地震作用下建筑结构的多时滞最优控制

对遭受地震激励的建筑结构主动控制中的多时滞问题进行研究.首先通过一种特殊的系统状态变量增广,将包含有多时滞项的系统状态方程转化为形式上不包含时滞的标准离散形式,然后采用离散最优控制方法设计时滞控制律.在所得出的时滞控制律中,除了包含有当前步的状态反馈,还包含有前若干步控制的线性组合.最后以三层建筑结构为例进行了仿真计算,验证了本文所给多时滞控制律的有效性.     

考虑驾驶员反应延时的自主车队最优巡航控制

针对传统的自主车队巡航控制方法只考虑通信延时而没有考虑驾驶员反应延时的问题,重新建立了自主车队巡航控制系统的数学模型,在建模过程中既考虑了通信延时,也考虑了驾驶员反应延时,得到了含有不同的状态延时和输入延时的非均匀自主车队巡航控制系统的状态空间数学模型;然后通过离散化,并通过定义增广状态向量,得到不含延时的离散时间状态空间模型,从而将含有延时的最优控制问题转变为不含延时的最优控制问题。在此基础上,应用最优控制理论,通过求解线性矩阵黎卡提方程,得到了最优巡航控制律。计算机仿真结果表明,本文提出的最优巡航控制律具有良好的控制性能。     

装有MR阻尼器的转向架动力系统的时滞输出反馈控制

建立了六自由度转向架模型,研究转向架动力系统的时滞输出反馈控制,通过部分可测输出量实现整个系统的振动控制.将系统的运动微分方程改写成状态空间模型,其控制输入中存在时滞.然后,利用一个线性项加积分项的变换将原时滞输入系统转化成无时滞的形式.在此基础上,应用输出反馈原理和合理的性能指标函数,以开关控制策略为依据设计了系统的时滞半主动控制律.最后,以一个具有典型参数的转向架模型为例来阐明所提出的控制策略的应用步骤.数值结果表明:所设计的时滞半主动控制策略是有效的.     

含有输入时滞的悬架系统的最优控制

伴随着主动控制环节的应用,悬架系统中不可避免会出现时滞因素。以含有时滞的2DOF主动悬架系统为研究对象,分别使用不考虑时滞的传统控制律和采用状态变换及系统离散化处理时滞后的控制律进行控制,并对控制系统的响应和稳定性特性进行对比。不考虑系统时滞时,直接采用传统的控制律进行控制,理论分析和数值仿真均表明:当时滞较小时,系统依然保持稳定,达到一定值时,可能引起系统响应定性特性改变,甚至失稳发散。采用状态变换的方法处理时滞后进行主动控制,能保证系统的稳定性,该控制律较好地反应了输入时滞对控制方程的影响。     

地震作用下主动减震结构的时滞离散最优控制

对地震作用下线性时滞结构的离散最优控制方法进行研究,按时滞量为采样周期的整数倍和非整数倍两种情况,将时滞连续控制系统离散为形式上不包含时滞的标准离散形式,采用连续时间形式的性能指标函数,按照离散最优控制方法进行控制设计。所得出的控制律表达式中,除了含有当前的状态反馈外,还包含有前若干步控制项的组合。最后结合一个三自由度建筑结构模型进行仿真计算,结果表明,算法中采用连续时间形式的性能指标函数优于离散形式的性能指标函数,此方法易于保证控制系统的性能和稳定性,而且可以看到,控制系统的时滞量并非越短越好。     

船舶航向非线性系统离散变结构控制

基于非线性模型研究船舶航向自动舵的离散变结构控制设计问题。通过状态反馈精确线性化方法设计了二次型最优滑模面，采用离散趋近律方法求得变结构控制律。研究结果表明，所设计的离散变结构控制器能够快速准确地跟踪设定航向，并对参数摄动和外界风浪干扰具有很强的鲁棒性。     

基于降维状态观测器的最优拥塞控制研究

在Internet拥塞控制系统建模的基础上,将降维状态观测引入到拥塞控制中,进而提出了一种基于主动队列管理(AQM)的新的最优拥塞控制方法。该方法利用降维状态观测器来获取无法直接获取的系统状态,从而实现状态反馈,克服传统的基于AQM的网络拥塞控制方法无法直接得到状态反馈控制律的缺陷,并能通过求解线性矩阵黎卡提方程,得到使性能指标达到最优的状态反馈控制律,实现Internet的最优拥塞控制。仿真结果表明,这种新的最优拥塞控制方法具有很好的跟踪性能。     

具有类反斜线回滞系统的自适应控制

考虑一类具有类反斜线回滞的不确定非线性系统自适应控制问题.利用神经网络提出了变结构自适应控制方法和近似自适应控制方法,变结构自适应控制方法能保证跟踪误差趋于零,近似自适应控制方法的控制律是光滑的,能保证跟踪误差最终小于任意给定的正数.文中举例说明了结果的有效性.     

