15 research outputs found

    A Singleton Type-1 Fuzzy Logic Controller for On-Line Error Compensation During Robotic Welding

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    During robot welding operations in the manufacturing industry there is a need to modify on-line the welding path due to a mismatch in the position of the components to be welded. These positioning errors are due to multiple factors such as ageing of the components in the conveyor system, clamp fixtures, disturbances, etc. Therefore, robot reprogramming is needed which requires a stop in the production line and consequently an increment in production costs. This article is an extension of [1]a and presents an alternative solution to this problem that involves the use of structured lighting using a low-cost laser beam, a CMOS camera and a Gaussian singleton fuzzy logic controller. To validate the proposed control system, a robotic cell was designed using an industrial KUKA KR16 robot for welding metallic plates. The method was evaluated experimentally under lateral and vertical positioning errors

    Fractional Order Controllers for Back-to-Back Converters

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    A Probabilistic Economic/CO2eq Emissions Dispatch Model: Real Applications

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    Optimal fractional order adaptive controllers for AVR applications

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    This work presents strategies for fractional order model reference adaptive control (FOMRAC) and fractional order proportional-integral-derivative control (FOPID) applied to an automatic voltage regulator (AVR). The paper focuses on tuning the gains and orders of the FOPID controller and the gains and orders adaptive laws of the FOMRAC controller, with the goal of minimizing non-linear and high dimensionality objective functions, using sequential quadratic programming (SQP), particle swarm optimization (PSO), and genetic algorithms (GA). Two models used for AVR have been studied and reported in the literature and are the bases of the three case studies reported in this paper. To analyze the advantages and disadvantages of the proposed MRAC, comparisons are made with the previous results, i.e. with the results obtained by a PID controller and an MRAC controller optimized by GA. We demonstrate through some performance criteria that fractional order controllers optimized by the PSO algorithm improve the behavior of the controlled system, specifically the robustness with respect to model uncertainties, and improvements with respect to the speed convergence of the signals.CONICYT Chile FB0809 FONDECYT 1120453 1150488 CONICYT/FONDECYT 314060
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