PI Ziegler-Nichols预测控制在机器人位置伺服控制中的应用

针对机器人姿态变换时伺服电机位置控制中惯量和负载转矩的变化,提出了一种PI Ziegler-Nichols预测并行控制策略。设计了PI Ziegler-Nichols控制器与预测控制器,PI Ziegler-Nichols控制可对传统PI控制器的比例、积分系数进行在线调整,抑制了参数变化和负载扰动,预测控制在误差较大时能够提高收敛速度并具有较好的跟踪能力。仿真结果表明,并行控制策略具有较好的稳定性和动态跟踪精度,当系统参量产生变化时,PI Ziegler-Nichols预测控制器可自适应调整,在机器人伺服系统中可实现较好的位置控制精度和较快的响应速度。

基于Ziegler-Nichols整定的PQF三辊连轧液压压下控制系统频域分析

通过对内蒙古某无缝钢管厂的φ159 mm三辊连轧管机组液压压下控制系统的研究,建立了该系统各环节数学模型,忽略一些次要的非线性因素,将系统做线性化处理;运用经典控制论推导出传递函数,并对系统的时域、频域进行分析;基于该系统响应时间长、存在稳态误差的特点,运用Ziegler-Nichols整定参数方法进行PI、PID控制,并运用MATLAB软件进行仿真,得到理想的参数,满足连轧机压下控制系统的要求。

基于Ziegler-Nichols优化算法的火电机组负荷频率PID控制研究

随着风电和光伏接入电网的规模不断扩大,电网负荷峰谷差逐渐增加,电网的频率控制出现超调量过大、调节速度过慢等一系列问题。本文针对互联电力系统的负荷分配以及频率控制问题,提出考虑发电机组分配系数的互联电力系统负荷频率控制方法。首先,建立单个区域包含多个火电机组的两区域电网自动发电控制(AGC)系统仿真模型,根据各发电机组的煤耗特性建立经济性目标函数,并且获得最优的出力分配系数;然后,基于联络线功率和频率偏差控制(TBC-TBC)的控制模式,采用经Ziegler-Nichols相关算法优化后的PID控制,并对优化后PID控制器的鲁棒性进行分析研究;最后,基于两区域系统仿真模型,在一定的负荷扰动工况下进行仿真验证。仿真结果表明:该分配方法能够有效节省煤耗,本文算法优化后的PID控制器在频率恢复速度方面具有一定的优势,并且鲁棒性良好。

Cessna-172P自动驾驶机翼水平调整器Ziegler-Nichols PID控制方法

针对Cessna-172P自动驾驶机翼水平调整器PID控制参数设计离线工作量大的问题,提出了Ziegler-Nichols PID控制方法。Ziegler-Nichols PID控制器的自适应过程不需要系统的任何先验知识,也不需要建立任何对象模型,可以保证控制回路始终运行在最佳状态。设计方法通过对Cessna-172P自动驾驶机翼水平调整器达到自适应控制,结合JSBSim飞行仿真系统对其进行初步仿真。仿真实验结果证明,所设计的驾驶机翼水平调整器在全局范围内具有良好的动态响应性能。

Ziegler-Nichols法在双容水箱中的Simulink仿真过程的研究

主要利用Ziegler-Nichols法对双容控制系统进行PID参数的整定,从而对液位达到自适应控制,并基于MAT-LAB中的Simulink对其进行初步仿真。PID控制一直是众多方法应用最为普遍的方法,具有稳定性好,可靠性高等优点,尤其适用于可建立数学模型的控制系统,所以可以利用该方法,确定最优PID参数,对实际条件下的双容及多容水箱的进一步研究有一定的参考价值。

基于粒子群算法与改进Ziegler-Nichols算法的PID整定方法

针对Ziegler-Nichols算法设计的PID控制器阶跃响应不理想,不具有灵活性等缺点,提出基于粒子群算法与改进Ziegler-Nichols算法的PID整定方法。采用粒子群算法优化了Ziegler-Nichols算法中的幅值和相角,设计了具有更好性能指标的PID控制器。实验结果表明采用该方法进行参数整定后的PID控制器响应速度较快,降低了系统的超调量。

