一类飞行器的多变量鲁棒控制

对一类飞行器建立了数学模型并进行了分析,使用非最小相位控制系统的智能设计方 法,设计了飞行器的多变量鲁棒控制系统.基于真实模型的控制系统仿真证实了这一设计方 法的有效性.该设计方法对航空航天控制工程具有参考意义.     

鲁棒对角优势及在多变量系统鲁棒设计中应用

本文基于多变量系统奈氏阵列设计方法和鲁棒对角优势保证系统鲁棒稳定的结论,提出一种多变量系统鲁棒设计方法,该方法设计的鲁棒预补偿器使广义对象在一定摄动范围内严格符合鲁棒对角优势定义,因而系统一定是鲁棒稳定的,该方法具有保守性小,设计的控制器简单,易于工程实现等优点,用该方法对一参数不确定性工业对象进行了鲁棒系统设计,结果令人满意。     

用输出反馈配置鲁棒极点的李雅普诺夫直接法*

本文讨论了输出反馈配置线性多变量定常系统鲁棒极点的问题,提出了一种设计方法和有关定理,并用实例说明了该法的应用。     

一种多变量系统鲁棒设计方法

本文介绍一种多变量系统鲁棒设计方法.该方法是基于"鲁棒对角优势保证鲁棒稳定"这 个一般性结论,其核心是多模型加权准优势化算法,该算法设计的鲁棒预补偿器,使系统为鲁 棒对角优势.用该设计方法对一大型工业加热炉进行鲁棒系统设计,结果令人满意.     

鲁棒观测器-控制器的设计*

本文讨论了多变量系统参数摄动下鲁棒观测器-控制器的设计方法,并给出了带观测器-控制器闭环系统的鲁棒稳定条件。     

加热炉控制系统鲁棒性设计

本文探讨了多变量系统鲁棒稳定性和鲁棒对角优势的关系,得出了系统鲁棒对角优势保证系统鲁棒稳定的一般性结论,提出了一种鲁棒系统的设计方法,并在IBM微机上实现了计算机辅助设计,用该方法对大型加热炉控制系统进行了设计,结果表明,设计的系统具有鲁棒稳定性和良好的性能鲁棒性。     

不确定区域下基于自适应并行遗传的最优鲁棒控制器

目前使用遗传算法设计鲁棒控制器时, 都要人为地给定变量搜索空间. 当变量区域不确定时, 采用自适应并行遗传算法设计出最优鲁棒控制器, 该方法根据当前搜索到的各种群最优个体的分布情况, 运用概率统计理论求出变量区域的最小方差无偏估计, 不断缩小不确定的变量搜索区域, 从而逐步达到最优, 并且考虑了种群个体适应度对算法中交叉概率和变异概率的影响. 该方法能设计出简单正则、阶数低的最优鲁棒控制器, 而且仿真结果表明, 这些控制器有效地避免了局部最优, 提高了算法的寻优精度和收敛速度.     

最优鲁棒输出反馈控制器参数化设计

本文提出了一种输出反馈控制器设计的参数化方法,同时利用投影定理给出了一个鲁棒性能指标,然后选择所得到的自由参数使上述鲁棒性能指标取最小而获得输出反馈的最优鲁棒设计。     

基于鲁棒规范变量分析的故障诊断方法

针对工业过程的建模数据中含有离群点的情况,提出一种基于鲁棒规范变量分析(CVA)的故障诊断方法.该方法使用相关系数的鲁棒估计代替传统的相关系数,通过基于粒子群算法的投影寻踪技术计算最大化鲁棒相关系数的规范变量,从而建立统计模型并监控统计量检测过程的变化.连续搅拌反应器(CSTR)系统的仿真结果说明,鲁棒规范变量分析方法能在含离群点数据的基础上建立准确的统计模型,比规范变量分析更有效地监控过程变化.     

含攻击角度约束的三维制导控制一体化鲁棒设计方法

针对具有攻击角度约束的STT飞行器对象,提出了一种三维制导控制一体化鲁棒设计方法.首先,基于某些可行性简化原则,推导出面向三维制导控制一体化设计的非线性数学模型.然后,针对一类多变量非线性系统,通过引入控制补偿项,提出了一种鲁棒动态逆设计方法.结合鲁棒动态逆和动态面控制方法,完成了制导控制一体化鲁棒算法的设计.仿真结果表明,所提出的三维制导控制一体化算法可保证飞行器的稳定飞行和精确制导,并且满足攻击角度的约束要求.此外,该方案具备针对参数不确定性和等效干扰的强鲁棒性能.     

