Journal of Intelligent & Fuzzy Systems - Volume 17, issue 5

Authors: Kim, Dongwon | Park, Gwi-Tae

Article Type: Research Article

Abstract: In this paper, a hybrid fuzzy modeling technique is described for an unknown system with a given set of numerical data. Nonlinear systems are difficult to model by conventional fuzzy systems because of problems such as the conflict between overfitting and underfitting, and low reliability. To overcome these problems, a great number of fuzzy rules and very complicated learning algorithms must be used. We propose the hybrid fuzzy modeling technique, which the combination of the fuzzy …system and self-organizing approximators (polynomial neural networks: PNN). Fuzzy systems have been used successfully for imprecise data or not well-defined concepts. PNN is an analysis technique used to identify nonlinear relations between system inputs and outputs and build hierarchical polynomial regressions of required complexity. Comparative studies of the proposed approach are presented for both Box-Jenkin data identification system and three-input nonlinear function to show the performance. The proposed method was efficient and much more accurate than previous other models because it used fewer fuzzy rules and had better generalization ability. Show more

Keywords: Hybrid fuzzy model, fuzzy systems, self-organizing approximator, nonlinear system modeling, overfitting and underfitting

Citation: Journal of Intelligent & Fuzzy Systems, vol. 17, no. 5, pp. 417-430, 2006

Authors: Song, Jialin | Tizhoosh, H.R.

Article Type: Research Article

Abstract: A fuzzy anisotropic diffusion algorithm based on edge detection and noise estimation is proposed for image denoising and edge enhancement. The edginess and noisiness fuzzy membership values are calculated with the edge detector and noise deviation of center pixel from the neighboring average, respectively. The employed edge detector provides more accurate estimation of edges and is less sensitive to noise than the gradient operator in anisotropic diffusion. Taking noise into account ensures that the diffusion process …works well regardless of the type of noise degradation, and effectively reduces the number of iterations. We demonstrate how the rather complicated edge detection and noise estimation can be put together through fuzzy inference and embedded into anisotropic diffusion to provide better control on the diffusion processing. Quantitative and qualitative evaluations demonstrate superior performance of the proposed fuzzy approach while processing images with additive and multiplicative noise. Show more

Citation: Journal of Intelligent & Fuzzy Systems, vol. 17, no. 5, pp. 431-442, 2006

Authors: Son, Changman

Article Type: Research Article

Abstract: Using the control of robotic part assembly tasks, consisting of a macro and a micro-assembly, as an example, a systematic way, not a heuristic one, that can determine an optimal membership function and rulebase among feasible fuzzy membership functions and rulebases which can execute the part assembly tasks successfully, based on a fuzzy entropy is introduced. In a macro-assembly, a part is brought from an initial position to an assembly hole or a receptacle (target or …destination) for a purpose of a part mating in a partially unstructured environment that includes unknown obstacles. Then, in a micro-assembly, the part is placed at a position that is ready to mate successfully with the target without jamming. An entropy function, which is a useful measure of the variability and the information in terms of uncertainty, is introduced to measure its overall performance of a task execution related to the part assembly tasks. Three different types of membership functions are applied to two different sets of fuzzy rulebases for a macro and a micro-assembly to show a robustness. The membership function that generates the lowest degree of uncertainty in the part assembly procedure is chosen as an optimal one. The same criterion is applied to determine an optimal fuzzy rulebase. In order to address the uncertainty associated with the part assembly procedure, a fuzzy theory, that is well-suited to the management of uncertainty, is introduced. The degree of uncertainty associated with the part assembly procedure is used as an optimality criterion, or cost function, e.g. minimum fuzzy entropy, for a specific task execution. The results show the effectiveness of the proposed approach. The proposed methodology is not only a useful tool in choosing an optimal membership function and fuzzy rulebase but applicable to a wide range of robotic tasks including controlling of mobile based robots around obstacles, and a part mating and pick and place operations. Show more

Keywords: Systematic methodology, optimal membership function/fuzzy rulebase, part macro/micro-assembly (part-bringing/mating), robustness, fuzzy entropy, uncertainty (= fuzziness), machine reasoning, inferencing, and decision-making, and vision sensor

Citation: Journal of Intelligent & Fuzzy Systems, vol. 17, no. 5, pp. 443-456, 2006

Authors: Mansoori, Eghbal G. | Eghbali, Hassan J.

Article Type: Research Article

Abstract: Edge detection is one of the most important preprocessing operations needed for detection and extraction of objects in scene, especially in the field of machine vision. Since the nature of image data is indeterminate and the edges of an object in an image are not very clear and occasionally transition from scene pixels to object ones occurs moderately, so fuzzy reasoning is able to extract useful attributes from approximate and incomplete data and improve the task …of edge detection. In this paper a heuristic fuzzy rule-based algorithm for detecting the edge patterns in an image is presented. The Heuristic Fuzzy Edge Detector, HFED, uses three features from a 3 by 3 window size for each central pixel surrounded by its eight neighbors, to classify that pixel as part of an edge or as non-edge patterns. The fuzzy inference system use these features for classification and because of interpolative operation of fuzzy reasoning, the results are comparable with other well-known edge detector, especially in degraded images. Show more

Keywords: Edge detection, block deviation, pixel discrepancy norm, local degree of edge, fuzzy rule-based classification system

Citation: Journal of Intelligent & Fuzzy Systems, vol. 17, no. 5, pp. 457-469, 2006

Authors: Zhu, Yuanguo | Ji, Xiaoyu

Article Type: Research Article

Abstract: Based on the expected value of a fuzzy variable, the expected value of function of a fuzzy variable is studied. A fuzzy expected value model is solved by an intelligent algorithm mixed integral sum approximation and genetic algorithm. As applications of results derived, a merchandize apportionment problem is investigated.