基于Ziegler-Nichols频域PID的水轮机自适应调速系统设计

针对水轮机常规PID调速器不能根据系统的动态过程自动调整控制参数的缺点,文章提出一种基于响应曲线的Ziegler-Nichols频域整定方法,在电力系统负荷不断变化时,根据水轮机调速系统Ziegler-Nichols根轨迹在线辨识出过程对象的临界振荡频率,然后基于Zieger-Nichols参数整定规则在线更新PID控制器参数.PID控制器的自适应过程能够在线实时修正PID参数,使控制器适应被控对象参数的任何变化,可以保证控制回路始终运行在最佳状态.结果表明,该方法具有较强的鲁棒性及自适应能力,且实时性强,易于实施,可以满足电网稳定性能指标要求.

On the Misunderstanding of the Ziegler-Nichols's Formulae Usage

In the Ziegler-Nichols' s method of reaction curve,the proportional gain should be calculated as an inverse relation of the plant steady-state gain. One of the reasons behind this is to avoid an excessively high loop gain, which can jeopardize many required characteristics of the closed loop. However, many reports, scientific papers and books have been neglecting such gain compensation in the tuning formulae.This brief presents a comprehensive discussion about such uncompensated tuning rules. The main paper finding is that either the stability margin or the disturbance rejection is reduced in this case. A theoretical analysis is performed to obtain the main result. Moreover, a consistent simulation study is also performed to show the impact of the lack of compensation on performance.

Application of artificial neural networks in optimal tuning of tuned mass dampers implemented in high-rise buildings subjected to wind load

High-rise buildings are usually considered as flexible structures with low inherent damping. Therefore, these kinds of buildings are susceptible to wind-induced vibration. Tuned Mass Damper（TMD） can be used as an effective device to mitigate excessive vibrations. In this study, Artificial Neural Networks is used to find optimal mechanical properties of TMD for high-rise buildings subjected to wind load. The patterns obtained from structural analysis of different multi degree of freedom（MDF） systems are used for training neural networks. In order to obtain these patterns, structural models of some systems with 10 to 80 degrees-of-freedoms are built in MATLAB/SIMULINK program. Finally, the optimal properties of TMD are determined based on the objective of maximum displacement response reduction. The Auto-Regressive model is used to simulate the wind load. In this way, the uncertainties related to wind loading can be taken into account in neural network’s outputs. After training the neural network, it becomes possible to set the frequency and TMD mass ratio as inputs and get the optimal TMD frequency and damping ratio as outputs. As a case study, a benchmark 76-story office building is considered and the presented procedure is used to obtain optimal characteristics of the TMD for the building.

Ziegler-Nichols Customization for Quadrotor Attitude Control under Empty and Full Loading Conditions

An aircraft quadrotor is a complex control system that allows for great flexibility in flight.Controlling multirotor aerial systems such as quadrotors is complex because the variables involved are not always available,known,and accurate.The inclusion of payload changes the dynamic characteristics of the aircraft,making it necessary to adapt the control system for this situation.Among the various control methods that have been investigated,proportional-integralderivative(PID)control offers good results and simplicity of application;however,achieving stability and high performance is challenging,with the most critical task being tuning the controller gains.The Ziegler-Nichols(ZN)theory was used to tune the controller gains for pitch and roll attitude command;however,the performance results were not satisfactory.The response of this system was refined,resulting in an improvement in the reference tracking and the rejection of disturbances.This particular refinement was applied to the quadrotor,and via a reverse calculation,the parameters that allow the tuning of PID gains were obtained,based on ZN.The particularization of the ZN theory applied to a quadrotor with and without a load(termed ZNAQ and ZNAQL,respectively)is proposed and results in a significant improvement in the control system response performance(up to 75%),demonstrating that ZNAQ and ZNAQL are valid for tuning the controller PID gains and are more efficient than the original ZN theory approach.

