基于模糊逻辑的一类复杂系统全息控制设计

针对一类结构上具有相似性的非线性不确定复杂系统,利用模糊逻辑系统可以充分逼近连续函数的性质,研究这类复杂系统的鲁棒镇定问题,设计出了系统的全息鲁棒控制器和模糊逻辑系统参数估计的自适应律。为了简化控制器结构,在构造模糊逻辑系统时对被控系统的不确定性进行了归一化处理。在较弱的假设条件下,证明了这种控制器使被控系统的状态及参数估计误差一致终极有界,同时给出了误差的严密的数学分析。仿真实例表明所提出的方法是有效的。     

ADAPTIVE SYSTEMS THEORY： SOME BASIC CONCEPTS, METHODS AND RESULTS

The adaptive systems theory to be presented in this paper consists of two closely related parts: adaptive estimation (or filtering, prediction) and adaptive control of dynamical systems. Both adaptive estimation and control are nonlinear mappings of the on-line observed signals of dynamical systems, where the main features are the uncertain-ties in both the system‘s structure and external disturbances, and the non-stationarity and dependency of the system signals. Thus, a key difficulty in establishing a mathematical theory of adaptive systems lies in how to deal with complicated nonlinear stochastic dynamical systems which describe the adaptation processes. In this paper, we will illustrate some of the basic concepts, methods and results through some simple examples. The following fundamental questions will be discussed: How much information is needed for estimation? How to deal with uncertainty by adaptation? How to analyze an adaptive system? What are the convergence or tracking performances of adaptation? How to find the proper rate of adaptation in some sense? We will also explore the following more fundamental questions: How much uncertainty can be dealt with by adaptation ? What are the limitations of adaptation ? How does the performance of adaptation depend on the prior information ? We will partially answer these questions by finding some “critical values“ and establishing some “Impossibility Theorems“ for the capability of adaptation, for several basic classes of nonlinear dynamical control systems with either parametric or nonparametric uncertainties.     

T-S模糊系统的一种新型PDC鲁棒模糊控制器设计

针对一类模有界的参数不确定Takagi-Sugeno(T-S)模糊系统,在分析模糊系统前提规则结构的基础上,设计了一种新的并行分配补偿(PDC)控制器,研究了其鲁棒控制问题。基于分段Lyapunov稳定性理论,导出了线性矩阵不等式(LMI)形式的鲁棒控制器设计方法。该方法充分利用了模糊系统隶属度函数的结构信息,降低了采用线性矩阵不等式方法求解的难度。仿真实验证明,通过该方法设计的模糊控制系统,具有良好的鲁棒性能,控制效果良好。     

网络控制系统结构下的非线性系统建模与仿真

针对非线性系统往往具有不确定性,结构复杂、建模困难和不适于网络条件下仿真研究的问题,提出了一种网络控制系统结构下非线性系统建模与仿真的方法.在对弹簧连接的双倒立摆耦合非线性系统模型及其通信网络进行Matlab/Simulink模块化建模的基础上,利用鲁棒控制器将对象模型的不确定性和网络时延的不确定性进行了综合处理.仿真结果表明,该方法不仅降低了非线性系统建模的复杂性,而且为研究网络控制系统结构下非线性系统的动态特性提供了条件.     

ENTROPY,INFORMATION,NOISE—STUDIES ON SYSTEM EVOLUTION

Universe, ecosystem, social system, etc. are evolving systems. The evolving processes of thesesystems have gradual small changes and rapid drastic changes with uncertainties under the constraintsof environment. Systems, as a whole, are evolving toward complexity, diversity and variety withfluctuations and jumps. New order emerges from "mutations". The evolution is bothchance-dependent and path-dependent. In this paper three basics: entropy, information and noise areemphasized with regard to system evolution which is a field that can give people wisdom to solvesystem problems with domain knowledge.     

