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The purpose of the Journal of Intelligent & Fuzzy Systems: Applications in Engineering and Technology is to foster advancements of knowledge and help disseminate results concerning recent applications and case studies in the areas of fuzzy logic, intelligent systems, and web-based applications among working professionals and professionals in education and research, covering a broad cross-section of technical disciplines.
The journal will publish original articles on current and potential applications, case studies, and education in intelligent systems, fuzzy systems, and web-based systems for engineering and other technical fields in science and technology. The journal focuses on the disciplines of computer science, electrical engineering, manufacturing engineering, industrial engineering, chemical engineering, mechanical engineering, civil engineering, engineering management, bioengineering, and biomedical engineering. The scope of the journal also includes developing technologies in mathematics, operations research, technology management, the hard and soft sciences, and technical, social and environmental issues.
Authors: Montoya, Felipe | Cipriano, Aldo | Ramos, María
Article Type: Research Article
Abstract: This paper presents a new identification method for fuzzy models used in nonlinear prediction. The structure and parameters of the fuzzy model are obtained, using input-output data, by minimization of the prediction error. The predictive capacity of the fuzzy model is compared with other linear and non-linear models analyzing an illustrative example. The results show that the new method presents a better behavior.
Citation: Journal of Intelligent & Fuzzy Systems, vol. 10, no. 3-4, pp. 131-137, 2001
Authors: Dassanayake, Palitha | Watanabe, Keigo | Kiguchi, Kazuo | Izumi, Kiyotaka
Article Type: Research Article
Abstract: In this paper, the concept of fuzzy behavior-based control is used to construct a fuzzy generator that generates the desired positions and orientations of a robot manipulator in the Cartesian space. A servo controller is introduced between the fuzzy trajectory generator and the robot. This method is proposed to minimize the drawbacks in extending a fuzzy behavior-based control used previously, while keeping the advantages of the fuzzy behavior-based strategy. For the PUMA robot, the direct extended …version of the control system applied to a three-link manipulator in a previous work, is compared with the proposed method. Two methods are first applied for two behavior groups without any obstacle, in which fuzzy behavioral elements in each method are trained by a genetic algorithm. It is proved that a desired result is not possible within a few numbers of generations for the extended method, whereas the proposed method is able to achieve good results. Moreover, the proposed method is simulated to prove the benefit of the method for three behavior groups with an obstacle. Therefore, it can be concluded that the present approach is suitable in task control of high degree-of-freedom multi-link manipulators while avoiding obstacles for manipulators similar to PUMA robot. Show more
Keywords: PUMA robot manipulator, fuzzy control, behavior-based control system, obstacle avoidance, genetic algorithms
Citation: Journal of Intelligent & Fuzzy Systems, vol. 10, no. 3-4, pp. 139-158, 2001
Authors: Tang, Poi Loon | Poo, Aun-Neow | Silva, de, Clarence W.
