Fundamental Properties and Optimal Gains of a Steady-State Velocity Measured <i>α</i>-<i>β</i>Tracking Filter

This paper clarifies the steady-state properties and performance of an α-β filter for moving target tracking using both position and velocity measurements. We call this filter velocity measured α-β (VM-α-β) filter. We first derive the stability condition and steady-state predicted errors as fundamental properties of the VM-α-β filter. The optimal gains for representative motion models are then derived from the Kalman filter equations. Theoretical and numerical analyses verify that VM-α-β filters with these optimal gains realize more accurate tracking than conventional α-β filters when the filter gains are relatively large. Our study reveals the conditions under which the predicted errors of the VM-α-β filters are less than those of conventional α-β filters. Moreover, numerical simulations clarify that the variance of the tracking error of the VM-α-β filters is approximately 3/4 of that of the conventional α-β filters in realistic situations, even when the accuracy of the position/velocity measurements is the same.

Optimal feedback gains of a delayed proportional-derivative(PD) control for balancing an inverted pendulum

In the dynamics analysis and synthesis of a controlled system, it is important to know for what feedback gains can the controlled system decay to the demanded steady state as fast as possible. This article presents a systematic method for finding the optimal feedback gains by taking the stability of an inverted pendulum system with a delayed proportional-derivative controller as an example. First, the condition for the existence and uniqueness of the stable region in the gain plane is obtained by using the D-subdivision method and the method of stability switch. Then the same procedure is used repeatedly to shrink the stable region by decreasing the real part of the rightmost characteristic root. Finally, the optimal feedback gains within the stable region that minimizes the real part of the rightmost root are expressed by an explicit formula. With the optimal feedback gains, the controlled inverted pendulum decays to its trivial equilibrium at the fastest speed when the initial values around the origin are fixed. The main results are checked by numerical simulation.

STEADY-STATE AND IDLE OPTIMIZA-TION OF INTERNAL COMBUSTION ENGINE CONTROL STRATEGIES FOR HYBRID ELECTRIC VEHICLES

A novel steady-state optimization （SSO） of internal combustion engine （ICE） strategy is proposed to maximize the efficiency of the overall powertrain for hybrid electric vehicles, in which the ICE efficiency, the efficiencies of the electric motor （EM） and the energy storage device are all explicitly taken into account. In addition, a novel idle optimization of ICE strategy is implemented to obtain the optimal idle operating point of the ICE and corresponding optimal parking generation power of the EM using the view of the novel SSO of ICE strategy. Simulations results show that potential fuel economy improvement is achieved relative to the conventional one which only optimized the ICE efficiency by the novel SSO of ICE strategy, and fuel consumption per voltage increment decreases a lot during the parking charge by the novel idle optimization of ICE strategy.

Steady-state Voltage Security-constrained Optimal Frequency Control for Weak HVDC Sending-end AC Power Systems

Due to the fact that a high share of renewable energy sources(RESs)are connected to high-voltage direct current(HVDC)sending-end AC power systems,the voltage and frequency regulation capabilities of HVDC sending-end AC power systems have diminished.This has resulted in potential system operating problems such as overvoltage and overfrequency,which occur simultaneously when block faults exist in the HVDC link.In this study,a steady-state voltage security-constrained optimal frequency control method for weak HVDC sending-end AC power systems is proposed.The integrated virtual inertia control of RESs is employed for system frequency regulation.Additional dynamic reactive power compensation devices are utilized to control the voltage of all nodes meet voltage security constraints.Then,an optimization model that simultaneously considers the frequency and steady-state voltage security constraints for weak HVDC sending-end AC power systems is established.The optimal control scheme with the minimum total cost of generation tripping and additional dynamic reactive power compensation required is obtained through the optimization solution.Simulations are conducted on a modified IEEE 9-bus test system and practical Qing-Yu line commutated converter based HVDC(LCC-HVDC)sending-end AC power system to verify the effectiveness of the proposed method.

Development and Experimental Evaluation of a Steady-state Model for the Step-feed Biological Nitrogen Removal Process

In this article,a steady-state mathematical model was developed and experimentally evaluated to inves- tigate the effect of influent flow distribution and volume ratios of anoxic and aerobic zones in each stage on the to- tal nitrogen concentration of the effluent in the step-feed biological nitrogen removal process.Unlike the previous modeling methods,this model can be used to calculate the removal rates of ammonia and nitrate in each stage and thereby predict the concentrations of ammonia,nitrate,and total nitrogen in the effluent.To verify the simulation results,pilot-scale experimental studies were carried out in a four-stage step feed process.Good correlations were achieved between the measured data and the simulation results,which proved the validity of the developed model. The sensitivity of the model predictions was analyzed.After verification of the validity,the step feed process was optimally operated for five months using the model and the criteria developed for the design and operation.During the pilot-scale experimental period,the effluent total nitrogen concentrations were all below 5mg·L -1 ,with more than 90%removal efficiency.