不确定非线性系统变结构模糊自适应鲁棒控制

考虑一类不确定非线性系统的鲁棒控制器设计问题,在假设系统不确定性函数结构未知的情况下,利用模糊系统对不确定性函数进行逼近,将获得的模糊系统函数作为系统不确定性界函数。在此基础上,提出了一种变结构模糊自适应鲁棒控制算法,该算法在确保系统的滑动模态超平面为渐近可达的前提下,在线对系统模型的控制增益参数和不确定性函数的界参数进行估计。最后以船舶减摇鳍非线性控制系统为例,进行了变结构鲁棒自适应模糊控制器的设计。仿真研究表明,所提出的算法是有效的。     

不确定非线性系统的鲁棒自适应跟踪简化算法

传统的Backstepping自适应控制方法需要对虚拟控制律进行求导,从而导致“计算复杂性膨胀”。动态平面控制技术能够克服这一缺陷。将这一技术扩展到一类具有参数严格反馈形式的不确定非线性系统输出跟踪,这类系统同时包含线性参数和未知非线性函数两种不确定性。所设计的控制算法比现有算法大大简化,解决了“计算复杂性膨胀”问题;运用Lyapunov理论证明了闭环系统一致最终有界,仿真结果表明了算法的有效性。     

具有非匹配不确定性相似组合系统的分散鲁棒控制

针对一类具有非匹配不确定性的相似组合系统 ,基于块控原理提出了一种变结构控制设计方法。不确定项存在于各子系统的互联项中 ,可以是非线性的或时变的 ,不满足匹配条件 ,但有界 ;利用反演设计方法来处理系统中的非匹配不确定性 ,再用变结构控制方法来改善系统的性能 ;然后 ,利用Lyapunov稳定性定理证明了闭环系统的信号为最终一致有界且系统的状态收敛于滑模超平面的邻域。最后 ,用一个仿真实例证明了所提出的方法的正确性和有效性。     

基于不确定理论的退化数据分析方法

作为可靠性领域传统的数学工具,概率论难以解决现代可靠性工程面临的难题。本文以不确定理论在退化数据分析中的应用为切入点,阐述了不确定理论的基本公理、运算法则与不确定统计方法,给出了基于确信可靠性理论的可靠性建模思路,提出了不确定失效阈值情形下的退化数据分析与可靠性建模方法。利用时变不确定正态分布建立产品的退化方程,根据专家知识建立失效阈值的不确定分布进而构建裕量方程,最终根据度量方程推导出产品可靠性模型。使用不确定统计中的极大似然估计法与假设检验法解决参数估计与模型验证问题。案例分析说明如果不考虑失效阈值的不确定性,会造成可靠性评估结果较大偏差。研究表明不确定理论适合处理退化数据分析中的不确定性难题,具有广阔的应用前景。     

不确定广义系统的鲁棒H2控制

利用线性矩阵不等式 (LMI)方法 ,研究范数有界的不确定广义系统的鲁棒H2 性能分析与控制问题。对该系统所有容许的不确定参数 ,提出了满足鲁棒H2 次优性能的一个线性矩阵不等式 (LMI)的充分条件。进而设计了一个状态反馈控制律 ,保证了闭环系统是容许的且满足鲁棒H2 次优性能 ,即闭环传递函数的H2 范数小于一个给定的正数。利用Matlab控制工具箱 ,给出了该控制律的LMI实用设计方法。最后的数值例子进一步说明了所取得的主要结果     

Simplified iterative algorithm for OFDM phase noise mitigation

OFDM has been widely adopted in several communication systems. However, OFDM systems are very sensitive to the phase noise, which causes the CPE (common phase error) and ICI (inter-carrier interference), and thus degrades the system performance significantly. Based on the IEEE 802.11a standard, a simplified iterative phase noise mitigation algorithm is proposed. The proposed algorithm has very low complexity, and requires no additional pilot information. The simulation result shows that good BER performance can be achieved through several few times of iteration.     

