动态自适应的HTTP流码率渐进切换算法

针对在动态网络环境和有限缓存容量限制下用户观看视频体验质量低的问题，提出一种综合考虑带宽和缓存因素的动态自适应的HTTP流码率渐进切换（DASBS）算法。首先，利用滑动窗口分析最近下载分片得到带宽初步估值；然后，依据实时带宽波动程度和缓存状态设置双矫正因子进一步平滑带宽估值；最后，设置缓存阈值使其与当前码率建立相关关系，并利用带宽估值和缓存动态阈值共同控制码率切换。使用libdash平台验证算法性能，DASBS在切换平滑性上优于VQCQ（Video Quality Control for QoE）算法，视频播放平均码率更高，有效提高了带宽利用率；平均码率稍低于EABS（Evolution of Adaptive Bitrate Switching）算法时，切换次数得到大幅下降，整体切换稳定性表现更优。实验结果表明，所提算法在动态网络环境中具有带宽高利用、切换平滑和切换稳定的良好表现，能够有效改善用户体验。     

应用模型预测控制的混合动力汽车模式切换动态协调控制

利用传统协调控制策略或模型预测控制(MPC)方法能够解决离合器模式切换的平顺性,但其改善效果不显著,且缺乏深入的细化研究.因此,为了改进混合动力汽车有离合器结合的模式切换过程中的平顺性,本文基于MPC制定有离合器模式切换过程的动态协调控制策略.在对混合动力系统有离合器模式切换模型进行简化的基础上,开展MPC在模式切换动态协调控制过程的原理描述,以减小有离合器模式间切换的冲击度进行基于MPC动态协调控制策略设计,并对不同权重下的冲击度进行了详细的对比.通过实验验证,其结果表明采用MPC的模式切换协调控制最大冲击度从26.3 m/s^3下降至9.26 m/s^3,降低了64.8%,明显的抑制了模式切换过程中的冲击度,有效的改善了模式切换的平顺性.     

基于多模型切换的过热汽温智能控制

针对火电厂过热汽温控制系统具有大迟延、时变等特点,常规控制难以取得满意的控制效果,提出了基于多模型切换的过热汽温智能控制方法。仿真结果表明,过热汽温控制的动态特性明显得到改善。     

多层次多模型预测控制算法的模型切换方法研究

针对多层次多模型(Multi-hierarchical multi-model, MHM)预测控制系统的模型切换问题, 在分析各通道非线性程度对模型层次切换以及层次 间模型切换过程对系统动态特性的影响的基础上, 提出了一种新的模型切换方法. 并将此方法应用到多输入多输出pH 中和过程, 仿真结果表明, 该方法有效地改善了系统工况大范围跳变时的动态性能.     

一类含阶跃干扰的切换系统最优控制

研究了一类含阶跃干扰的切换系统的二次最优控制问题,其中切换系统的切换序列、切换次数固定、采用动态规划方法,利用多级决策和改进的遗传算法来得到最优切换时刻和最优控制输入．最后通过一个数值例子说明了本文方法的有效性．     

一种新的H.264视频场景切换检测算法

H.264/AVC QCIF视频场景切换检测是视频应用中一个极具挑战性的研究课题,只利用宏块信息很难得到满意的检测效果,为此提出了一种采用动态阈值和AC相似度的H.264/AVC视频场景切换检测算法,考虑编码预测模式和DCT系数等信息,提出基于编码比特数的动态阈值和基于AC能量的AC图像相似性两个判决准则,据此进行视频场景切换检测。实验结果表明,在高速运动及场景切换频繁的视频上场景切换检测率得到提高,性能也优于现有的算法。     

具有逻辑切换的反馈控制系统的设计

为使线性系统的动态性能得到充分的改善,需实现非线性控制,如时间最短的 bang-bang 控制。这类最优控制,实质上是一种逻辑判别和切换的控制。然而这种按某种指标严格最优的控制所用的逻辑判别函数常常十分复杂,工程上不易实现,并且一般常对系     

非线性系统的反演自适应动态滑模控制

为削弱非线性系统中由滑模控制引起的抖振现象,提出自适应动态滑模控制方案.动态滑模方法是通过设计新的切换函数或将常规滑模变结构控制中的切换函数s通过微分环节构成新的切换函数,该切换函数与系统控制输入的一阶或高阶导数有关,可将不连续项转移到控制的一阶或高阶导数中去,得到在时间上本质连续的动态滑模控制律.该方案利用自适应技术和反演法,设计动态滑模控制器,有效地削弱了系统的抖振.最后仿真结果证明了该方案是正确的.     

