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Charles Krieger's Augustus Clothiers Inc. is one of the stalwarts of Brooklyn's apparel industry. The company, which has been making clothes in the Wyckoff Heights neighborhood for over 100 years, [...]

A realistic problem of an explosion-generated relativistic plasma is talked about with respect to the instabilities developed in such systems. For this, the dispersion equation is derived analytically and solved numerically for typical values of physical quantities. Our calculations reveal that two types of instabilities occur in the said plasma if the dust particles and relativistic effects of ions and electrons are considered. Both types of the instabilities are high-frequency instabilities, which carry growth rates of different magnitudes. In view of the magnitudes, the instability having higher/lower growth rate is called as high-frequency higher/lower growth rate instability. The relativistic effects of ions support the growth of these instabilities, whereas those of electrons suppress the growth of the instabilities. The waves propagating with larger phase velocity are found to grow at higher rates. There exists a critical value of the drift velocity of dust particles, above which another instability starts growing but with significantly lower growth rate.

An explosion-generated-plasma is explored for low and high frequency instabilities by taking into account the drift of all the plasma species together with the dust particles which are charged. The possibility of wave triplet is also discussed based on the solution of dispersion equation and synchronism conditions. High frequency instability (HFI) and low frequency instability (LFI) are found to occur in this system. LFI grows faster with the higher concentration of dust particles, whereas its growth rate goes down if the mass of the dust is higher. The ion and electron temperatures affect its growth in opposite manner and the electron temperature causes this instability to grow. In addition to the instabilities, a simple wave is also observed to propagate, whose velocity is larger for larger wave number, smaller mass of the dust and higher ion temperature.

This work shows that the direct PWM output electric signal, with a duty cycle controlled by light intensity, can be obtained using a circuit containing a saw-tooth voltage generator connected in series with a dc voltage source and a metal (semitransparent gate) oxide semiconductor capacitor (MOS-C).

A new wavelet network structure combining polynomial models with continuous wavelet decomposition is introduced for the identification of a synchronous generator model. The proposed structure uses features of polynomial models and wavelet networks to model non-linearities in the system. In this study, a serial-parallel identification model is applied to system modelling. In this structure, real system outputs are exercised for prediction of the future system outputs, so that stability and approximation of the network are guaranteed. This method is applied to identify the model of a synchronous machine from experimental data collected on a physical machine. The results show that the identified model has very good accuracy and may be valid for a broad range of operating conditions.

This paper is concerned with updating the protective device settings and coordination in an existing developed large industrial oil plant. Problems of short circuit carrying capacity of the system equipment, existence of different protection systems, and outdoor dropout fuses, as well as guidelines for some protective devices, are considered. This paper gives in steps the proper procedure to deal with such problems in a developed industrial plant.

Artificial neural networks (ANNs) have large input-error tolerance ranges and can be used as classifiers. Utilizing this property, a neural network-based detector, which identifies the faulty line directly by taking current and voltage patterns as feature vectors, has been designed. The quality of classification is not dependent on the transmission model, but rather on the net topology, training set, and the choice of learning law. A feed-forward multilayer perceptron, using the Back-Propagation Learning Algorithm, has been used to realize an optimal classifier. The classification quality, by simulating certain faults on the lines, has demonstrated the capability of the proposed approach for distribution power system protection.

To achieve better performance for the controlled system, the rule table of a fuzzy logic based controller is often determined by trial and error. To simplify this time-consuming task, a standardized rule table that can be used in a fuzzy logic control design procedure is developed in this paper. To demonstrate its applicability, the design technique proposed in this paper is employed to design a fuzzy logic based power system stabilizer. Details of the design procedure and results of performance studies with the proposed stabilizer are given in the paper.