Improved Disturbance Observer (DOB) Based Advanced Feedback Control for Optimal Operation of a Mineral Grinding Process

Advanced feedback control for optimal operation of mineral grinding process is usually based on the model predictive control (MPC) dynamic optimization. Since the MPC does not handle disturbances directly by controller design, it cannot achieve satisfactory effects in controlling complex grinding processes in the presence of strong disturbances and large uncertainties. In this paper, an improved disturbance observer (DOB) based MPC advanced feedback control is proposed to control the multivariable grinding operation. The improved DOB is based on the optimal achievable H 2 performance and can deal with disturbance observation for the nonminimum-phase delay systems. In this DOB-MPC advanced feedback control, the higher-level optimizer computes the optimal operation points by maximize the profit function and passes them to the MPC level. The MPC acts as a presetting controller and is employed to generate proper pre-setpoint for the lower-level basic feedback control system. The DOB acts as a compensator and improves the operation performance by dynamically compensating the setpoints for the basic control system according to the observed various disturbances and plant uncertainties. Several simulations are performed to demonstrate the proposed control method for grinding process operation.

Optimization of three-loop missile autopilot gain under crossover frequency constraint

The open-loop crossover frequency is pointed as an important parameter for practical autopilot design. Since different gain designs may achieve the same open-loop crossover frequency, it should be neither considered as a performance objective of the optimal autopilot design-schemes nor neglected. Besides, the main assignment of the autopilot is to drive the missile to track the acceleration commands, so the autopilot gain design should be evaluated directly according to the resultant tracking performance. For this purpose, an optimal design methodology of the three-loop missile autopilot is introduced based on constraint optimization technique, where the tracking performance is established analytically as the design objective and the open-loop crossover frequency is formed as inequality constraint function, both are manipulated in terms of stable characteristic parameters of the autopilot closed-loop. The proposed technique is implemented with the assistance of a numerical optimization algorithm which automatically adjusts the design parameters. Finally, numerical simulation results are provided to demonstrate the effectiveness and feasibility of the proposed approach compared with that in some references.

Optimization control of modulation-instability gain in photonic crystal fibres with two zero-dispersion wavelengths

We design three kinds of photonic crystal fibres （PCF） with two zero-dispersion wavelengths （ZDWs） using the improved full vector index method （FVIM） and finite-difference frequency domain （FDFD} techniques. Based on these designed fibres, the effect of fibre structure, pump power and wavelength on the modulation instability （MI） gain in the anomalous dispersion region close to the second ZDW of the PCFs is comprehensively analysed in this paper. The analytical results show that an optimal MI gain can be obtained when the optimal pump wavelength （1530 nm） is slightly shorter than the second ZDW （1538 nm） and the optimal pump power is 250 W. Importantly, the total MI gain bandwidth has been increased to 260 nm for the first time, so far as we know, for an optimally-designed fibre with ∧ = 1.4 nm and d/∧ = 0.676, and the gain profile became much smoother. The optimal pump wavelength relies on the second ZDW of the PCF whereas the optimal pump power depends on the corporate operation of the optimal fibre structure and optimal pump wavelength, which is important in designing the most appropriate PCF to attain higher broadband and gain amplification.

Optimal feedback based control for Mars entry trajectory tracking

The various uncertainties of Mars environment have great impact on the process of vehicles entering the atmosphere.To improve the robustness of control system against the model errors and to reduce the computational burden, an optimal feedback based tracking control law is developed. The control scheme presented in this paper determines the amplitude and the reversals of bank angle respectively in the longitudinal and lateral flight plane. At each control cycle, the amplitude of the bank angle is obtained by an optimal feedback controller to minimize tracking errors. The control gains are tuned according to the closed-loop error dynamics by using optimization methods. The bank reversals are executed if the crossrange exceeds a predetermined corridor which is designed by setting a boundary function. The accuracy and robustness of the proposed closed-loop optimal feedback based control law in tracking the reference trajectory is verified via500 deviation simulations, in which modeling errors and external disturbances are considered.

