This paper presents a control method for suppressing payload sway caused by operator commanded maneuvers, in rotary boom cranes. The crane configuration studied, consists of a payload mass that swings at the end of a ...
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This paper presents a control method for suppressing payload sway caused by operator commanded maneuvers, in rotary boom cranes. The crane configuration studied, consists of a payload mass that swings at the end of a spherical pendulum, which is attached to a boom capable of hub rotation and elevation. Positioning of the rotary crane is accomplished through the hub and boom angles, and the lift line length. Since the configuration of the crane affects the excitation and response of the lift line, the sway control scheme must account for the varying geometry of the system. Adaptive forward path command filters are employed to remove the components of the command signal which induce oscillation of the lift line. A real-time operator-in-the-loop simulation, is used to demonstrate results for a simultaneous three-axis maneuver.
Proposes a robust visual servoing scheme for robot manipulator with eye-in-hand camera configuration. To perform the tasks defined in the image plane, the velocity Jacobian matrix is used to transform the camera motio...
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ISBN:
(纸本)0780347781
Proposes a robust visual servoing scheme for robot manipulator with eye-in-hand camera configuration. To perform the tasks defined in the image plane, the velocity Jacobian matrix is used to transform the camera motion to the object position change. In addition, a dynamic learning controller is designed to improve the tracking performance of robotic system. The proposed control scheme is implemented for tasks of tracking moving objects and shown to outperform the conventional visual servo system without the dynamic control loop in convergence and robustness to parameter uncertainty, disturbances, low sampling rate, etc.
This paper presents an approach, called fuzzy model based nonlinear fuzzy control, that overcomes position dependent nonlinearity of magnetic bearing systems. We represent the nonlinear magnetic bearing by the Takagi-...
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This paper presents an approach, called fuzzy model based nonlinear fuzzy control, that overcomes position dependent nonlinearity of magnetic bearing systems. We represent the nonlinear magnetic bearing by the Takagi-Sugeno-Kang fuzzy model. Based on such model, nonlinear fuzzy controllers can be derived by means of a systematic synthesis approach. Moreover, the stability analysis of the fuzzy control system can be done efficiently by using linear matrix inequality method. Simulation results demonstrate that the proposed fuzzy controller yields not only maximized stability boundary but also better performance than a single operating point linear controller.
作者：
Malakooti, BKumar, ADepartment of Systems
Control and Industrial Engineering Center for Automation and Intelligent Systems Research and Case Western Reserve University Cleveland OH 44106 United States
This paper presents design-and-development details of a knowledge-based system that solve multi-objective assembly line balancing problems to obtain an optimal assignment of a set of assembly tasks to a sequence of wo...
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This paper presents design-and-development details of a knowledge-based system that solve multi-objective assembly line balancing problems to obtain an optimal assignment of a set of assembly tasks to a sequence of workstations. Assembly line balancing problems arise in high-volume production systems with a significant regularity. The formulation and solutions currently employed by managers and practitioners usually aims at optimizing one objective (e.g., number of work stations or cycle time), thus ignoring the multi-dimensional nature of the overall objectives of the manager. Furthermore, in practice ALBPs are ill-defined and ill-structured, making it difficult to formulate and solve them by mere mathematical approaches. The knowledge-based system multi-objective assembly line balancing approach, presented in this paper, addresses these needs. This paper presents a knowledge-base multi-objective approach to assembly line balancing problems. It demonstrates how such a system can be constructed and how a variety of assembly line balancing methods can be used in a uniform structure to support the decision maker (DM) to formulate, validate the formulation, generate alternatives, and choose the best alternative. Its capabilities include: (1) Elimination of inconsistencies in the problem structure, (2) The use of multi-objective formulation of the problem, (3) A well-designed user-interface, (4) Pursuance of the overall objectives of the manager via a new mechanism, (5) Development of several efficient alternatives, consistent with the user-specified constraint structure, providing the decision maker with a larger number of choices, and, (6) An approach for ranking and prioritizing alternatives consistent with the decision-maker's preferences.
作者：
MALAKOOTI, BYANG, ZDepartment of Systems
Control and Industrial Engineering The Case School of Engineering Center for Automation and Intelligent Systems Research Case Western Reserve University Cleveland OH 44106 United States
In this paper, we develop a new unsupervised learning clustering neural network method for clustering problems in general and for solving machine-part group formation problems in particular. We show that our new appro...
In this paper, we develop a new unsupervised learning clustering neural network method for clustering problems in general and for solving machine-part group formation problems in particular. We show that our new approach solves a very challenging problem in the area of machine-part group formation. A review of machine-part group formation methods and unsupervised learning artificial neural network methods is given. We modify the well-known competitive learning algorithm by using the generalized Euclidean distance, and a momentum term in the weight vector updating equations. The cluster structure can be adjusted by changing the coefficients in the generalized Euclidean distance. The algorithm is flexible and applicable to many practical problems. We also develop a neural network clustering system which can be used to cluster a 0-1 matrix into diagonal blocks. The developed neural network clustering system is independent of the initial matrix and gives clear final clustering results which specify the machines and parts in each group. We use the developed neural network clustering system to solve several machine-part group formation problems, in which the machine-part incidence matrix is to be clustered into a diagonal block structure. An algorithm is developed to consider lower and upper bounds on the number of machines for each cell. The computational results are compared with those from the well-known rank order clustering and directive clustering analysis methods.
