Neural network based control for synchronous generators

In this paper, a Radial Basis Function neural network based AVR is proposed. A control strategy which generates local linear models from a global neural model on-line is used to derive controller feedback gains based on the Generalised Minimum Variance technique. Testing is carried out on a micromachine system which enables evaluation of practical implementation of the scheme. Constraints imposed by gathering training data, computational load, and memory requirements for the training algorithm are addressed.

Determining generators' contribution to loads and line flows & losses considering loop flows

This paper presents a new method for calculating the individual generators' shares in line flows, line losses and loads. The method is described and illustrated on active power flows, but it can be applied in the same way to reactive power flows.

Methods and code for 'classical' age-modelling of radiocarbon sequences.

Age–depth models form the backbone of most palaeoenvironmental studies. However, procedures for constructing chronologies vary between studies, they are usually not explained sufficiently, and some are inadequate for handling calibrated radiocarbon dates. An alternative method based on importance sampling through calibrated dates is proposed. Dedicated R code is presented which works with calibrated radiocarbon as well as other dates, and provides a simple, systematic, transparent, documented and customizable alternative. The code automatically produces age–depth models, enabling exploration of the impacts of different assumptions (e.g., model type, hiatuses, age offsets, outliers, and extrapolation).

Predictive Current Control of Doubly Fed Induction Generators

This paper presents a predictive current control strategy for doubly-fed induction generators (DFIG). The method predicts the DFIG’s rotor current variations in the synchronous reference frame fixed to the stator flux within a fixed sampling period. This is then used to directly calculate the required rotor voltage to eliminate the current errors at the end of the following sampling period. Space vector modulation is used to generate the required switching pulses within the fixed sampling period. The impact of sampling delay on the accuracy of the sampled rotor current is analyzed and detailed compensation methods are proposed to improve the current control accuracy and system stability. Experimental results for a 1.5 kW DFIG system illustrate the effectiveness and robustness of the proposed control strategy during rotor current steps and rotating speed variation. Tests during negative sequence current injection further demonstrate the excellent dynamic performance of the proposed PCC method.

Ultra-lightweight true random number generators

A series of ultra-lightweight digital true random number generators (TRNGs) are presented. These TRNGs are based on the observation that, when a circuit switches from a metastable state to a bi-stable state, the resulting state may be random. Four such circuits with low hardware cost are presented: one uses an XOR gate; one uses a lookup table; one uses a multiplexer and an inverter; and one uses four transistors. The three TRNGs based on the first three circuits are implemented on a field programmable gate array and successfully pass the DIEHARD RNG tests and the National Institute of Standard and Technology (NIST) RNG tests. To the best of the authors' knowledge, the proposed TRNG designs are the most lightweight among existing TRNGs.

Adaptive Code Allocation for Interference Management on the Downlink of DS-CDMA Systems

A new technique based on adaptive code-to-user allocation for interference management on the downlink of BPSK based TDD DS-CDMA systems is presented. The principle of the proposed technique is to exploit the dependency of multiple access interference on the instantaneous symbol values of the active users. The objective is to adaptively allocate the available spreading sequences to users on a symbol-by-symbol basis to optimize the decision variables at the downlink receivers. The presented simulations show an overall system BER performance improvement of more than an order of a magnitude with the proposed technique while the adaptation overhead is kept less than 10% of the available bandwidth.

Two-Stage Transmitter Precoding Based on Data-Driven Code Hopping and Partial Zero Forcing Beamforming for MC-DCMA Communications

This paper proposes a hybrid transmission technique based on adaptive code-to-user allocation and linear precoding for the downlink of phase shift keying (PSK) based multi-carrier code division multiple access (MC-CDMA) systems. The proposed scheme is based on the separation of the instantaneous multiple access interference (MAI) into constructive and destructive components taking into account the dependency on both the channel variation and the instantaneous symbol values of the active users. The first stage of the proposed technique is to adaptively distribute the available spreading sequences to the users on a symbol-by-symbol basis in the form of codehopping with the objective to steer the users' instantaneous crosscorrelations to yield a favourable constructive to destructive MAI ratio. The second stage is to employ a partial transmitter based zero forcing (ZF) scheme specifically designed for the exploitation of constructive MAI. The partial ZF processing decorrelates destructive interferers, while users that interfere constructively remain correlated. This results in a signal to interference-plus-noise ratio (SINR) enhancement without the need for additional power-per-user investment. It will be shown in the results section that significant bit error rate (BER) performance benefits can be achieved with this technique.

Using bar-code technology to capture clinical intervention data in a hospital with a stand-alone pharmacy computer system

The use of barcode technology to capture data on pharmacists' clinical interventions is described.