采用Ziegler-Nichols-PID算法的激光红外多通池压强控制系统研制

为了实现CO2气体同位素的高性能检测,研制了高精度、高稳定性的激光红外多通池压强控制系统。硬件方面,采用压强传感器连接于多通池前、后端,检测多通池内部气压,主控制器通过PWM信号,调控多通池前、后端比例阀导通状态,从而实现压强的闭环控制。软件方面,采用Ziegier-Nichols工程整定方法,完成对P、I、D3个参数的确定。结果表明:多通池压强为60 Torr(1 Torr=133.322 Pa)时,控制精度为±0.04 Torr。试验中,利用研制的多通池压强控制系统对13CO2、12CO2气体分子在4.3μm吸收光谱进行测量。随着气体压强从0.026~0.066 atm(1 atm=101325 Pa),13CO2和12CO2气体分子吸收光谱的峰值随着压强增大而增大,吸收光谱宽度也随着压强的增大而增大。同时,利用红外气体检测系统对CO2同位素丰度进行长达2 h的测量。CO2同位素丰度均值为-9.081‰,测量值在-8.351‰^-9.736‰之间波动,最大偏差值为0.73‰。可以证明:该系统为红外CO2气体同位素的高性能检测提供可靠保障。

Ziegler-Nichols方法在发动机怠速控制器整定中的应用

当被控对象的结构和参数不够清楚,或得不到精确的数学模型时,应用PID控制技术最为方便。PID控制最大的优点是不需要了解被控对象的数学模型,只要调节控制参数就可以取得满意的控制效果。因此确定控制参数的值是对系统进行控制的关键。在实际应用中,控制参数应该避免复杂的计算公式,一般是用试凑法来确定。由于三个参数对控制效果的相互影响,得到精确的控制参数并不容易。Ziegler-Nichols方法是一种整定PID控制器,探索其控制参数的方法。在发动机怠速控制器参数整定中应用这一方法可以快速精确的算出相应的各参数数值,得到理想的控制效果。

A highly sensitive LITES sensor based on a multi-pass cell with dense spot pattern and a novel quartz tuning fork with low frequency

A highly sensitive light-induced thermoelectric spectroscopy(LITES)sensor based on a multi-pass cell(MPC)with dense spot pattern and a novel quartz tuning fork(QTF)with low resonance frequency is reported in this manuscript.An erbi-um-doped fiber amplifier(EDFA)was employed to amplify the output optical power so that the signal level was further enhanced.The optical path length(OPL)and the ratio of optical path length to volume(RLV)of the MPC is 37.7 m and 13.8 cm^(-2),respectively.A commercial QTF and a self-designed trapezoidal-tip QTF with low frequency of 9461.83 Hz were used as the detectors of the sensor,respectively.The target gas selected to test the performance of the system was acetylene(C2H2).When the optical power was constant at 1000 mW,the minimum detection limit(MDL)of the C2H2-LITES sensor can be achieved 48.3 ppb when using the commercial QTF and 24.6 ppb when using the trapezoid-al-tip QTF.An improvement of the detection performance by a factor of 1.96 was achieved after replacing the commer-cial QTF with the trapezoidal-tip QTF.