Article Type: Research Article
Abstract: This paper studies the development, implementation, and performance of three different types of model-referenced adaptive control with respect to a specific practical application. Conventional model-referenced adaptive control is used as the basis of comparison of the performance of two knowledge-based techniques. Fuzzy logic is used to represent the knowledge base of these techniques, and the compositional rule of inference is used for decision making. In one knowledge-based technique, the parameters of a low-level direct …digital controller are adapted by the inference engine so that the physical system tracks a reference model, which specifies the desired performance. In the other knowledge-based technique, the reference input to the system is adapted to achieve the desired performance, as specified by a reference model. Both analytical and practical details of the development and implementation of the adaptive control techniques are systematically presented. Development of the knowledge base is described. Representative experimental results from the three techniques, as applied to a prototype fish cutting machine are given. The performance of the techniques is evaluated on the basis of the developmental experience and the experimental results. Show more
Citation: Journal of Intelligent & Fuzzy Systems, vol. 10, no. 3-4, pp. 159-183, 2001
Authors: Khaki-Sedigh, Ali | Bavafa-Toosi, Yazdan
Article Type: Research Article
Abstract: New necessary and sufficient conditions for multivariable pole placement (MVPP) and entire eigenstructure assignment (EEA) through static linear multivariable output feedback are established. It is shown that the resultant matrix is of full rank and all design freedoms are retained. The problem of static linear multivariable output feedback control law design is then defined. Based on the EEA concept and sufficiency of the regional pole placement, the design is (re)formulated in terms of a constrained nonlinear …optimization problem. To this end, some decoupling indices for noninteractive performance are defined, their necessary and sufficient conditions are derived and tracker design is addressed. The problem formulation well suits the application of random/intelligent optimization techniques. By way of this approach, optimal robust stability/performance, noninteractive performance, reliability, actuator limitations and low sensitivity in the face of structured or unstructured plant uncertainties are achieved. The effectiveness of the proposed methodology is demonstrated by simulation results using genetic algorithm. Show more
Keywords: EEA, MVPP, static linear output feedback, robust stability/performance, random/intelligent optimization techniques
Citation: Journal of Intelligent & Fuzzy Systems, vol. 10, no. 3-4, pp. 185-195, 2001
Authors: DeKruger, David | Hodge, Jesse | Bezdek, James C. | Keller, James M. | Gader, Paul
Article Type: Research Article
Abstract: We describe an automatic target detection system whose objective is to detect surface-to-air missile launchers and tanks -- small, mobile land targets. The system uses range and intensity images from a Laser Detection and Ranging (LADAR) sensor. Each type of image is filtered and passed to a pair of (different) detectors. Outputs from the four detectors are subsequently filtered with a Choquet fuzzy integral, and then fused with a generalized mean. Finally, blob detections are superposed …on intensity images for visual assessment, and blob windows are compared to ground truth to compute performance statistics. The system is illustrated using images from two scenes available in several volumes of the Joint Advanced Weapons Guidance data; a target board site, and the so-called "Chicken Little" outer compound. The main objective of this article is to document the proposed architecture -- a novel target detection approach based on fuzzy decision theory -- as a proof of concept. We have left detailed comparisons with other approaches, as well as concrete error rate analysis, to another investigation. Show more
Keywords: data fusion, fuzzy systems, image processing, LADAR images, mobile land targets, target detection
Citation: Journal of Intelligent & Fuzzy Systems, vol. 10, no. 3-4, pp. 197-213, 2001
Authors: Trabia, Mohamed B. | Shi, Linda Z.
Article Type: Research Article
Abstract: Fuzzy logic control is already in use due to its computational efficiency and robustness. If a person is sufficiently familiar with a system, intuition can be used as a basis to design a fuzzy controller for it. It may be difficult to accurately describe the behavior for flexible manipulators as their variables are strongly coupled. This paper reviews existing fuzzy logic controllers for flexible manipulators and discusses some of their limitations. It presents an alternative structure …using a distributed fuzzy logic controller that controls angle and link vibrations of flexible manipulators independently. While the rules and structure of the proposed distributed controller offers significant advantages compared to those available in literature, its performance still depends on the membership functions for its input and output variables. Wrong choices of these membership functions may lead to sluggish response, excessive vibration, or instability. The paper presents a novel algorithm, Low Dimensionality Tuning Algorithm (LDTA), for tuning a fuzzy controller by changing the membership functions of its variables using nonlinear programming. LDTA uses only two variables to describe each fuzzy variable to avoid dimensionality problems associated with searching for a solution to problems with large number of variables. The paper also discusses possibilities of simplifying the tuned fuzzy controller. Show more
Keywords: flexible manipulators, fuzzy logic control, tuning, optimization, nonlinear programming
Citation: Journal of Intelligent & Fuzzy Systems, vol. 10, no. 3-4, pp. 215-233, 2001
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