Trapezoidal Intuitionistic Fuzzy Aggregation Operator Based on Choquet Integral and Its Application to Multi-Criteria Decision-Making Problems

The Choquet integral can serve as a useful tool to aggregate interacting criteria in an uncertain environment. In this paper, a trapezoidal intuitionistic fuzzy aggregation operator based on the Choquet integral is proposed for multi-criteria decision-making problems. The decision information takes the form of trapezoidal intuitionistic fuzzy numbers and both the importance and the interaction information among decision-making criteria are considered. On the basis of the introduction of trapezoidal intuitionistic fuzzy numbers, its operational laws and expected value are defined. A trapezoidal intuitionistic fuzzy aggregation operator based on the Choquet integral is then defined and some of its properties are investigated. A new multi-criteria decision-making method based on a trapezoidal intuitionistic fuzzy Choquet integral operator is proposed. Finally, an illustrative example is used to show the feasibility and availability of the proposed method.     

基于Choquet模糊积分SVM集成及其实证研究

为了进一步提高SVM集成的泛化能力,提出了基于Choquet模糊积分的SVMs集成方法,综合考虑各个子SVM输出重要性,避免了现有SVM集成方法中忽略次要信息的问题。应用该方法,以高校的区域经济贡献度为例进行仿真试验,结果表明基于Choquet模糊积分的SVMs集成方法较基于Sugeno模糊积分SVMs集成方法和基于投票策略的SVMs集成方法具有更高的准确性。该方法是可行、有效的,具有一定的推广价值。     

Information aggregation in industrial performance measurement: rationales,issues and definitions

Industrial performance can be defined in terms of numerous criteria to be synthesized for global control purposes, many of them being of a complex nature, i.e. not related to one elementary physical measure. In this context, determining a global performance expression raises the issue of performance expression aggregation. To address such an aggregation issue, so-called performance measurement systems need to be implemented. The analysis of the corresponding literature leads to the conclusion that the majority of the proposed approaches either do not provide explicit aggregation mechanisms or propose overly simplistic methods really to cope with the complexity of the situations at hand. Only a few consider explicit adequate aggregation methods. Therefore, a thorough characterization of performance expression aggregation based on four stages, namely extraction, representation, combination and interpretation, as proposed by the information aggregation community is presented. The contribution deals with the definition of a performance expression combination based on two kinds of performance expressions commonly encountered (physical measures and performance evaluations, i.e. objective satisfaction degrees). Methodological guidelines for performance expression aggregation are proposed as well as associated mathematical tools, especially the fuzzy Choquet integral for taking criteria interactions into account. An industrial case study is used as an illustration, and some concluding remarks and emerging problems to be considered in the future, such as temporal aggregation, are finally pointed out.     

Multidisciplinary design methodology for mechatronic systems based on interface model

Mechatronic system is considered as the resulting integration of electrical/electronic system, mechanical parts and information processing. Therefore, to enable a systematic design process of mechatronic systems with a high-level integration, the so-called multidisciplinary integrated design is required. However, neither academia nor industry has yet provided an effective solution, which can fully support the whole design process to achieve such multidisciplinary integrated design. In order to organise the design activities from different disciplines and to aid the designers to achieve the multidisciplinary integrated design, the authors propose a design methodology based on a multidisciplinary interface model. In line with the systems engineering practices, an extended V-model is used as the macro-level process in the proposed design methodology. It starts with identification of requirements on the entire system and ends with a user-validated system. The hierarchical design model is adopted as the micro-level process. It supports the specific design phases where individual designers can structure design sub-tasks and proceed and react in unforeseen situations. To ensure the consistency and traceability between the two levels, the multidisciplinary interface model is proposed. This design methodology is demonstrated by studying the design process of a quadrotor.     