OPTIMAL WAVELET FILTER DESIGN FOR REMOTE SENSING IMAGE COMPRESSION

A new approach for designing the Biorthogonal Wavelet Filter Bank (BWFB) for the purpose of image compression is presented in this letter. The approach is decomposed into two steps. First, an optimal filter bank is designed in theoretical sense based on Vaidyanathan’s coding gain criterion in SubBand Coding (SBC) system. Then the above filter bank is optimized based on the criterion of Peak Signal-to-Noise Ratio (PSNR) in JPEG2000 image compression system, resulting in a BWFB in practical application sense. With the approach, a series of BWFB for a specific class of applications related to image compression, such as remote sensing images, can be fast designed. Here, new 5/3 BWFB and 9/7 BWFB are presented based on the above approach for the remote sensing image compression applications. Experiments show that the two filter banks are equally performed with respect to CDF 9/7 and LT 5/3 filter in JPEG2000 standard; at the same time, the coefficients and the lifting parameters of the lifting scheme are all rational, which bring the computational advantage, and the ease for VLSI implementation.

基于遗传算法的不等间距阵优化方法

阵元数一定情况下,针对不等间距拖线阵高频信号处理存在的空间增益和无栅瓣兼容问题,提出一种基于遗传算法的不等间距拖线阵阵型优化方法。该方法以频带交互下最大旁瓣级最小作为约束因子,通过模拟生物自然进化过程搜索全局最优解,得到优化后的阵元位置。优化后阵型在保证低频信号处理空间增益不变情况下,实现对高频信号高空间增益、无栅瓣处理。计算机仿真结果表明:相比未优化阵型,在高频信号处理方面,优化后阵型在无栅瓣情况下,空间增益提升值近似理论值提升值;在低频信号处理方面,优化后阵型具有相同的空间增益。为实际不等间距拖线阵阵型优化和应用提供了一种思路。

考虑系统稳定边界的同步调相机励磁与升压变参数联合优化

现有提升调相机动态无功特性的参数优化方法侧重于电磁参数的优化,这给生产企业带来较高的工艺要求和较大的成本压力。针对该问题提出考虑系统稳定约束的调相机励磁系统及升压变参数联合优化方法,分析其对电磁参数优化的可替代性。首先,推导了基于Park模型下调相机的无功频域特性,与6阶实用模型下的无功频域特性对比,基于调相机的Park模型可提升调相机动态无功特性的分析精度。然后,提出根据调相机并网系统的稳定边界确定参数的优化区间,采用频域灵敏度方法确定重点参数,并基于人工鱼群算法进行参数优化。最后,通过仿真结果表明,励磁系统与升压变参数的联合优化,可获得与仅优化电磁参数时相近的调相机动态无功性能,验证了电磁参数优化的可替代性,从而降低调相机的制造成本,扩大同步调相机的应用场合和范围。

多芯超模光纤放大器增益均衡设计(内封底文章)

多芯超模光纤(MCSMF)的芯间距较小,多个芯子共同形成芯区支持多个超模传输,与普通单芯少模光纤相比,其具有较大的有效模场面积和较小的模式串扰,备受关注。MCSMF用于长距离传输时,与其相匹配的新型增益均衡放大器是实现信号中继并保持信号稳定传输的必要器件。文中提出了一种基于粒子群优化算法的19芯超模光纤增益均衡放大器,该光纤支持10个超模共同传输。通过粒子群算法分别优化各纤芯内掺铒浓度来降低不同超模的交叠积分因子,从而减小模式增益差(DMG)。结果表明,在包层泵浦条件下,最大DMG从1.33 dB (各纤芯均匀掺杂)降低至0.20 dB,在1 550 nm信号波长处10模式的平均增益为27.79 dB,且该放大器在整个C波段的增益平坦度低于1 dB。

基于实测数据的公路桥梁动态养修策略自适应优化模型

为了有效利用桥梁管养资源以确保桥梁在运营期的服役安全,本文构建了适用于公路桥梁的管养策略优化模型。基于1996—2020年间国内沿海地区208座及内陆地区176座存在历史养修工作的公路桥梁性能检测数据,建立了考虑养修时服役时长与养修频次的养修增益系数计算方法,并通过极大似然估计法计算出养修增益系数的取值范围。通过将改进逆高斯过程与贝叶斯更新方法结合建立了桥梁动态养修策略模型,并利用大量实测数据对模型性能进行评估,结果表明:模型预测平均相对误差为11.1%,可在一定程度上满足工程需要。采用改进后的灰狼算法对动态养修策略模型中的决策向量进行自适应优化,寻找使得剩余寿命累积成本最低的决策向量,并通过实际桥梁优化算例证实了决策向量最优解的存在以及自适应优化模型的有效性。

