The paper proposes a new Iterative Feedback Tuning (IFT)-based approach to the optimisation of a class of Takagi-Sugeno PI-fuzzy controllers (PI-FCs). A combination of IFT and the Extended Symmetrical Optimum method i...
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Nowadays production flows are modular, each module in the enterprise being specialized and used to achieve a particular task. In many cases the modules are connected and materials are sequentially processed in each mo...
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Nowadays production flows are modular, each module in the enterprise being specialized and used to achieve a particular task. In many cases the modules are connected and materials are sequentially processed in each module resulting a final, unique product or assembly. One typical such production module is a flexible cell/system using multiple robots. The paper describes a platform which is a software product designed to control and supervise multiple robot-vision controllers using remote connections with a number of Adept.Technology V+ controllers, either located in a local network or via Internet. Additionally the platform allows users to run remote robot vision sessions and to develop and execute robot-vision programs.
The paper suggests a fuzzy control solution for a class of servo systems. Simplified mathematical models of second-order integral type characterize the controlled plants. The design is done using the linear case resul...
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The paper suggests a fuzzy control solution for a class of servo systems. Simplified mathematical models of second-order integral type characterize the controlled plants. The design is done using the linear case results on the basis of the extended symmetrical optimum (ESO) method and Iterative Learning Control and by the transfer of these results to the fuzzy case. The sensitivity analysis of the fuzzy control systems with respect to the parametric variations of controlled plant is performed to enable the design of a class of Mamdani Pi-fuzzy controllers. Digital simulation results and real-time experimental results corresponding to a case study validate the new fuzzy control solution.
The paper presents aspects regarding different possibilities to represent the control problems in networked control systems (NCSs) characterized by variable time delays. The operational computations in linear systems ...
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The paper presents a new design method for low-cost fuzzy control systems used in mechatronics, characterized by second-order dynamics of integral type, controlled by two-degree-of-freedom Pi-fuzzy controllers. The me...
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ISBN:
(纸本)1424408296;97
The paper presents a new design method for low-cost fuzzy control systems used in mechatronics, characterized by second-order dynamics of integral type, controlled by two-degree-of-freedom Pi-fuzzy controllers. The method, referred to as delta domain design, consists of three design steps based on continuous-time linear case design results expressed in terms of the Extended Symmetrical Optimum method applied in the delta domain, followed by the transfer of these results to the fuzzy case. The new design method and Mamdani Pi-fuzzy controllers are validated by real-time experiments in controlling a nonlinear servosystem.
The paper proposes a new Iterative Feedback Tuning (IFT)-based approach to the optimisation of a class of Takagi-Sugeno PI-fuzzy controllers (PI-FCs). A combination of IFT and the Extended Symmetrical Optimum method i...
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The paper proposes a new Iterative Feedback Tuning (IFT)-based approach to the optimisation of a class of Takagi-Sugeno PI-fuzzy controllers (PI-FCs). A combination of IFT and the Extended Symmetrical Optimum method is used for the design of PI-FCs for servo systems with controlled plants characterized by second-order integral type models. Since the gradient in the optimisation approach is estimation, the results are quasi-optimal. Experimental results for a PI-fuzzy controlled servo system validate the proposed IFT-based design.
作者：
Radu-Emil PrecupStefan PreitlAxel GräserMiroslav Mihajlov“Politehnica” University of Timisoara
Dept. of Automation and Applied Informatics Bd. V. Parvan 2 300223 Timisoara Romania Phone: +40-2564032-26 -24 Fax: +40-2564032-14 E-mail: rprecup@aut.utt.ro spreitl@aut.utt.ro Bremen University
Institute of Automation FBI /NW1 Otto-Hahn-Allee 1 28359 Bremen Germany Phone: +49-421-218-7326 -3217 Fax: +49-421-218-4596 E-mail: ag@iat.uni-bremen.de mihajlov@iat.uni-bremen.de
The paper suggests an Iterative Feedback Tuning (IFT)-based approach in optimization problems ensuring both controller and reference model tuning. The cost function is introduced and Newton's method in terms of Ga...
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The paper suggests an Iterative Feedback Tuning (IFT)-based approach in optimization problems ensuring both controller and reference model tuning. The cost function is introduced and Newton's method in terms of Gauss-Newton approximation is applied in the minimization of the cost function. The new IFT approach is derived using matrix notation. The particular case of PI controllers for servo systems is considered where the controlled plants are characterized by second-order integral type models. For these control systems the combination between IFT and Extended Symmetrical Optimum method is successful. Real-time experimental results for a PI-controlled servo system validate the IFT approach.
Intelligent image processing blurs the distinction between Guidance Vision for Robots (GVR) and Automated Visual Inspection (AVI) applications. The paper presents AI techniques for interactive learning of scene-object...
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The paper proposes original low cost fuzzy control solutions for controlling servo systems in mechatronic systems. In this situation the controlled plants can be characterized well by simplified mathematical models of...
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Intelligent image processing blurs the distinction between Guidance Vision for Robots (GVR) and Automated Visual Inspection (AVI) applications. The paper presents AI techniques for interactive learning of scene-object...
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Intelligent image processing blurs the distinction between Guidance Vision for Robots (GVR) and Automated Visual Inspection (AVI) applications. The paper presents AI techniques for interactive learning of scene-object models by feature descriptions of part flows. Robot grippers are modelled by fingerprints for ***collision-free part access. The parameters of the vision models are remotely created by a Server application which accepts simultaneous connections over LAN/Internet with multiple Clients – executing on IBM PC robot terminals integrated in flexible, networked manufacturing structures. Experimental results are reported for cluster and pattern construction for part recognition.
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