Passive estimated state feedback fuzzy controller design for discrete perturbed fuzzy systems with multiplicative noises

This article presents an estimated state feedback fuzzy controller design method for uncertain passive discrete-time nonlinear stochastic systems with multiplicative noises. The nonlinear stochastic systems considered in this article are represented by Takagi–Sugeno (T–S) fuzzy models. For describing stochastic behaviors, stochastic differential equations are used to structure the stochastic T–S fuzzy model for representing nonlinear stochastic systems. Besides, the uncertainties of the controlled system are considered for dealing with molding errors and varying parameters. The concept of parallel distributed compensation is employed in this article to construct the estimated state feedback fuzzy controllers. Applying the Lyapunov and passivity theories, the sufficient stability conditions are derived in terms of linear matrix inequality. Finally, a numerical example is provided to show the effectiveness and applicability of the proposed fuzzy controller design approach.     

Arrow’s theorem, multi-criteria decision problems and multi-attribute preferences in engineering design

Arrow’s theorem poses limits to the translation of the different preference orders on a set of options into a single preference order. In this paper, I argue, against opinions to the contrary, that Arrow’s theorem applies fully to multi-criteria decision problems as they occur in engineering design, making solution methods to such problems subject to the theorem’s negative result. Discussing the meaning and consequences for engineering design, I review the solution methods to such problems presented in the engineering design literature in the light of the theorem. It appears that underlying such methods is a mix-up of two fundamentally different problem definitions, as the theory of multi-attribute preferences, which is often presented as an adequate approach for engineering design, in fact fails to address the Arrowian multi-criteria problem. Finally, I suggest ways how engineering design might adopt results from discussions of Arrow’s theorem elsewhere in resolving its multi-criteria decision problems.     

An aggregation technique for optimal decision-making in materials selection

Materials selection is an onerous but very important activity in the design process. An inappropriate choice of material(s) can adversely affect the productivity and profitability and hence reputation of a manufacturing organization. The complexity of materials selection makes multi-criteria analysis an invaluable tool in the engineering design process. However, the application of various multi-criteria decision making (MCDM) methods can yield different results, especially when alternatives lead to similar performance. Therefore, an aggregation technique is proposed in this paper for optimal decision-making. In this approach, ranking orders obtained by various MCDM methods are used as the input of the suggested procedure and the outputs are aggregation rankings, which help designers and engineers to reach a consensus on materials selection for a specific application. An illustrative example is given to demonstrate the application of this procedure and its effectiveness in obtaining optimal materials selection.     

基于单目视觉的四旋翼飞行器目标跟踪算法研究

以AR.drone四旋翼飞行器为研究平台,提出一种基于AR.drone前置单目摄像头,并结合卡尔曼滤波跟踪视频中移动目标的方法。将采集得到的RGB图像经过颜色空间转换成对光照变化影响不大的HSV图像;通过OpenCV对视频中跟踪目标的图像去噪,对轮廓进行检测寻找图像中最大的轮廓目标,并通过卡尔曼滤波对目标位置进行修正;计算四旋翼飞行器的飞行朝向并实现四旋翼飞行器对视频区域里移动目标的跟踪。实验表明,该方法有效地实现了对移动目标跟踪的准确性、稳定性和快速性。     

A multi-objective modular design method for creating highly distinct independent modules

With the current rise in environmental concerns, customers want products that reduce environmental impacts. As a result, new multi-objective modular design methods are needed that can consider multiple design objectives, related to both the customers’ and the companies’ functional, environmental, and economical constraints and objectives. Most previous multi-objective modular design methods create module configurations, in which each module meets all of the design objectives. However, highly distinct independent modules are important for current product replacement processes. This paper presents an innovative multi-objective green modular design method that uses atomic theory and fuzzy clustering to create module configurations, in which each module meets one distinct design objective. This paper also presents case studies that demonstrate the capabilities of the new multi-objective green modular design method.     

Controlling asynchronous team design environments by simulated annealing

An organizational strategy for design environments,asynchronous teams, is reviewed. Simulated annealing is used to implement the necessarycontracting search behavior of asynchronous teams. An example of an asynchronous team design environment controlled by simulated annealing is given from the building design domain. The simulated annealing algorithm used, which has been modified for distributed use and multi-criteria, non-preference objectives, is described.     