基于递归神经网络模型预测控制的模型平稳切换

不同生产条件下的控制系统可视多模型控制系统，但多模型控制在模型切换时会引起系统的瞬态响应。采用递归神经网络建立系统的多个模型，基于模型预测控制进行控制模型切换，克服了模型切换时引起的系统瞬态响应，实现系统的平稳切换。并通过仿真表明这种切换策略明显改善了模型切换过程的动态性能。     

基于非线性切换函数的动平衡系统控制研究

将具有非线性切换函数的滑模变结构控制方法引入到砂轮动平衡控制领域。提出了一种改善直流电动机速度控制系统动态性能的新方法,该方法基于变结构控制理论,通过引入非线性切换函数,解决了快速的动态响应和禁止超调间的矛盾要求,有效地缩短了调节时间。     

Dynamic switching based fuzzy control strategy for a class of distributed parameter system

In this work, a dynamic switching based fuzzy controller combined with spectral method is proposed to control a class of nonlinear distributed parameter systems (DPSs). Spectral method can transform infinite-dimensional DPS into finite ordinary differential equations (ODEs). A dynamic switching based fuzzy controller is constructed to track reference values for the multi-inputs multi-outputs (MIMO) ODEs. Only a traditional fuzzy logic system (FLS) and a rule base are used in the controller, and membership functions (MFs) for different ODEs are adjusted by scaling factors. Analytical models of the dynamic switching based fuzzy controller are deduced to design the scaling factors and analyze stability of the control system. In order to obtain a good control performance, particle swarm optimization (PSO) is adopted to design the scaling factors. Moreover, stability of fuzzy control system is analyzed by using the analytical models, definition of the stability and Lyapunov stability theory. Finally, a nonlinear rod catalytic reaction process is used as an illustrated example for demonstration. The simulation results show that performance of proposed dynamic switching based fuzzy control strategy is better than a multi-variable fuzzy logic controller.     

A powerful output‐feedback controller for uncertain nonlinear systems

System nonlinearities, immeasurableness, and uncertainties (especially their coupling/coexistence) have constantly challenged the control design, which requires the controller to be powerful enough to counteract the resulting negative effects. In this paper, a global adaptive output‐feedback controller is designed for uncertain nonlinear systems. The proposed controller is of switching type, in which the design parameters are online adjusted on the basis of a switching logic in a recursive manner. This makes the controller powerful enough to compensate the system unknowns and dominate the system nonlinearities and therefore be applicable to a rather wide range of systems. Remarkably, our strategy allows the coexistence of an unknown control direction and unmeasured state–dependent growth but which are substantially excluded in the related literature. An example of the single‐link robot arm system is provided to illustrate the effectiveness of the proposed controller.     

Neurovision-based logic control of an experimental manufacturing plant using neural net le-net5 and automation Petri nets

In this paper, Petri nets and neural networks are used together in the development of an intelligent logic controller for an experimental manufacturing plant to provide the flexibility and intelligence required from this type of dynamic systems. In the experimental setup, among deformed and good parts to be processed, there are four different part types to be recognised and selected. To distinguish the correct part types, a convolutional neural net le-net5 based on-line image recognition system is established. Then, the necessary information to be used within the logic control system is produced by this on-line image recognition system. Using the information about the correct part types and Automation Petri nets, a logic control system is designed. To convert the resulting Automation Petri net model of the controller into the related ladder logic diagram (LLD), the token passing logic (TPL) method is used. Finally, the implementation of the control logic as an LDD for the real time control of the manufacturing system is accomplished by using a commercial programmable logic controller (PLC).     

