Hybrid Fuzzy Model-Based Control of Nonholonomic Systems: A Unified Viewpoint

This paper proposes a unified hybrid fuzzy model-based control scheme for uncertain nonholonomic systems. Compared with typical hybrid fuzzy control, the stability analysis is performed based on a new concept of constructing a semicommon Lyapunov function and a new definition called as exponential-like model following. This advancement provides a strict stability analysis but results in relaxed gain conditions. In detail, a unified hybrid Takagi-Sugeno fuzzy model is first introduced for representing well-known nonholonomic systems with a momentum conservation constraint or a no-slip constraint. Then, the hybrid fuzzy controller is derived to ensure robust nonlinear model following control, i.e., an asymptotic convergence with adjustable ultimate bound and arbitrary disturbance attenuation in an -gain sense. Furthermore, an iterative linear matrix inequality technique is proposed to guarantee the stability and avoid the need of a common positive-definite matrix. Finally, the applications are carried out on a hopping robot and a car-like mobile robot. Numerical simulations and experiment results show the expected performances.     

一类带有传感器故障的混合系统的容错控制

A model-based fault tolerant control approach for hybrid linear dynamic systems is proposed in this paper. The proposed method, taking advantage of reliable control, can maintain the performance of the faulty system during the time delay of fault detection and diagnosis (FDD) and fault accommodation (FA), which can be regarded as the first line of defence against sensor faults. Simulation results of a three-tank system with sensor fault are given to show the efficiency of the method.     

一类带有传染器故障的混合系统的容错控制

A model-based fault tolerant control approach for hybrid linear dynamic systems is proposed in this paper. The proposed method, taking advantage of reliable control, can maintain the performance of the faulty system during the time delay of fault detection and diagnosis (FDD) and fault accommodation (FA), which can be regarded as the first line of defence against sensor faults.Simulation results of a three-tank system with sensor fault are given to show the efficiency of the method.     

分层的基于模型诊断方法

1引言 基于模型诊断是为了克服传统诊断方法的严重缺陷而兴起的一项新型智能推理技术,被AI专家誉为诊断理论和技术上的革命[1].在IJCAI-99上,Console和Dressler[2]指出:基于模型诊断对整个AI领域的研究起着重要推动作用.Struss[3]称基于模型诊断是对AI的一个重要挑战和检验.     

Redundancy Relations for the Diagnosis of Hybrid Systems

In the concept of analytical redundancy, the problem of the functional diagnosis of hybrid systems is studied. The solution of this problem assumes checking the redundancy relations between the inputs and outputs of the system. A method for constructing the redundancy relations that includes transformation of the operational and controlling subsystems and then reduction of the operational subsystem to a form without feedbacks is proposed. The problem is solved using the pair algebra of partitions, algebra of functions, and differential-algebraic methods.     

含约束的基于模型的诊断系统

在诊断空间中如何选取理想诊断是诊断系统面临的一个重要问题。在实际的诊断过程中,人们会利用限制条件排除不太可能的诊断,或者利用强制条件选取较优的诊断。按照这个思想,作者提出含约束的基于模型的诊断系统,通过增加依赖于应用领域的约束控制诊断空间,这是一种能够融入计算过程的选择诊断的机制,同时作者在系统拓扑结构的基础上给出了选取理想约束的理论依据。     

On the BGM Model-Based Diagnosis of Failed Modules and Communication Lines in Digital Systems

In the digital systems, combinations of failed components (modules and communication lines) are possible such that their potential syndromes are indistinguishable by one-step diagnosis. The logical functions used to decode the real syndrome were constructed with regard for the features of the BGM model. A procedure for sequential diagnosis of the failed components was developed. The requirements on the allocation (composition) of the operable components enabling correct diagnostic conclusions were established. Examples of using the procedure in the cases where these requirements are satisfied to some extent were presented.     

Model-Based Diagnosis and Conditional Logic

The model-based diagnostic approach was first introduced to overcome the limitations of heuristic systems. However, research on model-based systems showed that the model-based diagnosis approaches resort to assumptions that can be viewed as the return, though controlled, of heuristics into diagnostic reasoning. In this paper we focus on diagnosis with component-oriented device models. We argue for the need to represent and reason with these assumptions. We present a conditional logic, DL, That is suitable for diagnostic reasoning and allows us to represent and reason with assumptions.     

基于模型诊断的分步求解

对诊断问题的分解进行研究,给出了候选诊断的分解与组合定理.在此基础上,提出了利用分步求解方法实现诊断分解的算法,并对算法的正确性、完备性和复杂性进行了证明.实验结果表明,分步求解方法明显提高了包含多个输出的系统的诊断效率.与利用变量假定例化值分解诊断问题的方法相比,该算法能提高了效率并且扩大了适用范围.     

基于模型诊断的抽象分层过程

分层诊断是降低基于模型诊断计算复杂性的一个重要方法,在分层诊断中很重要的一步是构造系统的抽象分层模型,以往的分层方法都是建立在某一种特定抽象模型基础上,没有将抽象的一般理论与基于模型诊断中的分层过程相联系,并且对自动生成系统的分层表示方法也没有形式化的分析.KRA(Knowledge Reformulation and...     