Mathematical model for quality cost optimization

Quality engineering uses robust design in order to improve quality by reducing the effects of variability. Variability of the product can be reduced by two stages. One is parameter design which is adjustable to the nominal value so that output is less sensitive to the cause of variability. Other one is tolerance design which is to reduce the tolerance in order to control variability. All costs incurred in a product life cycle can be divided into two categories—manufacturing cost before the sale to the customer and quality loss after the shipment of the product to the customer. It is very important to find the optimum tolerances for each of the characteristics. A balance between manufacturing cost and quality loss should be arrived at in the tolerance design for quality improvement and cost reduction. For the case of Nominal-The-Best, a mathematical model is developed in order to determine the optimum product tolerance and minimize the total cost which includes the manufacturing cost and the quality loss. Since the process capability index (C_pm) shows the balance of quality responsibility between the design and the manufacturing engineers, this is taken as the basis in developing the functional relationship between the variability of the product and the tolerance. Based on these relationships, the total cost of model can be expressed as a function of product tolerance from which the optimal tolerance limits can be found out. Finally, using this model a tolerance design approach that increases the quality and reduces the cost can be achieved in the early stages of the product process design stage itself.     

Constraint-based functional design verification for conceptual design

In the early stages of mechanical product design, designers not only need to determine the physical structure of the design, but also need to verify that the design functions properly with the allowable values or ranges of values of the relevant design attributes. Existing work on design verification is either aimed at specific design problems, which are generally carried out at the downstream design stages, or aimed at deriving design behavior using a behavioral simulation approach. Functional design verification has largely been neglected by the research society. To tackle this problem, we propose a generic constraint-based approach that is based on a comprehensive functional design model. A number of strategies are proposed for the approach, including strategies for design variables reduction, variable dependency graph development, constraint propagation, and dynamic verification of a design over an assigned set of attributes (variables). The approach is implemented as part of a functional modeling design environment. A simple design verification case is presented to illustrate our approach.     

产品结构设计的数据模型

结构设计的产品数据模型很少受到研究,在整个产品数据模型中形成了一个断层,从产品整个生命周期的产品数据模型分析入手,结合一身的特点,对结构设计的产品数据建模进行了研究,提出了结构基元,结构变元的概念和结构变元设计,以结构变地为基础建立了结构设计的产品数据模型类链表实现结构设计的产品数据模型。     

Simultaneous optimal selection of design and manufacturing tolerances with alternative manufacturing process selection

Tolerance specification is an important part of mechanical design. Design tolerances strongly influence the functional performance and manufacturing cost of a mechanical product. Tighter tolerances normally produce superior components, better performing mechanical systems and good assemblability with assured exchangeability at the assembly line. However, unnecessarily tight tolerances lead to excessive manufacturing costs for a given application. The balancing of performance and manufacturing cost through identification of optimal design tolerances is a major concern in modern design. Traditionally, design tolerances are specified based on the designer’s experience. Computer-aided (or software-based) tolerance synthesis and alternative manufacturing process selection programs allow a designer to verify the relations between all design tolerances to produce a consistent and feasible design. In this paper, a general new methodology using intelligent algorithms viz., Elitist Non-dominated Sorting Genetic Algorithm (NSGA-II) and Multi Objective Particle Swarm Optimization (MOPSO) for simultaneous optimal selection of design and manufacturing tolerances with alternative manufacturing process selection is presented. The problem has a multi-criterion character in which 3 objective functions, 3 constraints and 5 variables are considered. The average fitness factor method and normalized weighted objective functions method are separately used to select the best optimal solution from Pareto optimal fronts. Two multi-objective performance measures namely solution spread measure and ratio of non-dominated individuals are used to evaluate the strength of Pareto optimal fronts. Two more multi-objective performance measures namely optimiser overhead and algorithm effort are used to find the computational effort of NSGA-II and MOPSO algorithms. The Pareto optimal fronts and results obtained from various techniques are compared and analysed.     

Concurrent optimal adjustment of nominal dimensions and selection of tolerances considering alternative machines

Traditional practice to tolerance design has been a part of a three-step sequential approach to the overall product design process involving (i) conceptual design, (ii) parameter design, and (iii) tolerance design, in isolation. This practice works well for linear assemblies, as the sensitivities of tolerances are fixed, i.e. independent of the nominal dimensions. However, for nonlinear assemblies after the second step, an integrated approach involving minor adjustment of nominal dimensions and selection of tolerances in the third step, can be better to control the variability in the assembly output characteristic. The latter case has been addressed in this study. Simultaneous selection of design and manufacturing tolerances, and choice of a machine from amongst the alternatives, frequently encountered in different stages of realization of individual dimensions, are important issues in product development. Optimal design problem with focus on these issues has been attempted here. The resulting optimization problem involving a combinatorial and nonlinear search space cannot be effectively solved for the global solution using conventional optimization techniques. The genetic algorithm, a nontraditional optimization technique, has been proposed in this research. The solution of the aforementioned concurrent design problem has been demonstrated with the help of a simple case study.     

