Improved Hybrid Robust Control Method for the Electromechanical Actuator in Aircrafts

In the flight process of aircrafts, their electromechanical actuators（EMA） must have the ability of enduring uncertainties caused by factors such as load disturbance, the variation of work temperature and the EMA＇s nonlinearity. At present, in order to increase the EMA＇s robustness on the uncertainties, the H, control method has been applied in aircrafts. The major problems with standard H∞ control lie in the large overshoot of step response and the high orders of the controller. For the purpose of addressing the two problems, this paper investigates several kinds of robust control strategies of the EMA. A mathematical model of the EMA is first built, and then with MATLAB software a H∞ controller and an improved hybrid robust controller composed of a reduced order H∞controller and a lead compensator are designed. In order to make a scientific comparison of the control effects of H∞ controller, hybrid controller and classic proportion-integral-differential（PID） controller, a simulation research is made in respect of the open loop frequency response and the closed loop step response of the three controllers. For comparing the robustness of the three controllers, the load torque is entered as a disturbance and the disturbance response of error and control input are thus obtained. The experiments with the three controllers are also conducted. Through giving the EMA a command and a disturbance torque successively, the transient response and disturbing process of EMA are recorded. The simulation and experiment results show that with the help of the hybrid controller, the EMA not only guarantees good dynamic characteristics, but also has strong robustness of disturbance rejection. Therefore, the excogitated H∞ hybrid control method effectively solves the problem of large overshoot in dynamic response, and moderately meets the requirement of overcoming the uncertainties in the EMA of aircrafts.

Response surface methodology-based hybrid robust design optimization for complex product under mixed uncertainties

Minimizing the impact of the mixed uncertainties(i.e.,the aleatory uncertainty and the epistemic uncertainty) for a complex product of compliant mechanism(CPCM) quality improvement signifies a fascinating research topic to enhance the robustness.However, most of the existing works in the CPCM robust design optimization neglect the mixed uncertainties, which might result in an unstable design or even an infeasible design. To solve this issue, a response surface methodology-based hybrid robust design optimization(RSM-based HRDO) approach is proposed to improve the robustness of the quality characteristic for the CPCM via considering the mixed uncertainties in the robust design optimization. A bridge-type amplification mechanism is used to manifest the effectiveness of the proposed approach. The comparison results prove that the proposed approach can not only keep its superiority in the robustness, but also provide a robust scheme for optimizing the design parameters.

Compliant landing of a trotting quadruped robot based on hybrid motion/force robust control

A compliant landing strategy for a trotting quadruped robot on unknown rough terrains based on contact force control is presented. Firstly, in order to lower the disturbance caused by the landing impact force, a landing phase is added between the swing phase and the stance phase, where the desired contact force is set as a small positive constant. Secondly, the joint torque optimization of the stance legs is formulated as a quadratic programming(QP) problem subject to equality and inequality/bound constraints. And a primal-dual dynamical system solver based on linear variational inequalities(LVI) is applied to solve this QP problem. Furthermore, based on the optimization results, a hybrid motion/force robust controller is designed to realize the tracking of the contact force, while the constraints of the stance feet landing angles are fulfilled simultaneously. Finally, the experiments are performed to validate the proposed methods.

汽车四轮转向动力系统的Hybrid控制研究

应用混和控制(Hybrid Control)中的切换系统(Switched System)的方法,分别对汽车四轮转向系统的高速态与低速态两个子系统以及由高速态向低速态变化的切换系统进行了最优控制设计.仿真结果表明,Hybrid 控制实现了四轮转向系统(4WS)的低速灵活性与高速稳定性,具有良好的控制效果.

受限机器人系统的力与关节的 Hybrid 控制

使用矩阵代数理论研究了受限机器人系统的力与关节的ｈｙｂｒｉｄ控制问题，导出了一种新的力与关节的鲁棒自适应控制器设计方案．

基于混合两阶段鲁棒的多微网合作优化运行

针对微网独立运行时面临运行成本高,受可再生能源出力和多能负荷功率不确定性影响大等问题,提出一种基于混合两阶段鲁棒优化的多微网合作运行方法。首先,为了应对源荷双重不确定性挑战,在传统两阶段鲁棒优化基础上,提出一种基于多场景数据的最恶劣概率场景驱动的混合两阶段鲁棒优化方法,并采用可并行计算列与约束生成(column and constraint generation,C&CG)算法来提高求解效率。然后,在建立的多微网点对点分布式能源交易系统框架上,根据纳什谈判理论构造多微网合作成本最小化问题和收益分配问题,并提出一种耦合可并行计算C&CG的交替方向乘子法进行求解。最后,根据各微网不同的贡献率,设计一种基于点对点电能交易贡献度的非对称纳什谈判机制来分配各微网的合作收益。算例结果表明,所提方法能兼顾系统的鲁棒性、经济性和隐私性,并实现每个微网公平合理的收益分配。

