Use Of Fuzzy System Research Articles

Intelligent mobile robot navigation, Federico Cuesta and Aníbal Ollero, Springer Tracts in Advanced Robotics, vol. 16, Springer: Berlin–Heidelberg, pages: XII + 204. Price $99.00, ISBN: 3‐540‐23956‐1 2005

Intelligent mobile robot navigation, Federico Cuesta and Aníbal Ollero, Springer Tracts in Advanced Robotics, vol. 16, Springer: Berlin–Heidelberg, pages: XII + 204. Price $99.00, ISBN: 3‐540‐23956‐1 2005

Use of fuzzy system in modeling of biped walking robot

Practical biped walking robot is presented in this paper. The biped walking robot is a popular research area in robotics because of the high adaptability of a walking robot in an unstructured environment. However, lots of circumstances which have to

FUZZY ASSOCIATION RULES FOR ESTIMATING CONSUMER BEHAVIOUR MODELS AND THEIR APPLICATION TO EXPLAINING TRUST IN INTERNET SHOPPING

Complex models have been traditionally and increasingly used by both marketing academics and practitioners to represent and understand consumer behaviour. Thus, we firstly pose that models of consumer behaviour firms use to make in which firms are based to take their decisions must be close to what a real Marketing Management Support System should offer, in order to be of use of being usefulness. In this sense, rather than focusing on analysing the quality of the consumer-related marketing phenomena represented by such models – i.e.: those theoretical issues which support their validity –, we take an in-depth look at deeply reflect about the utility of the statistical techniques used to estimate those models theoretically proposed. Thus, we pose that the use of fuzzy systems as a knowledge discovery tool is of great interest for improving the interpretation and understanding of such consumer models. Moreover, we put forward it is proposed a new application for consumer behaviour modelling, based on fuzzy association rules (FAS) for adjusting the data, as a complementary alternative to the results obtained by using the classic technique of model estimation based on Structural Equation Modelling (SEM). With this aim, a behavioural model centred on explaining consumer attitude towards Internet and trust in Internet shopping is presented, being later tested by making use of both FAS and SEM. Finally, a comparative analysis of the results is done, focusing particularly specially on our proposal of methodological application.

Rule-base derivation for intensive care ventilator control using ANFIS

In recent years, much research has been done on the use of fuzzy systems in medicine. The fuzzy rule-bases have usually been derived after extensive discussion with the clinical experts. This takes a lot of time from the clinical experts and the knowledge engineers. This paper presents the use of the adaptive neuro-fuzzy inference system (ANFIS) in rule-base derivation for ventilator control. The change of the inspired fraction of oxygen (FiO 2) advised by eight clinical experts responding to 71 clinical scenarios was recorded. ANFIS and a multilayer perceptron (MLP) were then used to model the relationship between the inputs (the arterial oxygen tension (PaO 2), FiO 2 and the positive end-expiratory pressure (PEEP) level) and the change in FiO 2 suggested. Compared to a previous fuzzy advisor (FAVeM), both the ANFIS and the MLP were found to correlate with the clinicians’ decision better (correlation coefficient of 0.694 and 0.701, respectively compared to 0.630). A formerly developed model-based radial basis network advisor (RBN-MB) was used for comparison. Closed-loop simulations showed that the ANFIS, MLP and the RBN-MB’s performance were comparable to the clinicians’ performance (correlation coefficients of 0.852, 0.962 and 0.787, respectively). The FAVeM’s performance differed from the clinicians’ performance (correlation coefficient of 0.332) but the resulting PaO 2 was still within safety limits.

Local and global bifurcations in simple Takagi-Sugeno fuzzy systems

The relevance of bifurcation analysis in Takagi-Sugeno (T-S) fuzzy systems is emphasized mainly through examples. It is demonstrated that even the most simple cases can show a great variety of behaviors. To understand the richness of asymptotic dynamics one can find in T-S systems, a methodology is proposed by invoking bifurcation theory. Several local and global bifurcations (some of them, degenerate) are detected and summarized in the corresponding bifurcation diagrams. It is claimed,that this kind of careful analysis could help to cope with some criticism raised regarding the blind use of fuzzy systems.

