作者：
Chiodo, E.Menniti, D.Testa, A.Picardi, C.Elio Chiodo (1959) received the degree in Electronics Engineering in 1985
and the Ph.D. degree in Computational Statistics both from the University of Naplefltaly. He is a Researcher at the Department of Electrical Engineering of the University of Naples and a member of the Italian Statistical Society. His areas of interest include probabilistic methods applied to electric power systems analysis. (University of Naples Fedrrico 11. Electrical Engineering Dept.via Claudio 21 1-80125 Naplefltaly T +3981/7683226 Fax+3981/2396897) Daniele Menniti (1958) received the degree in Electrical Engineering from the University of Calabria. Cosenzataly and the Ph.D. degree in Electrical Engineering from the University of NapleslItaly
in 1984 and 1989 respectively. He is a researcher at the Electronic. Computer and Systems Science Department of the University of Calabria. Italy. Hiscurrent research interests concern electric power system analysis real-time control and automation. (University of Calabria Electronic Computer and Systems Science Dep. Arcavacataji Rende (CS). 1-87036 CosenzdItaly T +39984/494707. Fax +39984/4947 13) Alfredo Testa (1950) received the degree in Electrical Engineering from the University of Naples/Italy
in 1975. He is an Associate Professor in Electrical Power Systems at the Department of Electrical Engineering of the University of Naples. He is engaged in researches on electrical power systems reliability and harmonic analysis. (University of Naples Federico 11. Electrical Engineering Dep. via Claudio '2 1 1-80 I25 NapleslItaly T + 39 8 I/7 68 3'2 11. Fax+3981/2396897) Ciro Picardi (1949) received the degree in Electronics Engineering from the University of Naples/Italy
in 1975. He is currently Associate Professor in Process Control at the Department of Electronic Computer and System Science of the University of Calabria. Italy. His current research interests are in the area of electrical drives robotics neural networks and fuzzy control. (University of Calabria Electronic. Compu
An artificial‐neural‐network (ANN) application for steady‐state security evaluation of electrical power systems is presented. Such application is based upon a combined use of a multilayer back‐propagation neural n...
Some applications of the fuzzy logic in the automated robotic deburring are described. Main motivations for these applications are (1) the unpredictability of positional inaccuracies and variations of buff sizes, whic...
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Some applications of the fuzzy logic in the automated robotic deburring are described. Main motivations for these applications are (1) the unpredictability of positional inaccuracies and variations of buff sizes, which are difficult to measure;and (2) the nonlinear and complex behaviour of the deburring process. For a passive deburring strategy the fuzzy logic is used to supervise positional inaccuracies, to directly process disturbed force/torque measurements to avoid time delays, and to adjust controller parameters according to working conditions. For an active deburring strategy a fuzzy man-machine interface is built to take the advantage of utilizing operator's knowledges about buff characteristics, and a fuzzy modeling algorithm is developed to get the input-output relationship of, and to extract qualitative understanding about the deburring process. Some experimental results are presented.
Proportional plus integral plus derivative (PID) control is a well established technique for industrial control and possesses a high flexibility for use in many applications. However the tuning procedure is in many si...
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Proportional plus integral plus derivative (PID) control is a well established technique for industrial control and possesses a high flexibility for use in many applications. However the tuning procedure is in many situations nontrivial, which implies that it is difficult to find the values of the parameters that guarantee a desired closed-loop performance. The purpose of this paper is to present a PID-tuning technique which is based on a combination of two popular methods;namely the pole placement and the parameter optimization methods. The resulting PID self-tuning controller was applied to several simulated examples. This study showed that the controller has an improved performance over the simple pole placement or the simple parameter optimization self-tuning PID controller.
The problem of optimizing the operation of an autonomous manufacturing/supply chain is considered. The chain consists of an upper level manufacturer and a hierarchy of intermediate suppliers/subsuppliers that provide ...