Stabilizing Hybrid Stochastic Interval Systems by Feedback Controls

The problem of stabilizing a hybrid stochastic interval system is studied in this article. A hybrid interval system with suitable controls will become stable in the sense of mean-square exponential stability. State-feedback controls are designed based on the discrete-time state observations. Controls are put both in the drift and diffusion parts of the system. Criteria are derived in terms of linear matrix inequalities( LMI) to get the controllers. Also one example is given to illustrate our techniques.

考虑光伏随机性的交直流混合配电网鲁棒机会约束安全域模型

为实现高比例光伏接入下交直流混合配电网的安全评估,构建了交直流混合配电网的鲁棒机会约束安全域模型。首先,提出一种基于区间划分的自适应带宽核密度估计方法,以获取光伏预测误差概率分布,构建光伏出力机会约束不确定集合;其次,采用功率与节点电压幅值比值为状态变量,在已有交流线性化潮流模型的基础上推导一种交直流混合配电网线性化潮流模型;然后,提出交直流混合配电网鲁棒机会约束安全域的概念和模型,结合列与约束生成算法和径向迭代搜索算法生成可观测的鲁棒机会约束安全域空间。最后,算例分析验证了所提模型能够在鲁棒机会约束安全域上准确、直观的反映光伏出力的随机性,进而为交直流混合配电网的准确安全评估提供支撑。

Optimization of Critical Systems for Robustness in a Multistate World

Critical systems are typically complex systems that are required to perform reliably over a wide range of scenarios, or multistate world. Seldom does a single system exist that performs best for all plausible scenarios. A robust solution, one that performs relatively well over a wide range of scenarios, is often the preferred choice for reduced risk at an acceptable cost. The alternative with the maximum expected utility may possess vulnerabilities that could be exploited. The best strategy is likely to be a hybrid solution. The von Neumann-Morgenstern Expected Utility Theory (EUT) would never select such a solution because, given its linear functional form, the expected utility of a hybrid solution cannot be greater than that of every constituent alternative. The continuity axiom and the independence axiom are assessed to be unrealistic for the problem of interest. Several well-known decision models are analyzed and demonstrated to be potentially misleading. The linear disappointment model modifies EUT by adding a term proportional to downside risk;however, it does not provide a mathematical basis for determining preferred hybrid solutions. The paper proposes a portfolio allocation model with stochastic optimization as a flexible and transparent method for defining choice problems and determining hybrid solutions for critical systems with desirable properties such as diversification and robustness.

考虑条件风险价值的交直流系统两阶段分布鲁棒低碳经济优化调度

考虑到海上风电出力的随机性以及日益突出的生态环境问题,以含柔性直流输电技术(voltagesource converter high voltage direct current,VSC-HVDC)的交直流系统为研究对象,提出了考虑条件风险价值(conditional valueatrisk,CVaR)的两阶段分布鲁棒低碳经济优化模型,构建了基于Kullback-Leibler(KL)散度的概率分布模糊集,同时利用条件风险价值量化了极端场景下的尾部风险,使得模型能够同时考虑概率分布不确定性以及处于最坏概率分布中极端场景下的尾部损失;此外,将阶梯型碳交易机制并入所提分布鲁棒模型中,通过合理利用柔性资源和储能装置,增强系统运行的灵活性,在兼顾运行风险的前提下,降低碳排放量的目标。再者,为了提高计算效率,在列和约束生成算法(column-and-constraint generation method,C&CG)和Multi-cut Benders分解算法的基础上提出了双循环分解算法。最后,在基于改进的IEEE RTS 79测试系统中验证了所提模型及算法的有效性。

数控机床磁悬浮直线同步电动机混合H_(2)/H_(∞)鲁棒控制器设计

针对数控机床磁悬浮直线同步电动机控制系统,提出混合H_(2)/H_(∞)鲁棒控制。首先,考虑不确定H_(∞)扰动以及端部效应等因素建立数控机床磁悬浮直线同步电动机的数学模型。其次,将鲁棒H_(∞)控制与线性矩阵不等式(linear matrix inequality,LMI)相结合,设计一种基于LMI的鲁棒H_(2)/H_(∞)控制器。再次,为提高系统的动态性能,设计基于LMI的混合鲁棒控制器。最后,仿真H_(2)/H_(∞)结果证明在保证系统鲁棒稳定的前提下,混合鲁棒控制可有效提高系统的收敛速度和响应灵敏度。

