Control of Ripple Eliminators to Improve the Power Quality of DC Systems and Reduce the Usage of Electrolytic Capacitors

The problem of voltage/current ripples has become a primary power quality issue for DC systems, which could seriously degrade the performance on both the source side and the load side and lead to reliability concerns. In this paper, a single-phase PWM-controlled rectifier is taken as an example to investigate how active control strategies can improve the power quality of DC systems, reduce voltage ripples and, at the same time, reduce the usage of electrolytic capacitors. The concept of ripple eliminators recently proposed in the literature is further developed and the ratio of capacitance reduction is quantified. With such ripple eliminators, this power quality problem is formulated as a control problem to actively divert the ripple current on the DC bus. The main focus of this paper is to investigate how advanced control strategies could improve the performance of ripple eliminators. An advanced controller on the basis of the repetitive control is proposed for one possible implementation of ripple eliminators in the continuous current mode (CCM). Experimental results are presented to verify the effectiveness of the strategy with comparison to another ripple eliminator operated in the discontinuous current mode (DCM). It has been shown that the proposed instantaneous ripple-current diversion in CCM leads to a nearly fourfold improvement of performance

Bounded Integral Control of Input-to-State Practically Stable Non-linear Systems to Guarantee Closed-loop Stability

A fundamental problem in control systems theory is that stability is not always guaranteed for a closed-loop system even if the plant is open-loop stable. With the only knowledge of the input-to-state (practical) stability (ISpS) of the plant, in this note, a bounded integral controller (BIC) is proposed which generates a bounded control output independently from the plant parameters and states and guarantees closed-loop system stability in the sense of boundedness. When a given bound is required for the control output, an analytic selection of the BIC parameters is proposed and its performance is investigated using Lyapunov methods, extending the result for locally ISpS plant systems. Additionally, it is shown that the BIC can replace the traditional integral controller (IC) and guarantee asymptotic stability of the desired equilibrium point under certain conditions, with a guaranteed bound for the solution of the closed-loop system. Simulation results of a dc/dc buck-boost power converter system are provided to compare the BIC with the IC operation

Improved Synchronverters with Bounded Frequency and Voltage for Smart Grid Integration

Synchronverters are grid-friendly inverters that mimic conventional synchronous generators and play an important role in integrating different types of renewable energy sources, electric vehicles, energy storage systems, etc., to the smart grid. In this paper, an improved synchronverter is proposed to make sure that its frequency and voltage always stay within given ranges, while maintaining the function of the original synchronverter. Furthermore, the stability region characterised by the system parameters is analytically obtained, which guarantees that the improved synchronverter is always stable and converges to a unique equilibrium as long as the power exchanged at the terminal is kept within this area. Extensive OPAL-RT real-time simulation results are presented for the improved and the original self-synchronised synchronverters connected to a stiff grid and for the case when two improved synchronverters are connected to the same bus with one operating as a weak grid, to verify the theoretical development

Prediction of solar particle events with SRAM-based soft error rate monitor and supervised machine learning

This work introduces an embedded approach for the prediction of Solar Particle Events (SPEs) in space applications by combining the real-time Soft Error Rate (SER) measurement with SRAM-based detector and the offline trained machine learning model. The proposed approach is intended for the self-adaptive fault-tolerant multiprocessing systems employed in space applications. With respect to the state-of-the-art, our solution allows for predicting the SER 1 h in advance and fine-grained hourly tracking of SER variations during SPEs as well as under normal conditions. Therefore, the target system can activate the appropriate mechanisms for radiation hardening before the onset of high radiation levels. Based on the comparison of five different machine learning algorithms trained with the public space flux database, the preliminary results indicate that the best prediction accuracy is achieved with the recurrent neural network (RNN) with long short-term memory (LSTM). © 2020 The Author

Robust Compensation of Delay and Diffusive Actuator Dynamics Without Distributed Feedback

[EN] This paper deals with robust observer-based output-feedback stabilization of systems whose actuator dynamics can be described in terms of partial differential equations (PDEs). More specifically, delay dynamics (first-order hyperbolic PDE) and diffusive dynamics (parabolic PDE) are considered. The proposed controllers have a PDE observer-based structure. The main novelty is that stabilization for an arbitrarily large delay or diffusion domain length is achieved, while distributed integral terms in the control law are avoided. The exponential stability of the closed loop in both cases is proved using Lyapunov functionals, even in the presence of small uncertainties in the time delay or the diffusion coefficient. The feasibility of this approach is illustrated in simulations using a second-order plant with an exponentially unstable mode.This work was supported in part by Project TIN2017-86520-C3-1-R, Ministerio de Economia y Competitividad, in part by the 16/17 UPV Mobility Award, and in part by the FPI-UPV 2014 Ph.D. Grant, Universitat Politecnica de Valencia, Spain.Sanz Diaz, R.; García Gil, PJ.; Krstic, M. (2019). Robust Compensation of Delay and Diffusive Actuator Dynamics Without Distributed Feedback. IEEE Transactions on Automatic Control. 64(9):3663-3675. https://doi.org/10.1109/TAC.2018.2887148S3663367564

Concentrations of heavy metals in soil and leaves of plant species Paulownia elongata S.Y.Hu and Paulownia fortunei Hemsl

This paper sums up the results of the research on heavy metals contents (Pb, Ni, Fe, Zn and Mn) in soil and leaves of the plant species, Paulownia elongata S.Y. Hu and Paulownia fortunei Hemsl. at the plantation established on the eutric brown soil in Banat (Vojvodina). The plantation, which served asthe control field is at the municipality of Bela Crkva, far away from the main traffic lines. Concentrations of analyzed heavy metals in the leaves of the tree species, Paulownia growing in urban and suburban conditions were compared with the concentration of polluters in the leaves of the tree species, P. elongata and P. fortunei in the experimental field in Bela Crkva

The Magellanic Stream and the density of coronal gas in the Galactic halo

The properties of the Magellanic Stream constrain the density of coronal gas in the distant Galactic halo. We show that motion through ambient gas can strongly heat Stream clouds, driving mass loss and causing evaporation. If the ambient gas density is too high, then evaporation occurs on unreasonably short timescales. Since heating dominates drag, tidal stripping appears to be responsible for producing the Stream. Requiring the survival of the cloud MS IV for 500 Myr sets an upper limit on the halo gas density n_H< 10^{-5} cm^{-3} at 50 kpc, roughly a factor of 10 lower than that estimated from the drag model of Moore & Davis (1994). Implications for models of the evolution of gas in galaxy halos are discussed.Comment: 4 pages, 1 figure, in press, ApJ

Adaptive Tuning of Feedback Gain in Time-Delayed Feedback Control

We demonstrate that time-delayed feedback control can be improved by adaptively tuning the feedback gain. This adaptive controller is applied to the stabilization of an unstable fixed point and an unstable periodic orbit embedded in a chaotic attractor. The adaptation algorithm is constructed using the speed-gradient method of control theory. Our computer simulations show that the adaptation algorithm can find an appropriate value of the feedback gain for single and multiple delays. Furthermore, we show that our method is robust to noise and different initial conditions.Comment: 7 pages, 6 figure