Keywords: Fuzzy variable, expected value, fuzzy expected value model, intelligent algorithm

Citation: Journal of Intelligent & Fuzzy Systems, vol. 17, no. 5, pp. 471-478, 2006

Authors: Lin, C.M. | Chen, C.H. | Lee, Y.F.

Article Type: Research Article

Abstract: This paper develops a design method of recurrent fuzzy neural network (RFNN) based adaptive hybrid control for multi-input multi-output (MIMO) linearized dynamic systems. This hybrid control system consists a feedback controller and an adaptive RFNN controller. The feedback controller is used as a basic stabilizing controller to stabilize the nominal system and the adaptive RFNN controller is used to deal with unknown part of system dynamics. The adaptive laws of RFNN are derived based on the …Lyapunov function so that the stability of the system can be guaranteed. Finally, the proposed control system is applied to an F-16 flight control system. Simulation results demonstrate that the developed control system can achieve favorable tracking performance even with some failure of the flight control system. Show more

Keywords: Adaptive control, recurrent fuzzy neural network, F-16 aircraft

Citation: Journal of Intelligent & Fuzzy Systems, vol. 17, no. 5, pp. 479-491, 2006

Authors: Xu, Min | Li, Ning | Li, Shao-Yuan

Article Type: Research Article

Abstract: This paper presents a novel fuzzy control strategy for a wide-range of operating condition system. Considering system error and the change rate of system error, a PI type fuzzy controller is obtained. On the basis of the novel fuzzy controller, a receding horizon optimization method to tune the fuzzy controller parameters is given through minimizing the generalized predictive control criterion. Therefore, the PI-type fuzzy controller has the capability to adapt a wide-range of operating condition. Then, …a simple and sufficient bound condition of input and output variable is achieved under the Lyapunov theory with brief analysis. Simulation results demonstrate the better performance of this novel fuzzy control scheme. Show more

Citation: Journal of Intelligent & Fuzzy Systems, vol. 17, no. 5, pp. 493-501, 2006

Authors: Corsini, Paolo | Marcelloni, Francesco

Article Type: Research Article

Abstract: Determining profiles of web portal typical users can be extremely useful, for instance, to personalize the web portal, to provide customized guide and to send tailored advertisements. In this work, we present a system to produce a small number of user profiles from the web access log and to associate each user with one of these profiles. The system is based on a version of the fuzzy C-means (FCM) algorithm which uses the cosine distance rather …than the classical Euclidean distance. After filtering the access log, for instance, by removing occasional and undecided users, the FCM algorithm clusters the users into groups characterized by a set of common interests and represented by a prototype, which defines the profile of the group typical member. To attest the validity of these profiles, we extract a set of association rules from the raw access log data by applying the well-known A-priori algorithm and show how the profiles are a concise representation of the association rules. Finally, to test the effectiveness of the overall fuzzy system, we illustrate how the profiles determined by the FCM algorithm from access log data collected along a period of 30 days allow classifying approximately 93% of the users defined by access log data collected during subsequent 30 days. Show more

Keywords: Web mining, user profile, fuzzy c-means, association rules

Citation: Journal of Intelligent & Fuzzy Systems, vol. 17, no. 5, pp. 503-516, 2006

Authors: Mendonça, L.F. | Sousa, J.M.C. | Kaymak, U. | Sá da Costa, J.M.G.

Article Type: Research Article

Abstract: Model predictive control (MPC) is a well-known control technique, which has been applied to complex and nonlinear processes. Fuzzy predictive control incorporates fuzzy goals and constraints in MPC, by combining predictive control with fuzzy decision making. In this paper, we propose the integration of weighted criteria in fuzzy predictive control, where the decision-maker can specify the preference for different goals and constraints by using weight factors for each criterion. A new heuristic is proposed to …select suitable weight factors that satisfy the overall control objective. In this context, a method to extend the t-norms to the weighted case is also discussed. The weighted approach is validated using a multivariable process: the simulation of a gantry crane system, which shows clear improvements in the control performance when using the weighted fuzzy predictive control approach. Show more

Keywords: Fuzzy predictive control, weighted criteria, multivariable control, fuzzy decision making, container gantry crane

Citation: Journal of Intelligent & Fuzzy Systems, vol. 17, no. 5, pp. 517-532, 2006

Authors: Shabaninia, Faridoon | Khorshidi, Reza

Article Type: Research Article

Abstract: We present an algorithm of supervisory control with fuzzy logic and adaptive control of a low earth orbit (LEO) satellite with single-spin stabilization. The error generated by an adaptive control signal can be computed with only the reference dynamics of the model and the damping. A fuzzy logic algorithm is presented that acts as a supervisory control and estimates the changes of the parameters and applies the necessary signals to avoid any unsuitability in the system. …The results of simulation have shown that position control is performed within an acceptable tolerance by using the suggested algorithm, which includes three closed-loop systems and unknown parameters of the system [1,2,3]. Show more

Keywords: Parameter estimation, adaptive control, fuzzy control, supervisory control, reference model, covariance matrix, low earth orbit (LEO)

Citation: Journal of Intelligent & Fuzzy Systems, vol. 17, no. 5, pp. 533-540, 2006