基于鲁棒优化的冷热电联供型微网混合储能经济配置

为解决源荷双侧不确定性对冷热电联供CCHP(combined cooling,heating and power)型微网经济运行带来的电量实时平衡问题,提出一种基于鲁棒理论的CCHP微网电、热、冷混合储能容量配置模型。基于鲁棒理论,建立源荷双侧不确定性变量合集。考虑储能设备日折算成本,以微网运行成本最低为目标,采用自适应差分进化算法对模型进行求解,得到不同预测精度与置信概率下的微网储能最优容量合集。通过设置评价指标,选取最合适的储能配置方案,对微网配置储能前后的调度情况作对比。结果表明,基于鲁棒理论配置的电、热、冷这3类储能可有效提升微网在源荷双侧不确定下的电力电量实时平衡能力与运行经济性。

基于混合稀疏ICCP的联合抗差重力匹配定位方法

针对经典最近等值线迭代(ICCP)算法因重力异常测量误差导致匹配精度下降甚至失效的问题,提出联合抗差匹配算法以提高匹配精度及可靠性。首先,分析了匹配点集间的匹配残差在高斯噪声影响下呈非高斯分布,为抑制其影响,采用l_(p)范数代替l_(2)范数计算匹配残差,并利用匹配残差重调野值点以获得有效的匹配区域。在此基础上,提出混合稀疏ICCP算法,并利用其进行粗匹配,然后将粗匹配后的位置作为惯导系统(INS)指示位置,再使用经典ICCP算法进行精匹配,获得更高的定位精度。仿真结果表明,考虑重力异常测量误差的情况下,重力联合抗差匹配算法的误差最大值小于1 n mile,导航精度较传统ICCP算法提升60%以上,提升了算法的鲁棒性和匹配精度。

考虑柔性资源多维价值标签的交直流配电网灵活调度

可再生能源高渗透率使得交直流配电网面临严重的随机性和波动性,充分挖掘柔性资源调控潜力可以有效地降低可再生能源带来的网络运行风险。针对当前交直流配电网优化调度主要考虑电压源型换流器(VSC)的调控能力,对VSC与柔性资源协同研究不足的问题,提出一种考虑柔性资源多维价值标签的交直流配电网灵活调度方法。首先,考虑柔性资源调控特性差异,构建了包含响应时段、调节能力、调节成本及响应意愿的多维价值标签评估体系,准确全面地评估柔性资源聚合调控潜力范围;其次,以运行成本最小为目标函数,柔性资源多维价值标签为约束,建立交直流配电网两阶段鲁棒日前优化调度模型,并采用嵌套列和约束生成算法(C&CG)及强对偶理论进行求解;最后,通过改进的IEEE 33节点交直流配电网仿真结果表明,所提方法能够充分发挥柔性资源的调控潜力和协同能力,同时可有效提高模型求解效率和求解精度。

基于多类型换流设备的受端电网耦合鲁棒阻尼控制策略

针对混合级联直流馈入与柔性输电设备密集接入的受端电网,为增强其特定振荡模式的阻尼,利用不同换流设备控制回路间的相互作用,提出了一种基于多输入多输出系统模型的耦合鲁棒阻尼控制器设计方法。根据主模比指标选取振荡抑制效果最佳的反馈信号作为控制器输入信号;利用总体最小二乘-旋转不变技术识别系统的振荡模式并辨识系统降阶模型;采用混合H_(2)/H_(∞)方法设计耦合鲁棒控制阻尼器。控制器采用平衡截断法进行降阶,兼具鲁棒性能与实际工程应用。混合级联直流与受端江苏电网互联系统的时域仿真结果表明,相比于传统超前-滞后控制器,耦合鲁棒阻尼控制器在多种扰动和故障下均能有效抑制低频振荡,使系统快速恢复稳定运行。

基于数据驱动多面体集合的交直流混合配电网鲁棒调度方法

针对现有配电网鲁棒调度方法缺乏对不确定参数相关性问题的考虑,提出了一种基于数据驱动多面体集合的交直流混合配电网鲁棒调度方法。首先,构建分布式光伏出力的传统多面体集合,利用历史数据驱动形成了相关性包络图,通过弯曲多面体集合边界,建立了相关性多面体集合模型。然后,在此基础上,针对相关性多面体集合存在鲁棒性差和保守性大的问题,建立了数据驱动的多面体集合模型。进一步,建立了基于数据驱动多面体集合的交直流混合配电网鲁棒调度模型,并采用列与约束生成(column and constraint generation,CCG)算法对鲁棒调度模型进行求解。最后,改进的IEEE33节点系统仿真结果表明,基于数据驱动多面体集合的交直流混合配电网鲁棒调度方法可以减少优化结果的保守性,提高其鲁棒性,证明了所提出方法的有效性。

