Journal of Intelligent & Fuzzy Systems - Volume 8, issue 1

Authors: Nalley, Michael J. | Trabia, Mohamed B.

Article Type: Research Article

Abstract: Transportation of massive loads using overhead cranes can excite undesirable payload swinging. These oscillations have to be damped before other payload manipulation is done. A fuzzy logic controller moves the overhead crane along a desired path while ensuring that the payload is swing-free at the end of the motion. The control action is divided between displacement and swing controllers to enable tuning the controllers. The fuzzy controller is used with a swing-damped bang-bang motion profile based on the natural frequency of the payload is used that ensures that large amplitudes are not excited. Examples, along with comparisons with a …PD controller, are included. Experimental implementation of the proposed controller is presented. Show more

Citation: Journal of Intelligent and Fuzzy Systems, vol. 8, no. 1, pp. 1-18, 2000

Authors: Senjyu, Tomonobu | Miyazato, Akihiro | Uezato, Katsumi

Article Type: Research Article

Abstract: This article presents the procedure to design a cooperative fuzzy controller applying a genetic algorithm (GA) to improve power system transient stability. A remarkable feature of the method lies in the fact that it can quickly provide a global approximately optimal solution for gains and parameters for the fuzzy controller. In real application problems, trial and error method is extensively used to decide the gains and parameters. However, when the system condition or fault location changes, it is necessary to iterate again to obtain an approximately optimal controller. Moreover, if parameters are changed, it is difficult to achieve good …dynamic response. Hence, a cooperative controller using a fuzzy-genetic system seems a quite efficient means for controlling electric generators. Show more

Citation: Journal of Intelligent and Fuzzy Systems, vol. 8, no. 1, pp. 19-26, 2000

Authors: Zhang, Runtong | Phillis, Yannis A.

Article Type: Research Article

Abstract: This paper considers tandem two-station queueing networks with two types of customers. Firstly, we examine a model where type 1 customers visit station 1 only while type 2 customers visit both stations in sequence. Each station has a single server and unlimited buffer capacity. The service rate in station 1 is variable. The cost depends on the queue length and selected rate. The objective is to dynamically route customers of both types to station 1 and choose the service rate, based on the state of the system, so as to minimize the average cost over an infinite horizon. Secondly, we …examine a system in which station 1 has one server, station 2 two servers, and the buffers have infinite capacity. Two types of customers are first served at station 1 and subsequently proceed to the buffer of a given server according to type in station 2. A reward is earned whenever station 1 accepts a customer and a holding cost is incurred by a customer in buffer at station 2. The objective is to dynamically select the type of customer to be next served at station 1 so as to maximize the average benefit. Customer routing, service rate selection, and flow control are considered simultaneously. We use fuzzy control to solve these complex problems. Simulation shows that the approach is efficient. Show more

Citation: Journal of Intelligent and Fuzzy Systems, vol. 8, no. 1, pp. 27-42, 2000

Authors: de Korvin, A. | Kleyle, R. | Hashemi, S. | Quirchmayr, G.

Article Type: Research Article

Abstract: In this article, we introduce a formal scheduling algorithm that uses redirecting of tasks from a bottlenecked employee while minimizing the completion time for the scheduled jobs. The paper focuses on instances in which a number of employees are to perform several jobs that are divided into various tasks with fuzzy values for their estimated duration times. Generally, efficient job scheduling requires that task and job duration be real values. This allows for precise calculation of time interval and time delay parameters when determining a job's completion time. When the precise values of either one of these parameters is …unknown, not only can the job's completion time not be minimized, but the scheduling of tasks, without regard to the possible bottlenecks, will be haphazard. Show more

Citation: Journal of Intelligent and Fuzzy Systems, vol. 8, no. 1, pp. 43-61, 2000

Authors: Karayiannis, Nicolaos B.

Article Type: Research Article

Abstract: This paper presents the development, testing and evaluation of generalized fuzzy c -means (FCM) algorithms. The proposed algorithms are developed by relaxing the constraints imposed on the membership functions by the axiomatic requirements associated with fuzzy c -partitions. Clustering is formulated as a constrained minimization problem, whose solution depends on the constraints imposed on the membership functions. This minimization problem results in a broad family of Generalized FCM algorithms, which include the FCM algorithm as a special case. The Minimum FCM and Geometric FCM algorithms are also obtained as limiting cases of Generalized FCM algorithms. The proposed formulation …assigns to each feature vector a parameter that can be used to measure the certainty of its assignment to various clusters. These parameters can be used to identify outliers in the feature set. The Generalized FCM algorithms are evaluated and tested by experiments involving the IRIS data set and a two-dimensional vowel data set. Show more

Citation: Journal of Intelligent and Fuzzy Systems, vol. 8, no. 1, pp. 63-81, 2000

Authors: Stylios, Chrysostomos D. | Groumpos, Peter P.

Article Type: Research Article

Abstract: This paper investigates a hybrid methodology that combines fuzzy logic and neural networks, Fuzzy Cognitive Map (FCM), for modeling and controlling Supervisory Control Systems. A mathematical description of Fuzzy Cognitive Maps (FCM) will be presented and new construction methods will be extensively examined. A Fuzzy Cognitive Map will be developed to model and control a process example and the Supervisor-FCM model characteristics will be discussed. There is a going need for more autonomous and intelligent systems, especially in Complex Systems area, the application of Fuzzy Cognitive Maps for modeling the Supervisor may contribute to develop more sophisticated systems.

Citation: Journal of Intelligent and Fuzzy Systems, vol. 8, no. 1, pp. 83-98, 2000