This paper describes an interactive tool focused on teaching and learning basic concepts on multivariable controlsystems. Most industrial processes are represented by multivariable systems and thus the teaching and l...
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This paper describes an interactive tool focused on teaching and learning basic concepts on multivariable controlsystems. Most industrial processes are represented by multivariable systems and thus the teaching and learning of basic concepts on multivariable control is a key factor in control engineering education. In this sense, the interactive tool presented in this paper is aimed to introduce basic ideas on multivariable controlsystems mainly focused on interaction and pairing concepts.
This paper presents a manipulation and measurement aid for tasks carried out in micro-nano environments operating with scanning AFM. In teleoperated manipulation or measurement over a given point of the target, where ...
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In this paper we study the tracking problem for the class of non-holonomic systems in chained form. In particular, with as outputs the first and last state component of the chained form, we suggest a solution for the ...
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An approach to the solution of the adaptive control for nonlinear systems with unknown parameters is presented by using the theory of nonlinear H∞ disturbance attenuation control. The two-level control law is present...
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ISBN:
(纸本)9783952426906
An approach to the solution of the adaptive control for nonlinear systems with unknown parameters is presented by using the theory of nonlinear H∞ disturbance attenuation control. The two-level control law is presented. It is shown that the adaptive control law is related to the existence of the solution of a new form of Hamilton-Jacobi-Isaacs inequlity. The stability of the closed loop system can be guranteed when the update rate of the unknown parameter is equal to the requested update law. The asymptotical stability of the closed loop system can be guranteed when the estimators of the uncertain parameters convergence to the true value.
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...
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