鲁棒性优化的混合四探针圆柱度测量方法

四点法在现场测量方面具有优越性,被广泛应用于圆柱度轴系轮廓重构中。为了进一步提高四点法的测量精度,构建了一种混合四点法测量模型。在第一个测量位置布置不同的探头角度并进行多次测量,为每个谐波系数提供多个候选解;针对单个谐波系数,根据传递矩阵从候选解集合中选取最优估计;将探针支架移动到第二个测量位置,重复上述步骤,直到测量全部截面;利用最优谐波系数得到整体圆柱度误差。实验证明,混合四点法比常规方法对误差源的测量具有更强的鲁棒性。

多输入多输出微振动系统的混合鲁棒自适应控制

Q参数化方法在结构振动自适应控制领域的应用中体现出明显优势.本文针对多输入多输出(MIMO)结构振动主动控制系统,利用Q参数化方法的优势,基于无限冲激响应(IIR)滤波器,提出了一种结合前馈控制与反馈控制的MIMO混合鲁棒自适应控制方法.同时,给出前馈,反馈MIMO鲁棒自适应控制方法的详细推导过程,给出混合MIMO鲁棒自适应控制方法的推导和稳定性,收敛性分析.在此基础上,通过构建三自由度微振动主动振动控制实验系统,针对单频窄带和双频窄带扰动展开了对比实验分析,相关的实验结果验证了本文所提出MIMO混合鲁棒自适应控制方法的可行性和有效性.

基于多特征检测与自适应权重调整的鲁棒联邦学习算法

联邦学习作为一种保护隐私的分布式机器学习范式,允许多个客户端在不泄露原始训练数据的情况下协同训练全局模型。然而,由于无法直接访问客户端本地训练数据和无法监控本地训练过程,联邦学习面临各种拜占庭攻击的威胁,如数据中毒和模型篡改攻击。这些攻击旨在扰乱联邦学习模型训练过程,降低模型性能。针对此问题,尽管已有许多研究提出了不同的聚合算法,但这些方法主要聚焦于单一拜占庭攻击场景,而忽略了实际环境中可能出现的混合拜占庭攻击所带来的威胁。为应对这一难题,受净水器的原理启发,提出了一种基于多特征检测与自适应权重调整的新型拜占庭鲁棒聚合算法FL-Sieve,旨在通过多层次的筛查过滤恶意客户端。首先,算法通过角幅相似度和模型边界测度评估客户端间的特征相似性,生成相似度矩阵并计算相似性分数;接着,利用聚类算法将相似的节点归入同一簇,以确保相似的节点能够被正确分类;随后,根据预定义规则筛选潜在良性客户端;最后,根据每个客户端的信任度智能地分配权重,进一步增强防御效果和系统鲁棒性。为了验证FL-Sieve的性能,实验利用了MNIST,Fashion-MNIST和CIFAR-10这3种数据集,考虑了Non-IID数据分布情景和混合拜占庭攻击场景。混合拜占庭客户端的数量从20%递增到49%,以模拟大规模混合拜占庭客户端攻击的场景。同时也对FL-Sieve在IID和Non-IID数据分布以及单攻击场景下的性能进行了测试。实验结果表明,FL-Sieve能够有效抵御不同场景下的拜占庭攻击,即使在高达49%的混合拜占庭客户端攻击下,FL-Sieve依然能够维持较高的主任务准确率。相比之下,几种现有的经典算法存在不同程度的失效,凸显出FL-Sieve的优势。

电-热-氢综合能源系统鲁棒区间优化调度

储能技术与风电相结合实现电能的时空平移是解决系统运行稳定性问题的有效手段。氢储能具有储存容量大、可实现电热联产联供的优点,具有很大的发展潜能。然而由于风电存在不确定性,氢储能系统在频繁切换工作模式时面临着不确定的热能需求。因此,文中综合考虑氢储能在间歇模式下的热能需求,首先,介绍了氢储能系统接入的电-热综合能源系统基本结构,将风电场与氢储能相结合构成风-氢混合系统;然后,提出考虑风-氢混合系统热平衡需求不确定性的电-热综合能源系统鲁棒区间优化调度模型;最后,基于对偶理论,对所提出的模型转化求解,通过算例对比分析各类情况优化结果,验证了氢储能在促进风电消纳、提高系统能源综合利用率方面的有效性,并证明了考虑电解槽和燃料电池工作温度能提高系统的工作效率并提高风电场并网功率。