基于模型的网络控制系统性能优化

文中讨论了采用基于模型的设计方法来减小网络控制系统的网络诱导时延的问题。通过在系统中加入一个对象模型可以增大系统的容许采样周期并减小时延,针对现有基于模型的网络控制系统设计方法中存在的不足,文中给出了系统的稳定性定理并提出了一种新的寻找最优模型的方法,仿真结果表明了该方法的有效性。     

基于最优FADEC系统故障诊断方法

研究航空发动机控制系统传感器与执行机构故障的统一优化检测问题,Luenberger观测器结构简单、计算量小、设计简单,特别适合对变化缓慢的参数(如发动机控制系统软故障)进行估计.提出建立动态特性已知而初始条件未知的航空发动机控制系统典型故障模型,通过对故障状态和系统状态进行分离,并设计降维Luenberger观测器,得到满足故障估计误差和控制能量综合最优的故障诊断器,实时输出故障最优估计值,实现对传感器和执行机构故障的检测.经仿真验证,改进方法具有收敛快、检测准确度高的特点,满足实时性要求.     

基于模型的嵌入式系统性能分析框架

在现代嵌入式系统中,性能的重要性日益凸显.传统的基于测量的性能分析方法在运行时对性能进行测试,往往在代码实现后才考虑实施.若此时发现的问题是体系结构或设计因素造成的,修复的代价将非常昂贵.提出了一种基于形式化模型的性能分析（formal method-based performance analysis,简称FMPA)方法框架,希望在系统开发的早期,对系统设计模型进行性能分析,以便尽早发现并解决潜在的性能问题.FMPA具有统一的对外接口（UML-MARTE),基于多种形式化模型,并可对多种系统性能指标进行分析.该方法适用于基于模型的开发过程,可为实时嵌入式系统的设计开发提供多项性能指标的参考.通过介绍利用实时模型检测技术分析响应时间与吞吐量,利用概率模型检测技术分析系统可靠性,以及FMPA方法的支撑工具FMPAer的总体设计方案,说明了FMPA方法框架的可行性.     

基于模型诊断的动态测试策略

本文通过分析基于模型诊断的候选诊断集的特点，提出了基于模型的动态测试策略，并提出了采用关联规则挖掘的技术－－频繁模式增长法，作为解决选择测试元件过程的处理技术，巧妙地解决了动态选择的策略问题。     

基于模型的曲轴位置传感器故障诊断研究

为了对汽车发动机转速传感器作出快速准确的诊断,结合曲轴信号处理原理,在MATLAB/simulink中设计基于卡尔曼滤波器残差检验的OBD诊断模块,实现了曲轴位置传感器无信号、信号错误等故障诊断功能。针对卡尔曼滤波器法无法排除掉非故障性信号输入的缺点,在卡尔曼滤波法基础上加入逻辑诊断,通过条件判断以启动诊断,加入决策逻辑以确定故障状态。验证结果表明,卡尔曼滤波器法能够准确快速识别两种传感器故障,但在非故障性信号时无法准确判断故障。加入诊断逻辑的改进卡尔曼滤波法能够准确排除非故障性输入,保证诊断的准确性。     

基于模型的机载燃油系统故障诊断研究

针对某型号飞机的燃油系统进行故障诊断,应用基于模型的故障诊断算法,采用离散的状态变量描述系统行为和功能,基于一致性算法判定系统当前行为是否正常以及冲突搜索算法对异常进行诊断.诊断过程引入故障可能性概率的函数Rank,避免了传统穷举方法,有效提高了算法的效率.诊断结果能够很好地涵盖单故障以及多故障组合,同时也能满足系统进行实时故障诊断的要求.     

社交关系在基于模型社会化推荐系统中的影响

目前社会化推荐系统方面的研究主要集中于构建性能更优的基于模型的推荐算法,然而模型算法中分解得到的隐式特征和社交信息的变化会给推荐性能带来不确定性。为了消除不确定性,探究了在基于模型的社会化推荐系统中社交关系的变化对推荐性能的影响。实验首先按比例移除关系网络中的连边或节点,再对推荐质量进行评估,结果表明,社交关系的数量增多将对推荐质量带来明显提升,同时关系网络中心节点对推荐质量的影响巨大。因此,在构建基于模型的社会化推荐系统的过程中应尽可能多地获取社交关系,并提升中心节点的关系在推荐中的权重,降低非中心节点(潜在噪声)的影响。     

基于模型的诊断问题分解及其算法

对诊断问题的分解进行了研究，给出了基于模型诊断问题分解的判定定理，刻画了利用系统观测值和参量假定例化值分解诊断问题，提出了有条件可分解诊断问题的概念，进一步刻画了基于模型的诊断问题分解，对如何利用参量假定例化值分解诊断问题给出了最可能优先算法，并对该算法的正确性、完备性及复杂性进行了证明，文中的工作为具有树型结构的系统诊断效率的提高提供了理论依据。     

O-Minimal Hybrid Systems

An important approach to decidability questions for verification algorithms of hybrid systems has been the construction of a bisimulation. Bisimulations are finite state quotients whose reachability properties are equivalent to those of the original infinite state hybrid system. In this paper we introduce the notion of o-minimal hybrid systems, which are initialized hybrid systems whose relevant sets and flows are definable in an o-minimal theory. We prove that o-minimal hybrid systems always admit finite bisimulations. We then present specific examples of hybrid systems with complex continuous dynamics for which finite bisimulations exist. Date received: June 9, 1998. Date revised: June 28, 1999.