Robust motion control design for dual-axis motion platform using evolutionary algorithm

This paper presents a new approach to deal with the dual-axis control design problem for a mechatronic platform. The cross-coupling effect leading to contour errors is effectively resolved by incorporating a neural net-based decoupling compensator. Conditions for robust stability are derived to ensure the closed-loop system stability with the decoupling compensator. An evolutionary algorithm possessing the universal solution seeking capability is proposed for finding the optimal connecting weights of the neural compensator and PID control gains for the X and Y axis control loops. Numerical studies and a real-world experiment for a watch cambered surface polishing platform have verified performance and applicability of our proposed design.     

A study on group decision-making based fault multi-symptom-domain consensus diagnosis

In the field of fault diagnosis for rotating machines, the conventional methods or the neural network based methods are mainly single symptom domain based methods, and the diagnosis accuracy of which is not always satisfactory. In this paper, in order to utilize multiple symptom domains to improve the diagnosis accuracy, an idea of fault multi-symptom-domain consensus diagnosis is developed. From the point of view of the group decision-making, two particular multi-symptom-domain diagnosis strategies are proposed. The proposed strategies use BP (Back-Propagation) neural networks as diagnosis models in various symptom domains, and then combine the outputs of these networks by two combination schemes, which are based on Dempster–Shafer evidence theory and fuzzy integral theory, respectively. Finally, a case study pertaining to the fault diagnosis for rotor-bearing systems is given in detail, and the results show that the proposed diagnosis strategies are feasible and more efficient than conventional stacked-vector methods.     

Engineering design and mechatronics: The schemebuilder project

The paper describes the development of a software design aid for use at the conceptual stage of engineering design. It is intended for use in the design of mechatronic products but has wider potential uses. Early approaches were based on function structures and tables of options and the system that evolved allows the assembly of schemes linked by matching their input and output ports. A database of components is provided which can be accessed via different indexes and the designer can easily create and compare alternative schemes at the concept stage.A bond graph approach is used to define the interconnections between components. This allows correct port matching but also provides for future development such as constraint propagation through the design and links to simulation tools.     

Computation of pareto optima in structural design

The structural design problem is acknowledge to be commonly multi-criteria in nature. The various bases for multi-criteria optimization methodologies are outlined and a computationally viable method for generating Pareto optimal solutions is adopted for the structural design problem where the criteria may be non-commensurable. A numerical example on optimal truss design illustrating non-commensurable criteria is given.     

基于Sugeno型模糊神经网络的空间杆系结构的压电驱动器主动控制

基于自主研发的压电主动杆件的振动控制特性,采用主动杆件两端节点的相对位移和相对速度作为输入以及控制电流作为输出,设计了空间杆系结构的Sugeno型模糊神经网络控制系统。首先通过LQR方法对结构进行控制产生训练数据样本,再利用神经网络的自适应学习功能进行模糊划分及产生模糊规则,最后利用模糊系统的推理能力对空间杆系结构模型进行基于地震响应的主动控制仿真,同时与基于经验的Mamdani型模糊推理规则进行仿真对比。仿真结果表明两种模糊推理模型对结构模型的控制都能达到良好效果,但是由于Sugeno型模糊推理的计算简单,其仿真速度比Mamdani型模糊推理快几十倍,而且省去了人为的经验总结过程,因而采用Sugeno型模糊神经网络控制器更能满足工程应用的要求。     

Evaluating the Impact of Software Security Tactics: A Design Perspective

Design architecture is the edifice that strengthens the functionalities as well as the security of web applications. In order to facilitate architectural security from the web application’s design phase itself, practitioners are now adopting the novel mechanism of security tactics. With the intent to conduct a research from the perspective of security tactics, the present study employs a hybrid multi-criteria decision-making approach named fuzzy analytic hierarchy process-technique for order preference by similarity ideal solution (AHP-TOPSIS) method for selecting and assessing multi-criteria decisions. The adopted methodology is a blend of fuzzy analytic hierarchy process (fuzzy AHP) and fuzzy technique for order preference by similarity ideal solution (fuzzy TOPSIS). To establish the efficacy of this methodology, the results are obtained after the evaluation have been tested on fifteen different web application projects (Online Quiz competition, Entrance Test, and others) of the Babasaheb Bhimrao Ambedkar University, Lucknow, India. The tabulated outcomes demonstrate that the methodology of the Multi-Level Fuzzy Hybrid system is highly effective in providing accurate estimation for strengthening the security of web applications. The proposed study will help experts and developers in developing and managing security from any web application design phase for better accuracy and higher security.     