Enhancing analytical methods of collective decision making

A common method of analysis when decisions have to be made by multiple stakeholders using multiple criteria is value tree analysis. Variations of this, such as the Public Value Forum (PVF), have been used especially in complex choices involving environmental issues [Keeney et al., MgtSci, 36, 9, 1990, pp. 1011-30]. Value tree analysis uses Multiattribute Utility Theory (MAUT) [Keeney and Raiffa, 1976] to evaluate a large number of alternatives. Decisionmakers decide the impact an alternative will have on each of many attributes and express how important each attribute is to them. The choice of attributes and the weights attached to them provide evidence of their values and preferences. The success of the PVF depends on the fact that individuals will understand each others' positions as they make explicit the tradeoffs among various attributes. However, participants in the PVF may have difficulty conveying in a precise way the information needed to calculate value scores and preference weights. Also, the language of MAUT lacks the flexibility to measure the degree to which a consensus of opinion can be reached. Fuzzy analysis [Zadeh, Info&Ctrl, 8, 1965, pp. 338-53] provides for uncertainty in scale responses which can be very common in a decisionmaker's choice of environment and flexibility of linguistic expression of preferences. The authors had a group of students decide whether to retain the present use of a cement facility or to adopt a modified use of the facility which involved the use of hazardous waste. Three stakeholder groups emerged from the student group--the community, the company, and the local officials. The attributes used by the participants were monetary impact, risk reduction, risk preference, health, and environmental quality. Using the fuzzy linguistic acceptability, the authors searched for the degree of acceptability each attribute had with each group and determined the lowest degree of acceptability around which a consensus could be obtained on an attribute, e.g., health. Also obtained for each attribute was a most desirable outcome, around which a consensus could be obtained. By examining the difference between the lowest consensus value and the most desirable outcome determined by a stakeholder group on a particular attribute, the authors identified where the greatest disagreement would arise. Thus, the outcome of the decision process is broadened from a single choice. Moreover, using joint analysis of the impact of each attribute and the most desirable outcome, one could assess that the most likely outcome of the decision process would be to reject the modified use of the facility. Strategic behavior could have been adopted by the students and there were limitations in the scope of study and the specifics of the scenario. However, the approach allows the inclusion of linguistic expressions difficult with the use of the traditional quantitative method of MAUT alone. One could expect to see that the complexity of a policy issue like this one is better handled, and its results better defended, with this inclusive, modified use of the PVF in which decisionmaking is enhanced by the use of fuzzy systems.

Fuzzy Production Scheduling for JIT Manufacturing

ABSTRACTProduction scheduling for a flexible manufacturing environment operating under just-in-time involves solving for a different set of criteria compared with the traditional job-shop model. Practical considerations coupled with customer service orientation prevalent in modem organizations today require a scheduling system ensuring as far as possible that goods are delivered on time yet still maintain efficient use of resources within the manufacturing cells. Thus the multi-criteria problem is difficult to solve using existing heuristics without means to combine these rules and weight them accordingly. Furthermore, the ideal scheduling package will also take into consideration the interactions between resource and component to assist in optimal process planning. A revised scheduling system incorporating fuzzy logic to solve the multi criteria problem is proposed. In addition, the system is designed to be implemented using readily available software tools and through the use of fuzzy systems, able to b...

Fuzzy controller synthesis for an inverted pendulum system

A frequently discussed issue in the use of fuzzy systems for control design is related to the ad hoc nature by which controller synthesis is performed, where incorporation of the designer's knowledge into the synthesis procedure is often not straightforward. This paper describes a controller synthesis procedure based on the idea of expanding the usable region of a linear control design technique. Comparative analyses are carried out via implementation of swing-up and balancing control for a rotational inverted pendulum system. For the complete control problem, the paper focuses on three aspects of fuzzy control in the overall control design: direct, supervisory, and auto-tuning fuzzy control. For swing-up control, an energy pumping strategy, enhanced by introducing a fuzzy supervisory mechanism, is utilized. For balancing control, an LQR-based linear control strategy, valid in the “linear region” of operation of the pendulum, is generalized to a nonlinear direct fuzzy control design. For improved performance when modeling uncertainties affect controller performance, a new scheme is developed, again based on the LQR design, which is a simple yet effective auto-tuned fuzzy controller, having the capability to vary its resolution on-line. All controllers are tested on an experimental apparatus, and performance comparisons are drawn.

Switched reluctance motor control via fuzzy adaptive systems

This article presents the application of fuzzy adaptive systems to the problem of torque ripple reduction in a switched reluctance motor. Conventional methods for torque linearization and decoupling are reviewed briefly, as is the previous application, by the authors, of neural network based techniques. A solution based on the use of fuzzy adaptive systems is then described. Experimental measurements of the static torque production characteristics of a 4 kW, four-phase switched reluctance motor form the basis of simulation studies of this novel approach. The simulation results demonstrate the capability of fuzzy adaptive systems to learn nonlinear current profiles that minimize torque ripple. The use of fuzzy systems in this application has potential advantages where the incorporation of a priori information, expressed linguistically, is concerned. Experimental results illustrate the effectiveness of the approach.< <ETX xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">&gt;</ETX>