自动装配的导纳控制系统中关键影响机制研究

在工业自动装配中,机械卡阻现象经常导致零件接触力增大,进而导致装配失败。本文以汽车装配中车门销与车身孔的装配任务为背景,运用导纳控制方法解决柔顺性难题。受导纳参数(弹性、阻尼和质量)的影响,控制系统可能在稳态误差、超调量和响应速度等方面出现不同程度的波动。为消除稳态误差的影响,本文采用基于倍率调节的积分优化方法成功消除稳态误差。面对超调量和响应速度不平衡的问题,本文提出一种基于罚函数的自动调参算法。通过设置惩罚项,在求解过程中逐渐满足约束条件。实验结果表明:接触力的震荡波动从0.1 N减小至0.05 N,当外界阻抗消失时,缩短50%的回落调整时间。该方法成功避免震荡引起的零件损坏,能够提高自动装配时的柔顺性能。

Optimization Design of Active Structure of Strained MQW DFB Lasers

The well number and the cavity length of 1.55μm wavelength In 1-x-y Ga y Al x As MQW DFB lasers are optimized using a simple model.A low threshold,maximum operating temperature of 550～560K,and high relaxation oscillation frequency of over 30GHz MQW DFB laser is presented.

迭代学习控制器参数的数据驱动自适应整定方法

针对PID型迭代学习控制(iterative learning control,ILC)方法,提出了两种数据驱动自适应整定(data-driven adaptive tuning,DDAT)方法。首先采用紧格式迭代动态线性化(compact form iterative dynamic linearization,CFIDL)方法将原始的非线性系统转化为等价的线性数据模型,设计了一个目标函数来动态地调整PID型ILC的学习增益。其次,通过对设计的目标函数进行优化,提出了一种基于CFIDL的DDAT方法。该方法只使用实际的I/O数据,而不需要任何机理模型信息。进一步,引入偏格式迭代动态线性化(partial form iterative dynamic linearization,PFIDL)方法对结果进行扩展,提出了一种基于PFIDL的DDAT方法。所提出的两种DDAT方法都可以提高PID型ILC对不确定性的鲁棒性。最后,通过仿真验证了两种方法的有效性。

Optimization of Linear Antenna Arrays Based on Genetic Algorithms

The methods of moment and genetic algorithm (GA) are combined to optimize the Yagi Uda antenna array and Log periodic dipole antenna (LPDA) array. The element lengths and spacing are optimized for the Yagi Uda array; while the ratio factor of spacing to length as well as the ratio of length to diameter of the elements are optimized for LPDA array. The results show that the main parameters, such as gain and pattern, have been improved apparently; and the high back lobe level of LPDA can be reduced greatly, therefore, GA is a very competent method for optimizing the linear array as well as in other fields.

融合稀疏注意力机制在DDoS攻击检测中的应用

针对现有的DDoS(distributed denial of service)攻击检测模型面临大量数据时,呈现出检测效率低的问题。为适应当前网络环境,通过研究DDoS攻击检测模型、提取流量特征、计算攻击密度,提出一种基于融合稀疏注意力机制的DDoS攻击检测模型GVBNet(global variable block net),使用攻击密度自适应计算稀疏注意力。利用信息熵以及信息增益分析提取攻击流量的连续字节作为特征向量,通过构建基于GVBNet的网络模型在两种数据集上进行训练。实验结果表明,该方法具有良好的识别效果、检测速度以及抗干扰能力,在不同的环境下具有应用价值。

基于参数优化随机森林模型的消费行为预测算法

在大数据与线上营销的影响下,零售企业也积极采取大数据智能营销方案。为了提高零售企业在消费行为预测中的精准率,从而提高企业销售额获取更大利润,从消费数据、会员数据和商品数据中通过信息增益的方法提取特征,构建基础特征群,挖掘潜在信息。利用遗传算法对随机森林的参数进行优化,建立基于参数优化的随机森林消费行为预测模型,实验数据来自某线下连锁药店37天的消费记录。将实验模型和原始随机森林模型、决策树模型、支持向量机模型和XGBoost模型进行实验对比,实验结果表明遗传算法参数优化后的随机森林消费行为预测模型的精准率和AUC值均高于其他四种模型。