Though there are many strategies to control single-phase uninterruptible power supply (UPS) inverters, they suffer from some drawbacks, the main being complexity. This paper proposes a simple dual-loop controller for the single-phase UPS inverter with the LC filter. The suggested control scheme uses the capacitor current as the feedback signal in the inner current loop. No fictitious phase generation or reference frame transformations are required, and simple proportional gains are employed as both voltage and current regulators. A feedforward of the derivative of the output voltage is also proposed, which significantly improves the performance of the closed loop control system. Then, based on the model of the inverter with the proposed control strategy, a simple and systematic design procedure is presented. Finally, the theoretical achievements are supported by extensive simulations.
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Stimulation of the occipital cortex with transcranial magnetic stimulation (TMs) can interfere with visual processing and may cause masking comparable to visual masking. The effect is most pronounced when the TMS pulse is delivered with stimulus onset asynchronies (SOAs) of 80-100 ms. In a few experiments a second time window of TMS-induced visual masking has been identified with its maximum around an SOA of 40 ms. The existence of two masking windows has been taken as evidence for two distinct visual processes taking place in V1: an early feedforward component and a later re-entrant feedback component. The evidence for the existence of two separate TMS time windows is reviewed. The early time window was not reproducible in all the attempts to characterize TMs masking effects. Interindividual anatomical differences in the location of V1 might contribute to the heterogeneous results.
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DC voltage choppers such as buck, boost, and buck/boost are widely used in electrical power applications. Since these choppers are connected directly between DC source such as solar photovoltaic PV systems or batteries, a disturbance or dc source fluctuations may occur at the input of chopper circuits. Therefore, the control systems must be designed and developed in order to reduce such an increase or decrease in voltage. In this paper, two control strategies have been studied and analyzed to reduce system disturbance and minimize the error resulted from noise. The first strategy uses both feedback and feedforward controllers, in this strategy the controllers are designed based on linearization system. The second strategy uses genetic algorithm to tune the integrated proportional, integral, and differentiator PID feedback controller parameters directly for the nonlinear system. The results show that, the genetic PID controller has better performance than the Feedforward/Feedback controller. The mathematical model of the chopper-controlled system using both strategies and the simulation results are extracted using Matlab/Simulink 2018.
PL
Przerywacze napięcia stałego, takie jak buck, boost i buck/boost, są szeroko stosowane w zastosowaniach elektroenergetycznych. Ponieważ przerywacze te są połączone bezpośrednio między źródłami prądu stałego, takimi jak fotowoltaiczne systemy fotowoltaiczne lub akumulatory, na wejściu obwodów przerywacza mogą wystąpić zakłócenia lub wahania źródła prądu stałego. Dlatego też układy sterowania muszą być projektowane i rozwijane w celu ograniczenia takiego wzrostu lub spadku napięcia. W niniejszym artykule zbadano i przeanalizowano dwie strategie sterowania w celu zmniejszenia zakłóceń systemu i zminimalizowania błędu wynikającego z hałasu. Pierwsza strategia wykorzystuje zarówno regulatory sprzężenia zwrotnego, jak i sprzężenia do przodu, w tej strategii regulatory są projektowane w oparciu o system linearyzacji. Druga strategia wykorzystuje algorytm genetyczny do dostrojenia parametrów zintegrowanego regulatora proporcjonalnego, całkowego i różniczkowego ze sprzężeniem zwrotnym PID bezpośrednio dla systemu nieliniowego. Wyniki pokazują, że genetyczny regulator PID ma lepszą wydajność niż regulator sprzężenia zwrotnego/zwrotnego. Model matematyczny systemu sterowanego chopperem wykorzystujący obie strategie i wyniki symulacji są wyodrębniane za pomocą Matlab/Simulink 2018.
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This paper presents a new approach to robust adaptive control, using fractional order systems as parallel feedforward in the adaptation loop. The problem is that adaptive control systems may diverge when confronted with finite sensor and actuator dynamics, or with parasitic disturbances. One of the classical robust adaptive control solutions to these problems makes use of parallel feedforward and simplified adaptive controllers based on the concept of positive realness. The proposed control scheme is based on the Almost Strictly Positive Realness (ASPR) property of the plant. We show that this condition implies also robust stability in the case of fractional order controllers. An application to Model Reference Adaptive Control (MRAC) with a fractional order adaptation rule is provided with an implementable algorithm. A simulation example of a SISO robust adaptive control system illustrates the advantages of the proposed method in the presence of disturbances and noise.
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