基于L1自适应律的尾坐式飞行器悬停位置控制

针对一款飞翼布局的尾坐式垂直起降飞行器,研究了悬停阶段的位置控制问题。小型飞行器质量、惯量小,具有纵向横向耦合严重、难以精确建模以及对扰动敏感等特点。首先,建立包含不确定性的非线性动力学模型,通过整合将其改写为一个不含不确定的标称系统和一个非线性非匹配的不确定性两部分,使用级联形式的非线性动态逆架构进行标称系统控制器的设计,显式的期望动力学表达使其更易与L1自适应控制器结合。接着使用L1自适应控制器对非线性非匹配的不确定性进行补偿,以便提高系统鲁棒性,改善瞬态性能。为减小运算负荷,便于工程实现,使用计算更轻量的比例型自适应律进行L1自适应控制器设计。数值仿真验证了所设计控制器具有良好的位置和高度指令跟踪能力。     

Complexity and intransitivity in technological development

This paper investigates the existence of a fundamental link between two disciplines that emerged during last few decades： complexity science and advanced engineering. During this time many industries, especially those related to the high-tech end of technological development, have faced the problem of increasing complexity of design, production and operation. Industrial projects have grown to become multidisciplinary, tightly interconnected, costly and difficult to control and predict. Two trends can be identified in this respect： one is the consistent effort of systems engineering in reducing the uncertainties of complex industrial operations and the other is the effort undertaken in complexity studies to account for uncertainties present in the real world.
In this work, we provide a brief overview of recent developments in advanced engineering and give a consistent interpretation of technological evolution from the perspective of complexity science in general and complex competitive systems （CCS） in particular. CCS is a general framework that was recently developed for analysis of complex systems involving competition. Transitivity of the decision-making process and the cyclic nature of technological progress are considered. Correctness of intransitive decisions is inherently relativistic： the same decisions can be seen as correct or incorrect when considered from different perspectives. When treated simplistically, intransitivity may seem to be illogical but, nevertheless, it is common in nature and needs to be studied. CCS provides a formalised scientific framework for analysis of intransitivity and establishes the existence of an important connection linking complexity and uncertainty with intransitivity. Implications of intransitivity for engineering decision-making and strategic planning are considered in the context of CCS. A working example of intransitivity in competition between major car mantifacturers is presented.     

一类不确定混合线性时滞系统鲁棒控制问题研究

讨论了一类不确定混合线性时滞系统在其Markov跳跃参数所处模态非精确可测得情况下的鲁棒控制问题。给出了非匹配条件下系统不确定部分范数上界已知时,使系统呈均方意义下指数稳定的保代价控制充分条件。并根据混合系统模式下的LaSalle稳定性定理,对匹配条件下系统不确定部分的未知范数上界给出了一种参数自适应估计方法,设计了相应的鲁棒自适应控制律以实现混合线性时滞系统以概率1渐近稳定。鲁棒自适应控制律的设计仅依赖于跳跃参数的非精确测量值。     

残留频偏下LDPC-MSK系统码辅助载波同步算法

针对低信噪比条件下低密度奇偶校验码〖CD*2〗最小频移键控系统载波同步实现困难的问题,提出了一种新的码辅助载波同步算法。该算法将译码软信息分别运用到基于代价函数的载波粗同步和基于最大似然迭代的载波细同步之中,将同步器、解调器与译码器联合迭代,从而实现较理想的载波同步。理论研究和仿真结果表明,在低信噪比条件下,该算法能够在大频偏、大相偏范围内实现有效的载波同步,并以较低系统复杂度的代价,获得近似理想的系统性能。     

高阶非线性控制系统相平面的图解实现

非线性控制系统在实际中的存在非常普遍，分析方法有多种。而非线性系统的相平面法既能提供稳态性能信息，又能提供时问响应信息，因而被广泛使用，但相平面法只限于一阶、二阶线性系统的分析。为得到高阶非线性系统的相平面，借助状态空间法，提出一种利用图解方法实现高阶非线性系统相轨迹的作图方法。数值仿真结果表明该算法与解析法相比具有良好的动静态性能、高的控制精度和较强的适应性，同时结果说明了该方法的有效性，算法具有计算简单、易于实现的特点。     