Self-organizing migration algorithm applied to machining allocation of clutch assembly

Tolerancing is an important issue in product and manufacturing process designs. The allocation of design tolerances between the components of a mechanical assembly and manufacturing tolerances in the intermediate machining steps of component fabrication can significantly affect the quality, robustness and life-cycle of a product. Stimulated by the growing demand for improving the reliability and performance of manufacturing process designs, the tolerance design optimization has been receiving significant attention from researchers in the field. In recent years, a broad class of meta-heuristics algorithms has been developed for tolerance optimization. Recently, a new class of stochastic optimization algorithm called self-organizing migrating algorithm (SOMA) was proposed in literature. SOMA works on a population of potential solutions called specimen and it is based on the self-organizing behavior of groups of individuals in a “social environment”. This paper introduces a modified SOMA approach based on Gaussian operator (GSOMA) to solve the machining tolerance allocation of an overrunning clutch assembly. The objective is to obtain optimum tolerances of the individual components for the minimum cost of manufacturing. Simulation results obtained by the SOMA and GSOMA approaches are compared with results presented in recent literature using geometric programming, genetic algorithm, and particle swarm optimization.     

支持参数和公差设计的多学科协同建模

分析了多学科协同设计的耦合关系，提出支持参数和公差设计的多学科协同建模．首先。获得设计初始阶段各领域专家给出的约束条件和设计变量的大致范围；然后，抽取所有领域中在参数和公差设计阶段的耦合参数和相关约束；最后，构建产品的变动约束网络模型．在多学科协同建模中，考虑了不等式约束条件的转化、微分方程形式约束的转化、参数和公差的综合，以及与三维CAD系统的集成；为进一步实现参数和公差协同求解奠定了基础。     

Multiple-view feature modelling for integral product development

To allow a designer to focus on the information that is relevant for a particular product development phase, is an important aspect of integral product development. Unlike current modelling systems, multiple-view feature modelling can adequately support this, by providing an own view on a product for each phase. Each view contains a feature model of the product specific for the corresponding phase. An approach to multiple-view feature modelling is presented that supports conceptual design, assembly design, part detail design and part manufacturing planning. It does not only provide views with form features to model single parts, as previous approaches to multiple-view feature modelling did, but also a view with conceptual features, to model the product configuration with functional components and interfaces between these components, and a view with assembly features, to model the connections between components. The general concept of this multiple-view feature modelling approach, the functionality of the four views, and the way the views are kept consistent, are described.     

Generation and evaluation of product concepts by integrating extended axiomatic design,quality function deployment and design structure matrix

Existing product concept generation and evaluation methods are mainly based on designers' experience to determine design schemes in the process of product development, which is time-consuming and ineffective. This paper proposes an approach to generate and evaluate design concepts by integrating the extended axiomatic design, quality function deployment and design structure matrix. Different design domains are mapped for matrix operations to generate feasible concepts based on design criteria. A domain mapping matrix is built to determine technical measures, functional requirements and design parameters based on customer requirements. The proposed approach provides a structured method to quantify, validate and qualify design concepts. A case study of the design of a hand rehabilitation device demonstrates the effectiveness of the proposed method.     

Accessibility and ergonomic analysis of assembly product and jig designs

In the aircraft industry, the design of floor assembly jigs (FAJs) is an important activity that directly affects productivity. It involves tool frame generation and locator and clamp placement to ensure that the assembly components are held properly with respect to each other to meet the required tolerances. The tool designer also has to analyze the design to ensure that the assembly process does not pose accessibility and ergonomics related problems. The current approach is dependent on the experience of the tool designer and the limited visualization possible on commercial CAD systems. This leads to extensive redesign when accessibility and ergonomic related problems are detected on the physical prototype. In this research, an integrated Virtual Reality-based environment is being developed for the analysis of assembly product and jig designs. CAD models of the assembly product and jig are imported into a Virtual Reality (VR)-based visualization system for accessibility analysis. A motion tracking system is integrated to allow ergonomic posture analysis. The combined VR and motion tracking system allows evaluation of alternate assembly sequences and the jig design. In this paper, the theoretical basis for the analysis environment is presented along with details of the prototype implementation of this system.

Relevance to industry

Floor assembly jigs are used extensively by the aircraft industry. Improvement of their design process will lead to savings in better design and reduced development time and cost. Better designs will require fewer changes after the jigs have been fabricated. The overall result will be a reduction in product realization time and cost and improved product quality.