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The problem of optimizing the operation of an autonomous manufacturing/supply chain is considered. The chain consists of an upper level manufacturer and a hierarchy of intermediate suppliers/subsuppliers that provide the required materials. Each subsystem involved in the chain incurs some costs that have to be handled effectively. This paper considers the case of ordering and holding costs. It is assumed that each level in the chain may add some delay in the materials' procurement due to the extra processing taking place or to the time required to supply the corresponding materials. Three possible scenaria are examined. In scenario I, the manufacturer optimizes his own costs and imposes the resulting policy to the (sub)suppliers without any question. In scenario II, all levels of the chain are assumed to cooperate in the sense that their common objective is to minimize the overall operational cost. Finally, in scenario III, each level is optimizing a local cost function in a decentralized way, which may be in conflict with that of the other levels. A partial cooperation is assumed, in the sense that each part minimizes its own costs, plus appropriately weighted deviations of its order profile from a set of calculated reference variables that depend upon the dynamics of the immediate downstream level. A complete numerical example illustrates the above cases.
Flexibility and versatility are two basic requirements for industrial robots used in manufacturing areas. In the present paper, a kinematic transformation for redundant robots between Cartesian and joint coordinates i...
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Flexibility and versatility are two basic requirements for industrial robots used in manufacturing areas. In the present paper, a kinematic transformation for redundant robots between Cartesian and joint coordinates is achieved in the trajectory planner. This problem is treated by taking into account both the dynamics of the system expressed by its Lagrangian and the kinematic constraints of the robot. Given the joint trajectories as above, a control law for joint trajectory tracking is generated here using the Model Based Predictive control (MBPC) approach. The MBPC strategy is based on an explicit robot model to predict the process output over a long-range time period. The postulated control law is constructed such that to fit a desired command acceleration for the servo motors of the robotic system. The actual control law is calculated by minimizing a suitable objective function. A numerical example concerning a robot with one degree of redundancy illustrates the method and shows the excellent performance of the proposed MBPC scheme. The drifting problem that emerges in the resolved motion control of redundant robots is successfully faced.
This paper presents an overview of fuzzy set theory and its application to the analysis and design of fuzzy expert control systems. Starting with a short account of the basic concepts and properties of fuzzy sets and ...
This paper presents an overview of fuzzy set theory and its application to the analysis and design of fuzzy expert control systems. Starting with a short account of the basic concepts and properties of fuzzy sets and fuzzy reasoning, a few fuzzy rule-based controllers, viz. basic single-input single-output fuzzy control, self-organizing fuzzy control, fuzzy PID supervisor, and the fuzzy PID incremental controller, are described in some detail. Then a survey of the theoretical results and applications is provided which gives a good picture of the current status of the field. This survey includes the work on neuro-fuzzy systems, and software systems for the representation and processing of fuzzy information. The paper closes with four application examples which show the type of results that must be expected from fuzzy expert control.
The paper deals with new developments of interpolating memories as the basic element of learning control and with their possible application. It discusses learning control, interpolating memories, characteristic manif...
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The paper deals with new developments of interpolating memories as the basic element of learning control and with their possible application. It discusses learning control, interpolating memories, characteristic manifolds for automotive control, and possible future developments.< >
Five scheduling problems are considered, concerning unit-length independent tasks and uniform machines. New improved optimal algorithms are presented that can solve these problems in at most O(n log n) time, where n i...
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Five scheduling problems are considered, concerning unit-length independent tasks and uniform machines. New improved optimal algorithms are presented that can solve these problems in at most O(n log n) time, where n is the number of tasks. The existing algorithms solve most of these problems in O(n3) time. Proofs of optimality of the present algorithms are included, and simple representative examples are provided that illustrate the type of results obtained.
The paper describes the design of an advanced control system for the PUMA560 industrial robotic manipulator using a high-performance parallel transputer (T805) network. The Transputer Interface Board (TIE) which estab...
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The paper describes the design of an advanced control system for the PUMA560 industrial robotic manipulator using a high-performance parallel transputer (T805) network. The Transputer Interface Board (TIE) which establishes a transputer link to the 6503 microprocessors of the PUMA arm controller, is detailed. Much more flexibility can be achieved with this system. The interface period is now reduced to 1.75 ms (instead of the default 28 ms). controlled by this new system, PUMA moves much more smoothly.< >
The authors present a practical solution to the problem of real-time robot control including the nonlinear dynamic model of the manipulator by employing a parallel processing approach. The parallelism inherent in the ...
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The authors present a practical solution to the problem of real-time robot control including the nonlinear dynamic model of the manipulator by employing a parallel processing approach. The parallelism inherent in the adaptive controllers is exploited to obtain an efficient implementation that reduces the overall computation time to within the limit acceptable for real-time control. The distributed algorithm is implemented on a network of transputers for the six-joint PUMA 560 arm.< >
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