混合不确定多态系统可靠性的EUGF分析方法

在进行多状态系统可靠性分析时,很多情况下系统中同时存在着多个类型不确定信息,如一些复杂系统中,由于样本量的差异,一些信息可以作为随机信息,而另一些信息由于缺少足够的样本,只能以区间形式给出。提出一种基于证据通用生成函数理论的多状态系统可靠性分析方法,来处理多类不确定性信息的多态系统。该方法基于证据不确定性量化理论,能够充分利用区间信息和认知信息,避免了系统中信息的浪费。基于证据量化理论建立证据通用生成函数模型,采用信度和似然度对多态系统进行可靠性评价,提高了基于认知不确定性的可靠性分析结果的可信性。对于同时含有随机信息和认知信息的多态系统,该方法首先通过将随机信息离散处理,然后建立统一的证据通用生成理论模型进行多态可靠性分析。通过案例分析对所提出的方法进行了验证。     

Stabilization of Continuous-Time Systems Against Stochastic Network Uncertainties: Fundamental Variance Bounds

This paper studies the stabilizability and stabilization of continuous-time systems in the presence of stochastic multiplicative uncertainties. The authors consider multi-input, multi-output(MIMO) linear time-invariant systems subject to multiple static, structured stochastic uncertainties,and seek to derive fundamental conditions to ensure that a system can be stabilized under a mean-square criterion. In the stochastic control framework, this problem can be considered as one of optimal control under state-or input-dependent random noises, while in the networked control setting, a problem of networked feedback stabilization over lossy communication channels. The authors adopt a mean-square small gain analysis approach, and obtain necessary and sufficient conditions for a system to be meansquare stabilizable via output feedback. For single-input, single-output(SISO) systems, the condition provides an analytical bound, demonstrating explicitly how plant unstable poles, nonminimum phase zeros, and time delay may impose a limit on the uncertainty variance required for mean-square stabilization. For MIMO minimum phase systems with possible delays, the condition amounts to solving a generalized eigenvalue problem, readily solvable using linear matrix inequality optimization techniques.     

T-S模糊系统的鲁棒耗散控制

通过应用Lyapunov稳定性理论,研究了具有参数不确定性的T-S模糊系统的鲁棒稳定性和耗散性。具有参数不确定性的T-S模糊模型可以以任意精度近似连续非线性不确定系统。假设系统中的参数不确定性是范数有界的。利用Lyapunov稳定性理论给出了鲁棒耗散控制器存在的充分条件。通过解一组线性矩阵不等式(LMIs),可获得鲁棒耗散控制器。设计的鲁棒耗散控制器能够保证对于T-S模糊系统中所有的参数不确定性,闭环系统都是稳定的,且满足给定的耗散性能指标。数值例子证明了方法的有效性。     

OFDM系统中基于盲检测的低复杂度分块SLM算法

为了降低正交频分复用(orthogonal frequency division multiplexing, OFDM)系统中传统选择性映射(conventional selected mapping, CSLM)算法的计算复杂度,提高系统的频谱利用效率,提出了一种基于盲检测的低复杂度分块选择性映射(block selected mapping, BSLM)算法,发送端利用逆快速傅里叶反变换(inverse fast fourier transform,IFFT）性质仅需少量低维IFFT运算即可获得较多的备选序列,接收端采用低复杂度的盲检测方式。仿真分析了所提算法的峰均功率比(peak to average power ratio, PAPR)、立方度量(cubic metric, CM)和误比特率(bit error rate, BER)性能。结果表明,所提算法不仅明显降低了计算复杂度,而且有效抑制了OFDM信号的PAPR和CM,获得与已知边带信息的CSLM算法相近的BER性能。