作者：
MALAKOOTI, BBDepartment of Systems
Control and Industrial Engineering Center for Automation and Intelligent Systems Research Case Western Reserve University Cleveland OH 44106 United States
One of the problems in the design of multi-station lines is the allocation of different work elements to various workstations. This problem is called Assembly Line Balancing (ALB). The failure of workstations and othe...
One of the problems in the design of multi-station lines is the allocation of different work elements to various workstations. This problem is called Assembly Line Balancing (ALB). The failure of workstations and other unforeseen circumstances can result in unnecessary idling of the production line. In order to improve the production rate of such systems, buffer storage of certain capacities can be allocated between each pair of workstations. In this paper, ALB with buffers is formulated as a Single Criterion Decision Making as well as a Multiple Criteria Decision Making problem. In the single objective problem, the cycle time is given and the optimal number of workstations and buffer sizes is obtained to minimize the total cost. In the Multiple Criteria problem, several criteria (objectives) are defined. These objectives are the number of workstations, their buffer sizes, the cycle time, and the total cost of operation with buffers. We demonstrate how the set of efficient (nondominated) alternatives for the multiple criteria problem can be generated. The paper also describes how the best alternative can be selected through the use of existing interactive multiple criteria methods. Several examples are solved and the results of computational experiments are provided.
This paper outlines some preliminary work on the stability analysis of switched and hybrid systems. The hybrid systems considered are those that combine continuous dynamics, represented by differential or difference e...
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This paper outlines some preliminary work on the stability analysis of switched and hybrid systems. The hybrid systems considered are those that combine continuous dynamics, represented by differential or difference equations, with finite dynamics usually thought of as being a finite automaton. Here, we concentrate on the continuous dynamics and model the finite dynamics as switching among finitely many continuous systems. We introduce multiple Lyapunov functions as a tool for analyzing Lyapunov stability of such "switched systems". We use iterated function systems theory as a tool for Lagrange stability. We also discuss the case where the switched systems are indexed by an arbitrary compact set.< >
作者：
Djukanovic, M.B.Sobajic, D.J.Pao, Y.‐H.Miodrag B. Djukanovic (1959) received his B.S.
M.Sc. and Ph.D. degrees in Electrical Engineering from the University of Belgrade/Yugoslavia in 1982 1985 and 1992 respectively specializing in electric power systems. In 1984 he joined the Electrical Engineering Institute “Nikola Tesla” in Belgrade where he was working on the scientific studies in the field of power systems planning operation and control. In 1985 and 1990 he was appointed as a research scholar at the Royal Institute of Technology Stockholm and Case Western Reserve University Cleveland Ohio. His major in- terests are in the area of power system analysis steady-state and dynamic security and application of neural networks in electric power systems. (Electrical Engineering Institute “Nicola Tesla” ul. Koste Glavinica 8A YU-11000 Belgrad T +3811/2351-619 Fax + 3811/2351-823) Dejan J. Sobajic (1949) received the B.S.E.E. and the M.S.E.E. degrees from the University of Belgrade/Yugoslavia in 1972 and 1976
respectively and the Ph.D. degree from Case Western Reserve University Cleveland Ohio in 1988. At present he is with the Department of Electrical Engineering and Applied Physics Case Western Reserve University Cleveland. He is also the Engineering Manager of A1 WARE Inc. Cleveland. His current research interests include power system operation and control neuralnet systems and adaptive control. He is a member of the IEEE Task Force on Neural-Network Applications in Power Systems and of the IEEE Intelligent Controls Committee. He is the Chairman of the International Neural-Networks Society Special Interest Group on Power Engineering. (Case Western Reserve University Department of Electrial Engineering and Computer Sciences Glennan Building Ohio 44 106 USA T + 1216/421-2380 Fax +1216/368-8776) Yoh-Han Pao (1922) has been a Professor of Electrical Engineering and Computer Science at Case Westem Reserve University (CWRU)
Cleveland Ohio since 1967. He has served as chairman of the University's Electrical Engineering Department
The Transient Energy Function (TEF) method has been intensely investigated over the last decade as a reliable and accurate tool for transient stability assessment of multimachine power systems. In this paper we propos...
This book presents an authoritative collection of contributions reporting on fuzzy logic and decision theory, together with applications and case studies in economics and management science. Dedicated to Professor Jau...
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ISBN:
(数字)9783319699899
ISBN:
(纸本)9783319699882;9783319888750
This book presents an authoritative collection of contributions reporting on fuzzy logic and decision theory, together with applications and case studies in economics and management science. Dedicated to Professor Jaume Gil Aluja in recognition of his pioneering work, the book reports on theories, methods and new challenges, thus offering not only a timely reference guide but also a source of new ideas and inspirations for graduate students and researchers alike.
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