柔性基础主动隔振系统的缩聚建模和时滞问题研究

以复杂柔性耦合主动隔振系统为对象,研究其动力学建模和时滞主动控制问题。考虑筏架和基础的弹性,建立浮筏系统的有限元模型,并基于超单元动力缩聚技术,把系统的有限元模型在物理空间中进行减缩。考虑作动器的时滞效应,建立系统的时滞主动控制模型,对系统的最大时滞量和控制器的时滞稳定性进行了数值研究。数值计算表明,主动控制中有必要考虑时滞因素以避免失稳,本文所提出的方法易于保证控制系统的性能和稳定性。     

永磁同步电动机位置伺服系统的自适应神经网络控制

针对需要考虑参数不确定和负载扰动的永磁同步电动机位置伺服系统,提出了一种新型的自适应神经网络控制方法。首先,利用神经网络建立永磁同步电动机的智能模型。其次,针对模型特点,在反步递推设计框架下,应用神经网络基函数的本质特征,并引入动态面控制技术克服控制设计中存在的“复杂性爆炸”问题,设计基于自适应神经网络动态面控制的位置跟踪算法。最后,仿真结果表明该控制方案是有效可行的,与反步递推控制方案相比,基于神经网络动态面控制的位置伺服系统的跟踪误差具有更快的收敛速度。通过设计新的神经网络自适应律,提出的自适应神经网络控制方法可以避免现有反步递推控制设计中存在的代数环问题。此外,提出的控制算法不仅能够克服不确定性因素对系统性能的影响,而且算法结构简单,易于实现。     

基于迭代学习控制的二阶延迟微分系统研究

针对由二阶延迟微分方程刻画的系统过程,提出应用其基本解阵延迟正、余弦矩阵函数表达的精确解设计迭代学习控制算法来对系统进行输出跟踪控制。给出能使得延迟系统的系统输出随迭代次数增加而收敛到给定期望输出的充分条件,并能由系统重复运行逐步迭代出能使得输出收敛的最优控制输入。数值仿真实验结果表明:设计的迭代算法能使系统输出随迭代次数增加而精确收敛到期望输出,验证了所提方法的有效性。     

基于部分可观察马尔可夫决策过程的受控无线网络系统动态资源分配

研究了受控无线网络的动态资源分配。针对传统无线通信传输模型的局限性随着无线通信系统架构的发展日益凸显的问题,提出了一种引入反馈控制策略的受控无线网络模型。该模型结合部分可观察马尔可夫决策过程(POMDP),将用户接收功率与数据传输误码率作为反馈观测对象,对通信小区内基站天线开启数与用户接入数进行动态资源最优匹配。仿真结果表明,这种方法能够有效提升系统传输能效性与可靠性,降低传输误码率,改善系统资源动态匹配控制性能。     

含控制时滞的海洋平台前馈反馈最优跟踪控制

通过引入状态变换,将含控制时滞的海洋平台系统转化为无时滞系统.然后,通过引入渐近稳定的期望系统,基于波浪力线性外系统近似模型,给出了海洋平台系统基于二次型性能指标泛函的前馈反馈最优跟踪控制器设计方法及其控制器的存在唯一性条件.控制器的前馈增益矩阵和反馈增益矩阵可分别经由求解代数Riccati方程和Sylvester方程得到.仿真算例表明了方法的有效性,且在减小平台的振动幅值和控制力方面,前馈反馈最优跟踪控制方法优于前馈反馈最优控制方法.     

Cross-layer design for block subchannel allocation and admission control in the IEEE 802.16 OFDMA networks

The flexibility of orthogonal frequency-division multiple access (OFDMA) technology necessitates a compromise between spectrum efficiency and quality of service (QoS) in IEEE 802.16 broadband wireless networks. This article proposes a complete solution with the nice feature of adaptive modulation and a coding scheme to provide both delay and loss rate guarantees for real-time services. The proposed method first determines the subframe boundary according to the current downlink and uplink backlogs. To comply with the IEEE 802.16 standard, the proposed method then groups contiguous subchannels and allocates them to proper connections based on the current loss rate and available modulation and coding schemes for each connection. By modeling the aggregated required subchannels as a Gaussian distribution, this study develops a simple admission control algorithm by checking if there are enough resources for a new connection. Simulation results show that the proposed solution can provide QoS guarantee with high spectrum efficiency.     

Adaptive opportunistic fair scheduling in power-controlled code division multiple access systems

The authors treat the multiuser scheduling problem for practical power-controlled code division multiple access (CDMA) systems under the opportunistic fair scheduling (OFS) framework. OFS is an important technique in wireless networks to achieve fair and efficient resource allocation. Power control is an effective resource management technique in CDMA systems. Given a certain user subset, the optimal power control scheme can be derived. Then the multiuser scheduling problem refers to the optimal user subset selection at each scheduling interval to maximise certain metric subject to some specific physical-layer constraints. The authors propose discrete stochastic approximation algorithms to adaptively select the user subset to maximise the instantaneous total throughput or a general utility. Both uplink and downlink scenarios are considered. They also consider the time-varying channels where the algorithm can track the time-varying optimal user subset. Simulation results to show the performance of the proposed algorithms in terms of the throughput/ utility maximisation, the fairness, the fast convergence and the tracking capability in time-varying environments are presented.     

