28 research outputs found

    Identification of Distributed Parameter Systems Based on Sensor Networks

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    Tuning Fuzzy PID Controllers

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    Introductory Chapter: Basic Properties of Fuzzy Relations

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    A generic method to construct new customized-shaped haotic systems using the relative motion concept

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    Constructing chaotic systems tailored for each particular real-world application has been a long-term research desideratum. We report a solution for this problem based on the concept of relative motion. We investigate the periodic motion on a closed contour of a coordinate frame in which a chaotic system evolves. By combining these two motions (periodic on a close contour and chaotic) new customized shape trajectories are acquired. We demonstrate that these trajectories obtained in the stationary frame are also chaotic and, moreover, conserve the Lyapunov exponents of the initial chaotic system. Based on this finding we developed an innovative method to construct new chaotic systems with customized shapes, thus fulfilling the requirements of any particular application of chaos

    Matlab Program Library for Modeling and Simulating Control Systems for Electric Drives Based on Fuzzy Logic

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    Fuzzy control of the speed of electric drives is an alternative in the field of the control system. Modeling and simulation of electric drive control systems based on fuzzy logic is an important step in design and development. This chapter provides a complete means of modeling and simulation of fuzzy control systems for DC motors, induction motors, and permanent magnet synchronous motors, made in the Matlab/Simulink program environment, useful for performing complex analyzes. The functioning of the programs is demonstrated by an example of characteristics obtained practically, with a functioning regime often encountered in practice

    Introductory Chapter: Matlab and Simulink Applications

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    Path Planning Algorithm based on Arnold Cat Map for Surveillance UAVs

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    During their task accomplishment, autonomous unmanned aerial vehicles are facing more and more threats coming from both ground and air. In such adversarial environments, with no a priori information about the threats, a flying robot in charge with surveilling a specified 3D sector must perform its tasks by evolving on misleading and unpredictable trajectories to cope with enemy entities. In our view, the chaotic dynamics can be the cornerstone in designing unpredictable paths for such missions, even though this solution was not exploited until now by researchers in the 3D context. This paper addresses the flight path-planning issue for surveilling a given volume in adversarial conditions by proposing a proficient approach that uses the chaotic behaviour exhibited by the 3D Arnold’s cat map. By knowing the exact location of the volume under surveillance before take-off, the flying robot will generate the successive chaotic waypoints only with onboard resources, in an efficient manner. The method is validated by simulation in a realistic scenario using a detailed Simulink model for the X-4 Flyer quadcopter
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