Optimal neuro‐fuzzy control of hepatitis C virus integrated by genetic algorithm

Hepatitis C blood born virus is a major cause of liver disease that more than three per cent of people in the world is dealing with, and the spread of hepatitis C virus (HCV) infection in different populations is one of the most important issues in epidemiology. In the present study, a new intelligent controller is developed and tested to control the hepatitis C infection in the population which the authors refer to as an optimal adaptive neuro‐fuzzy controller. To design the controller, some data is required for training the employed adaptive neuro‐fuzzy inference system (ANFIS) which is selected by the genetic algorithm. Using this algorithm, the best control signal for each state condition is chosen in order to minimise an objective function. Then, the prepared data is utilised to build and train the Takagi–Sugeno fuzzy structure of the ANFIS and this structure is used as the controller. Simulation results show that there is a significant decrease in the number of acute‐infected individuals by employing the proposed control method in comparison with the case of no intervention. Moreover, the authors proposed method improves the value of the objective function by 19% compared with the ordinary optimal control methods used previously for HCV epidemic.Inspec keywords: epidemics, diseases, blood, medical computing, microorganisms, genetic algorithms, fuzzy control, neurocontrollers, adaptive control, medical control systemsOther keywords: genetic algorithm, hepatitis C blood born virus, liver disease, hepatitis C virus infection, epidemiology, intelligent controller, optimal adaptive neuro‐fuzzy controller, adaptive neuro‐fuzzy inference system, ANFIS, genetic algorithm, control signal, state condition, objective function minimisation, Takagi‐Sugeno fuzzy structure, acute‐infected individuals, ordinary optimal control methods, HCV epidemic     

Research on conceptual design of mechatronic systems

Based on the fact that function-structure generating and function solving are alternant processes with mutual causality during the conceptual design phase of mechatronic systems, a conceptual design cyclic feedback solving model of a mechatronic system is put forward on the basis of mapping between function layer, effect layer, working principle layer and structure layer. The process of solving single and system functions is analysed. Key technologies of interface matching and function solving are then advanced. Finally, a computer-aided conceptual design automatic software system for mechatronic systems is developed and the conceptual design of a computerised embroidery machine is given as an example. This work was supported by the National Natural Science Foundation of China (Grant No. 50375045) and the Shanxi Natural Science Foundation of China (Grant No. 20041070).     

Behavioural representation and simulation of design concepts for systematic conceptual design of mechatronic systems using Petri Nets

The systematic representation of design concepts is an important requirement for computational support during the conceptual design stage within the process of product development. Behavioural simulation of design concepts is used as a systematic representation framework, and behavioural representation is based on modelling and simulating the behaviour of a design artefact at the conceptual level to perform an overall function, leading to behaviour-based conceptual design. The behaviour-based conceptual design approach is critical for mechatronic systems since they require synergistic integration starting from the initial conceptual design phase. The present study is focused on behavioural representation and simulation of design concepts via discrete event system specification formalism and Petri Nets so as to contribute to systematic conceptual design in mechatronic systems. The paper introduces a representation framework for the behaviour-based conceptual design of mechatronic systems and its implementation on five selected case studies, among laboratory-level educational robots. In addition to Petri Net modelling and computer simulations, the implementation also includes physical simulations of the intended operational behaviours for educational robots on a distributed physical structure called the ‘desktop design model’. In this paper, implementation on one of these case studies, namely the ‘frog robot’, is presented in detail.     

Exponential stability and stabilization of uncertain T–S fuzzy system with time-varying delay

In this article, the problem of exponential stability and stabilization is investigated for Takagi–Sugeno fuzzy time-varying delay systems with parameter uncertainties. Improved conditions are presented in terms of linear matrix inequalities (LMIs). The desired fuzzy controller is obtained by solving these LMIs. In addition, the new integral inequalities can derive less conservative stability criteria. In the end, some numerical simulations are given to illustrate the validity of the proposed methodology.