换控制存在的上述问题,对保护气切换策略进行了优化,通过新增计时器模块,对控制炉段前的工艺控制情况计时,并将计时器模块的输出状态引入到新的切换控制策略中,自动判断切换工艺条件,有效提高了退火炉保护气切换稳定性,取得了较好的控制效果。

硅钢脱碳退火机组卷取机弱磁区张力优化

由于近期硅钢市场需求强劲,连续退火机组投产10年后面临提速、提质的要求,材质单层越来越薄,整卷后工序成材率、让步率,受到卷取张力的影响越来越明显,通过研究张力控制的原理及张力优化方案、建立实际作用于带钢卷取的张力模型,逐步排查出处于弱磁区的卷取机异步电机转矩精度、线性度不足,针对电机传动(逆变器)、PLC程序的优化使得转矩精度达到工艺的要求。

冷轧连退板锈蚀问题与控制技术探究

冷轧连退板的锈蚀对其性能和使用寿命具有显著影响。为了确保产品的质量和安全性,必须采取有效的控制和防护措施来预防和减轻锈蚀的影响。总结梳理了冷轧连退板锈蚀问题的影响因素,探究冷轧连退板锈蚀控制技术,旨在为冷轧连退板锈蚀问题防控提供一定指导,促进冷轧连退板的安全、有效应用。

基于改进粒子群算法的湿法冶金技术优化控制

分析了湿法冶金技术的关键工艺,构建了优化控制模型,并利用自适应惯性权重和模拟退火算子对粒子群算法进行改进,对湿法冶金技术进行优化控制。仿真试验结果显示:在A风力发电场优化数据集中测试中,AIW-SAO-PSO算法迭代225次时趋于稳定,适应度值约为0.165,且迭代100次时,算法的均方根误差、平均绝对误差、相对标准偏差分别为0.0080,0.0045和0.971%;在湿法冶金技术优化控制模型的寻优求解中,得到的综合效益值为1.9×10^(5)元/h,与目标期待值的绝对误差约为0.1×10^(4)元/h。实现了湿法冶金技术的优化控制,并为同类型优化控制提供理论支持。

基于质量控制方法的电子驻车制动系统开关开裂的问题研究

电子驻车制动系统开关外壳一般通过注塑成型制得,是电子驻车制动系统的触发接口。针对某车型售后开关开裂问题,通过采用质量控制方法探究开关外壳开裂的原因,对各个末端因素进行了逐个确认,最终明确失效的直接原因是退火的工序执行不到位,并据此制定了改进策略,从而有效改善了开关外壳质量,为类似塑料制品开裂问题提供了参考。