Adaptive variable structure control law for a variable speed wind turbine

Presentado en el 13th WSEAS International Conference on Automatic Control, Modelling and Simulation, ACMOS'11

Sliding mode control law for a variable speedwind turbine

Modern wind turbines are designed in order to work in variable speed operations. To perform this task, wind turbines are provided with adjustable speed generators, like the double feed induction generator. One of the main advantage of adjustable speed generators is improving the system efficiency compared to fixed speed generators, because turbine speed can be adjusted as a function of wind speed in order to maximize the output power. However this system requires a suitable speed controller in order to track the optimal reference speed of the wind turbine. In this work, a sliding mode control for variable speed wind turbines is proposed. An integral sliding surface is used, because the integral term avoids the use of the acceleration signal, which reduces the high frequency components in the sliding variable. The proposed design also uses the vector oriented control theory in order to simplify the generator dynamical equations. The stability analysis of the proposed controller has been carried out under wind variations and parameter uncertainties by using the Lyapunov stability theory. Finally simulated results show, on the one hand that the proposed controller provides a high-performance dynamic behavior, and on the other hand that this scheme is robust with respect to parameter uncertainties and wind speed variations, that usually appear in real systems.

An adaptive sliding mode control law for the power maximization of the wind turbine system

POWERENG 2011

Sliding mode control strategy for variable speed wind turbines

EFTA 2009

Variable structure control for maximum wind power extraction

EuroPES 2009

Broadband high-gain optical parametric chirped-pulse amplification near 780 nm with LBO-I near-degenerate near-collinear phase match

Near-degenerative near-collinear phase-match geometry for broadband optical parametric chirped-pulse amplification (OPCPA) at approximate to 780 nm is calculated in comparison with nondegenerate noncollinear phase-match geometry. In an experiment on LBO-I near-degenerate near-collinear OPCPA, high gain with broad gain bandwidth (approximate to 71 nm, FWHM) at approximate to 780 nm is achieved by using an approximate to 390-nm pumping pulse. The stretched broadband chirped signal pulse near 780 nm is amplified to approximate to 412 mu J with a pumping energy of approximate to 15 mJ, and the total gain is > 3.7 X 10(6), which agrees well with the calculation. For a broadband (covering approximate to 100 nm) chirped signal pulse, the theoretical gain bandwidth has been attained experimentally for the first time. (c) 2005 Society of Photo-Optical Instrumentation Engineers.

Latent variable models for neural data analysis

The brain is perhaps the most complex system to have ever been subjected to rigorous scientific investigation. The scale is staggering: over 10^11 neurons, each making an average of 10^3 synapses, with computation occurring on scales ranging from a single dendritic spine, to an entire cortical area. Slowly, we are beginning to acquire experimental tools that can gather the massive amounts of data needed to characterize this system. However, to understand and interpret these data will also require substantial strides in inferential and statistical techniques. This dissertation attempts to meet this need, extending and applying the modern tools of latent variable modeling to problems in neural data analysis.

It is divided into two parts. The first begins with an exposition of the general techniques of latent variable modeling. A new, extremely general, optimization algorithm is proposed - called Relaxation Expectation Maximization (REM) - that may be used to learn the optimal parameter values of arbitrary latent variable models. This algorithm appears to alleviate the common problem of convergence to local, sub-optimal, likelihood maxima. REM leads to a natural framework for model size selection; in combination with standard model selection techniques the quality of fits may be further improved, while the appropriate model size is automatically and efficiently determined. Next, a new latent variable model, the mixture of sparse hidden Markov models, is introduced, and approximate inference and learning algorithms are derived for it. This model is applied in the second part of the thesis.

The second part brings the technology of part I to bear on two important problems in experimental neuroscience. The first is known as spike sorting; this is the problem of separating the spikes from different neurons embedded within an extracellular recording. The dissertation offers the first thorough statistical analysis of this problem, which then yields the first powerful probabilistic solution. The second problem addressed is that of characterizing the distribution of spike trains recorded from the same neuron under identical experimental conditions. A latent variable model is proposed. Inference and learning in this model leads to new principled algorithms for smoothing and clustering of spike data.

Broadband high-gain optical parametric chirped-pulse amplification near 780 nm with LBO-I near-degenerate near-collinear phase match

Near-degenerative near-collinear phase-match geometry for broadband optical parametric chirped-pulse amplification (OPCPA) at approximate to 780 nm is calculated in comparison with nondegenerate noncollinear phase-match geometry. In an experiment on LBO-I near-degenerate near-collinear OPCPA, high gain with broad gain bandwidth (approximate to 71 nm, FWHM) at approximate to 780 nm is achieved by using an approximate to 390-nm pumping pulse. The stretched broadband chirped signal pulse near 780 nm is amplified to approximate to 412 mu J with a pumping energy of approximate to 15 mJ, and the total gain is > 3.7 X 10(6), which agrees well with the calculation. For a broadband (covering approximate to 100 nm) chirped signal pulse, the theoretical gain bandwidth has been attained experimentally for the first time. (c) 2005 Society of Photo-Optical Instrumentation Engineers.

High-conversion-efficiency and broadband tunable femtosecond noncollinear optical parametric amplifier

We build a compact high-conversion-efficiency and broadband tunable noncollinear optical parametric amplifier (OPA) in the infra-red (IR) pumped by a femtosecond Ti:sapphire CPA laser. The OPA consists of an internal seed of white-light continuum generator (WLG) and two noncollinear optical parametric amplifiers. The tunable wavelength range is from 1.2 mu m to 2.4 mu m for both signal and idle pulses. The total OPA efficiency in the last OPA stage reaches about 40% in a wider tunable spectral range (from 1.3 mu m to 1.7 mu m for signal pulse, from 1.5 mu m to 2.0 mu m for idle pulse respectively).