Morphological disruption and visual tuning alterations in the primary visual cortex in glaucoma(DBA/2J)mice

Glaucoma is a leading cause of irreve rsible blindness wo rldwide,and previous studies have shown that,in addition to affecting the eyes,it also causes abnormalities in the brain.However,it is not yet clear how the primary visual cortex(V1)is altered in glaucoma.This study used DBA/2J mice as a model for spontaneous secondary glaucoma.The aim of the study was to compare the electrophysiological and histomorphological chara cteristics of neurons in the V1between 9-month-old DBA/2J mice and age-matched C57BL/6J mice.We conducted single-unit recordings in the V1 of light-anesthetized mice to measure the visually induced responses,including single-unit spiking and gamma band oscillations.The morphology of layerⅡ/Ⅲneurons was determined by neuronal nuclear antigen staining and Nissl staining of brain tissue sections.Eighty-seven neurons from eight DBA/2J mice and eighty-one neurons from eight C57BL/6J mice were examined.Compared with the C57BL/6J group,V1 neurons in the DBA/2J group exhibited weaker visual tuning and impaired spatial summation.Moreove r,fewer neuro ns were observed in the V1 of DBA/2J mice compared with C57BL/6J mice.These findings suggest that DBA/2J mice have fewer neurons in the VI compared with C57BL/6J mice,and that these neurons have impaired visual tuning.Our findings provide a better understanding of the pathological changes that occur in V1 neuron function and morphology in the DBA/2J mouse model.This study might offer some innovative perspectives regarding the treatment of glaucoma.

Manipulation of High-Fidelity Sidebands under Large Detuning by Floquet Technology:Application to Multi-Mode Cooling

The Floquet technology,a powerful way to manipulate quantum states,is employed to drive sidebands transition under large detuning.Our results demonstrate that high fidelities over 99%can be achieved through optimizing suitable modulation frequencies under large detuning.We observe high-fidelity transitions within a high bandwidth by utilizing a single modulation frequency and reveal that this capability is due to the emergence of a flat-band structure in the bandwidth range.The key finding of high-fidelity sideband manipulation under large detuning is experimentally confirmed in nuclear magnetic resonance platform.Finally,we propose a new parallel sideband cooling scheme that enables simultaneous cooling of multiple motional modes.This approach improves the cooling rate compared to conventional schemes with fixed laser frequency and power,and eliminates the need for mode-specific addressing.Our Floquet parallel scheme is applicable to any harmonic oscillator system and is not limited by bandwidth in theory.

Conceptual design of a 714-MHz RFQ for compact proton injectors and development of a new tuning algorithm on its aluminium prototype

Radio frequency quadrupoles(RFQs),which are crucial components of proton injectors,significantly affect the performance of proton accelerator facilities.An RFQ with a high frequency of 714 MHz dedicated to compact proton injectors for medi-cal applications is designed in this study.The RFQ is designed to accelerate proton beams from 50 keV to 4 MeV within a short length of 2 m and can be matched closely with the downstream drift tube linac to capture more particles through a preliminary optimization.To develop an advanced RFQ,challenging techniques,including fabrication and tuning method,must be evaluated and verified using a prototype.An aluminium prototype is derived from the conceptual design of the RFQ and then redesigned to confirm the radio frequency performance,fabrication procedure,and feasibility of the tuning algorithm.Eventually,a new tuning algorithm based on the response matrix and least-squares method is developed,which yields favorable results based on the prototype,i.e.,the errors of the dipole and quadrupole components reduced to a low level after several tuning iterations.Benefiting from the conceptual design and techniques obtained from the prototype,the formal mechanical design of the 2-m RFQ is ready for the next manufacturing step.

基于prompt tuning的中文文本多领域情感分析研究

不同领域的情感文本表达方式不一样,通常需要为各个领域训练相应的情感分析模型。针对无法用一个模型进行高效多领域情感分析的问题,提出了基于提示微调(prompt tuning)的多领域文本情感分析方法MSAPT。借助hard prompt,指示情感文本的所属领域和待选的情感标签,调动不同领域情感分析相关的知识,再为情感分析预训练一个统一的“通才模型”,在下游的各领域文本学习中,保持模型冻结,通过prompt tuning使模型学习到下游各领域情感文本的特征。MSAPT仅需保存一个模型和一些参数量远远小于模型的prompt,实现了多领域情感分析。在多个属于不同领域的情感文本数据集上进行实验,结果表明仅进行prompt tuning时,MSAPT效果优于模型微调(model tuning)的。最后,分别对适应特定领域的prompt tuning、hard prompt、soft prompt的长度和中间训练数据集的大小进行消融实验,从证明其对情感分析效果的影响。