Analysis and control of switched linear systems via modified Lyapunov–Metzler inequalities

This paper addresses analysis and switching control problems of continuous/discrete‐time switched linear systems. A particular class of matrix inequalities, the so‐called Lyapunov–Metzler inequalities, will be modified to provide conditions for stability analysis and output feedback control synthesis under a relaxed min‐switching logic. The switching rule combined with switching output feedback controllers will be designed to stabilize the switched system and satisfy a prespecified gain performance. The proposed analysis and switching control approach could refrain frequent switches commonly observed in min‐switching based designs. The effectiveness of the proposed approach will be illustrated through numerical examples. Copyright © 2012 John Wiley & Sons, Ltd.     

Finite-time quantised feedback asynchronously switched control of sampled-data switched linear systems

This paper studies the problem of stabilising a sampled-data switched linear system by quantised feedback asynchronously switched controllers. The idea of a quantised feedback asynchronously switched control strategy originates in earlier work reflecting actual system characteristic of switching and quantising, respectively. A quantised scheme is designed depending on switching time using dynamic quantiser. When sampling time, system switching time and controller switching time are all not uniform, the proposed switching controllers guarantee the system to be finite-time stable by a piecewise Lyapunov function and the average dwell-time method. Simulation examples are provided to show the effectiveness of the developed results.     

Adaptive logic‐based switching fault‐tolerant controller design for nonlinear uncertain systems

This paper deals with the problem of fault‐tolerant control (FTC) for a class of nonlinear uncertain systems against actuator faults using adaptive logic‐based switching control method. The uncertainties under consideration are assumed to be dominated by a bounding system which is linear in growth in the unmeasurable states but can be a continuous function of the system output, with unknown growth rates. Several types of common actuator faults, e.g., bias, loss‐of‐effectiveness, stuck and hard‐over faults are integrated by a unified fault model. By utilizing a novel adaptive logic‐based switching control scheme, the actuator faults can be detected and automatically accommodated by switching from the stuck actuator to the healthy or even partly losing‐effectiveness one with bias, in the presence of large parametric uncertainty. In particular, two switching logics for updating the gain in the output feedback controllers are designed to ensure the global stability of the nominal (fault‐free) system and the boundedness of all closed‐loop signals of the faulty system, respectively. Two simulation examples of an aircraft wing model and a single‐link flexible‐joint robot are given to show the effectiveness of the proposed FTC controller. Copyright © 2010 John Wiley & Sons, Ltd.     

FUZZY SCHEDULING OF REGIONAL QFT CONTROLLERS

A novel optimization-based controller synthesis method is developed for nonlinear dynamic systems with structured parametric uncertainty. Fuzzy logic is used to smoothly schedule independently designed regional robust controllers over the plant's operational envelope. These linear controllers are synthesized using established conventional control design techniques, e.g., quantitative feedback theory. The resulting full envelope nonlinear dynamic controller handles complex dynamic systems which cannot otherwise be addressed by simple fuzzy logic control (FLC). An analytical representation of the membership functions of FLC allows the optimization to chose the location parameters of the regional controllers. The scheduled controller's valid region of operation is maximized, thus efficiently achieving full envelope operation, while guaranteeing pre-specified tracking performance. © 1997 by John Wiley & Sons, Ltd. This paper was produced under the auspices of the US Government and it is therefore not subject to copyright in the US.     

Reaching condition for variable-structure output feedback controller using a search technique

The aim of this paper is to establish the reaching condition for a variable-structure output feedback controller based on Genetic Algorithms (GA). The design of the variable-structure controller using output feedback provides a technique to compute matrix parameters and guarantees the reaching conditions for a general class of linear systems. A combination of both a modified control law and a simple search technique based on the GA approach is proposed to obtain a good dynamic response. The proposed method is computationally simple and tractable, and guarantees a sliding motion along the switching surface. The efficacy of the theoretical results is illustrated by considering a linearized model of an aircraft control problem.     

用遗传算法优化设计模糊控制器的软件研制

文章叙述了利用遗传算法优化设计模糊控制器的原理,介绍了相应软件的组成和基本功能。该软件不仅能优化设计模糊控制器,而且能根据不同被控对象模型进行仿真,从而评价模糊控制器的鲁棒性及动态性能。     

具有逻辑切换的反馈控制系统的设计

本文讨论如何应用李亚普诺夫函数法设计可以改善动态性能的逻辑切换反馈控制.所提 出的方法既适用于线性定常系统,也适用于双线性系统.