Joint Spectrum Partition and Performance Analysis of Full-Duplex D2D Communications in Multi-Tier Wireless Networks

Full-duplex (FD) has been recognized as a promising technology for future 5G networks to improve the spectrum efficiency. However, the biggest practical impediments of realizing full-duplex communications are the presence of self-interference, especially in complex cellular networks. With the current development of self-interference cancellation techniques, full-duplex has been considered to be more suitable for device-to-device (D2D) and small cell communications which have small transmission range and low transmit power. In this paper, we consider the full-duplex D2D communications in multi-tier wireless networks and present an analytical model which jointly considers mode selection, resource allocation, and power control. Specifically, we consider a distance based mode selection scheme. The performance analysis of different D2D communications modes are performed based on stochastic geometry, and tractable analytical solutions are obtained. Then we investigate the optimal resource partitions between dedicated D2D mode and cellular mode. Numerical results validate the theoretical anlaysis and indicate that with appropriate proportions of users operated in different transmission modes and optimal partitioning of spectrum, the performance gain of FD-D2D communication can be achieved.     

Nimble and adaptive time-division multiple access control phase algorithm for cluster-based wireless sensor networks

Control phase plays a critical role in the performance of time-division multiple access (TDMA)-based networks. Within cluster-based wireless sensor networks, a nimble and adaptive control phase algorithm called NACPA to control the control phase of TDMA-based medium access control (MAC) in cluster-based sensor networks is proposed. This algorithm takes advantage of the wireless sensor hardware feature and presents a more accurate although simpler means to calculate the number of contention nodes in one round. On the basis of the analysis of the features of contention probability against the number of contention nodes, this algorithm can significantly reduce its computation complexity, rendering it practically feasible for resource-constrained sensor networks. Detailed analytical evaluation against two typical MAC algorithms (polling and carrier sense multiple access) is presented both in terms of packet transmission delay and average channel utilisation, the results of which, while also matching the simulation observation, have shown its effectiveness and efficiency.     

WiFi6 Dynamic Channel Optimization Method for Fault Tolerance in Power Communication Network

As the scale of power networks has expanded, the demand for multi-service transmission has gradually increased. The emergence of WiFi6 has improved the transmission efficiency and resource utilization of wireless networks. However, it still cannot cope with situations such as wireless access point (AP) failure. To solve this problem, this paper combines orthogonal frequency division multiple access (OFDMA) technology and dynamic channel optimization technology to design a fault-tolerant WiFi6 dynamic resource optimization method for achieving high quality wireless services in a wirelessly covered network even when an AP fails. First, under the premise of AP layout with strong coverage over the whole area, a faulty AP determination method based on beacon frames (BF) is designed. Then, the maximum signal-to-interference ratio (SINR) is used as the principle to select AP reconnection for the affected users. Finally, this paper designs a dynamic access selection model (DASM) for service frames of power Internet of Things (IoTs) and a scheduling access optimization model (SAO-MF) based on multi-frame transmission, which enables access optimization for differentiated services. For the above mechanisms, a heuristic resource allocation algorithm is proposed in SAO-MF. Simulation results show that the method can reduce the delay by 15% and improve the throughput by 55%, ensuring high-quality communication in power wireless networks.     

有源电力滤波器半矢量预测控制策略研究

针对经典模型预测电流控制算法电压矢量选择范围有限、电流跟踪精度不高的问题,提出改进型模型预测电压控制算法。利用滚动寻优得到较优电压矢量,再利用较优电压矢量和零矢量各作用T_s/2得到半幅值矢量,根据较优电压矢量和半幅值矢量的评价函数选择最优电压矢量。每个周期仅增加一个电压矢量,能有效减小预测电压矢量和实际电压矢量之间的误差,实现对谐波电流的准确跟踪,提高有源电力滤波器的补偿性能。仿真结果表明,所提出的改进型模型预测电压控制算法与经典模型预测电流控制算法相比,补偿电流对参考电流的跟踪更加准确,经补偿后并网电流中的谐波含量由4.86%下降到3.32%,且在稳态和动态情况下都能实现单位功率因数并网。     

时间异步无线传感器网络的目标跟踪动态成簇算法

为了解决时间异步无线传感器网络在目标跟踪时的节点协作管理和跟踪时间配准问题,提出了一种适用于时间异步条件下目标跟踪的动态成簇算法。该方法通过分析目标的无线信号强度和各节点至目标的距离来动态组建跟踪簇,然后依据目标及簇头的通信距离对簇头射频信号的覆盖区域进行功能划分,实现节点对目标的协作跟踪,同时以簇为跟踪时间的计算单元,通过簇内计时和簇间贯序传递的方法实现跟踪时间的配准。仿真实验表明,该算法进行目标跟踪时能有效均衡网络能耗,且具有较好的跟踪精度和系统鲁棒性。