Improved isochronous mass spectrometry with tune measurement

In conventional isochronous mass spectrometry(IMS)performed on a storage ring,the precision of mass measurements for short-lived nuclei depends on the accurate determination of the revolution times(T)of stored ions.However,the resolution of T inevitably deteriorates due to the magnetic rigidity spread of the ions,limiting the mass-resolving power.In this study,we used the betatron tunes Q(the number of betatron oscillations per revolution)of the ions and established a correlation between T and Q.From this correlation,T was transformed to correspond to a fixed Q with higher resolution.Using these transformed T values,the masses of ^(63)Ge,^(65)As,^(67)Se,and ^(71)Kr agreed well with the mass values measured using the newly developed IMS(Bρ-IMS).We also studied the systematics of Coulomb displacement energies(CDEs)and found that anomalous staggering in CDEs was eliminated using new mass values.This method of T transformation is highly effective for conventional IMS equipped with a single time-of-flight detector.

Vibration attenuation performance of wind turbine tower using a prestressed tuned mass damper under seismic excitation

With the rapid development of large megawatt wind turbines,the operation environment of wind turbine towers(WTTs)has become increasingly complex.In particular,seismic excitation can create a resonance response and cause excessive vibration of the WTT.To investigate the vibration attenuation performance of the WTT under seismic excitations,a novel passive vibration control device,called a prestressed tuned mass damper(PS-TMD),is presented in this study.First,a mathematical model is established based on structural dynamics under seismic excitation.Then,the mathematical analytical expression of the dynamic coefficient is deduced,and the parameter design method is obtained by system tuning optimization.Next,based on a theoretical analysis and parameter design,the numerical results showed that the PS-TMD was able to effectively mitigate the resonance under the harmonic basal acceleration.Finally,the time-history analysis method is used to verify the effectiveness of the traditional pendulum tuned mass damper(PTMD)and the novel PS-TMD device,and the results indicate that the vibration attenuation performance of the PS-TMD is better than the PTMD.In addition,the PS-TMD avoids the nonlinear effect due to the large oscillation angle,and has the potential to dissipate hysteretic energy under seismic excitation.

Multiscale and Auto-Tuned Semi-Supervised Deep Subspace Clustering and Its Application in Brain Tumor Clustering

In this paper,we introduce a novel Multi-scale and Auto-tuned Semi-supervised Deep Subspace Clustering(MAS-DSC)algorithm,aimed at addressing the challenges of deep subspace clustering in high-dimensional real-world data,particularly in the field of medical imaging.Traditional deep subspace clustering algorithms,which are mostly unsupervised,are limited in their ability to effectively utilize the inherent prior knowledge in medical images.Our MAS-DSC algorithm incorporates a semi-supervised learning framework that uses a small amount of labeled data to guide the clustering process,thereby enhancing the discriminative power of the feature representations.Additionally,the multi-scale feature extraction mechanism is designed to adapt to the complexity of medical imaging data,resulting in more accurate clustering performance.To address the difficulty of hyperparameter selection in deep subspace clustering,this paper employs a Bayesian optimization algorithm for adaptive tuning of hyperparameters related to subspace clustering,prior knowledge constraints,and model loss weights.Extensive experiments on standard clustering datasets,including ORL,Coil20,and Coil100,validate the effectiveness of the MAS-DSC algorithm.The results show that with its multi-scale network structure and Bayesian hyperparameter optimization,MAS-DSC achieves excellent clustering results on these datasets.Furthermore,tests on a brain tumor dataset demonstrate the robustness of the algorithm and its ability to leverage prior knowledge for efficient feature extraction and enhanced clustering performance within a semi-supervised learning framework.