A microprocessor-based fault monitor for rotating rectifiers of brushless ac exciters using a pattern-recognition approach is presented in this paper. The features of the frequency spectrum of the voltage waveform induced in a search coil placed in the stator slots of the brushless ac exciter are used in pattern recognition. Based on these features a classifier is designed using the nearest-neighbour rules. A prototype of the microprocessor-based fault monitor has been built. Studies show that the fault monitor can accurately recognize the various classes of faults of the rotating rectifier of the brushless ac exciter.

Most protective relaying schemes use single frequency information from transient current/voltage signals to discriminate faults. In microprocessor based protective relaying, digital filtering is an attractive method of extracting effective frequency components. This paper presents three digital filtering methods based on frequency-spectral analysis for microprocessor based protective relaying: unit-combined filters, assigned zero-points filters and narrow band-pass filters. Test results are also presented.

Power system stability can be improved by proper control of the excitation and governor systems. A stabilizer using multivariable control techniques can be designed to combine and coordinate these two stabilizing contributions. Optimal performance at all operating conditions can be realized by using an adaptive control technique. In this technique the system dynamics for an operating point are identified on line in the calculation of a suitable control. The performance of such a controller was tested on a micro alternator. The prime mover of the micro alternator is a dc machine. This paper describes a method of modeling pre-specified governor-turbine dynamic characteristics on that machine using analog computer techniques. The torque of the dc motor is controlled so that it is proportional to the output of the low power stage by using a PI controller and a voltage chopper.

A high speed directional comparison relay based on the evaluation of the locally measured deviations of the voltage and current from their prefault values is described in this paper. Signal processing techniques are used to damp out the exponentially decaying dc component and high frequency transient components so that the operation of the relay depends on the power frequency components of the voltage and current deviation signals. The direction to a fault is determined by detecting the first transgression of the fault trajectories across threshold boundaries in the deviation plane. Studies on a three phase power system model show that the direction to a fault is determined within a first few milliseconds following the inception of a fault.

This paper describes the application of quasilinearization algorithm and its various modifications to solve the non-linear optimal control problems in power systems. Results obtained by this indirect numerical technique are compared to those obtained by other, direct methods. It is shown that a proposed hybrid approach, in conjunction with the continuation method, can be considered as an effective iterative procedure for most practical problems in power systems.

Power systems are non-linear: the structure and parameters of a network are time varying and cannot be represented accurately by a linear model under all operating conditions. In addition power system disturbances are random in nature, therefore self-tuning controllers are more suitable for power system control than constant parameter linear controllers. The non-minimum phase nature of power systems prohibits the use of simple minimum-variance self-tuning controllers. Generalized minimum variance control can be used to overcome this difficulty. Using multi-input multi-output (MIMO) control, the control efforts of both the excitation and governor systems can be coordinated to improve dynamic stability. The objective of this paper is to present the results obtained from simulation studies in which the MIMO generalized minimum variance control, with square-root least-squares identification and variable forgetting factor, is used to improve the damping of the power system oscillations.

This paper describes the application of quasilinearization algorithm and its various modifications to solve the non-linear optimal control problems in power systems. Results obtained by this indirect numerical technique are compared to those obtained by other, direct methods. It is shown that a proposed hybrid approach, in conjunction with the continuation method, can be considered as an effective iterative procedure for most practical problems in power systems.

A computationally powerful digital signal processor (DSP)-based implementation of adaptive speed control algorithms for a diesel-driven electric generating unit is described in this paper. The complexity of the algorithm and the short control interval required for this application necessitated the use of a DSP. Hardware and software have been designed such that the overall structure of the adaptive controller is similar to the corresponding components of a commercially available PI controller. Illustrative real-time tests with the proposed adaptive controller and the commercial controller illustrate the effectiveness of the adaptive controller.

System identification plays an extremely important role in the self-tuning controller. As the recursive least squares (RLS)identification technique has the advantages of simple calculation and good convergence properties, it is the preferred technique for use in the design of the self-tuning controllers. However, use of RLS identification in a real-time environment does raise some problems such as the speed of parameter convergence, identification going to 'sleep', covariance matrix 'blow up', biased identification, etc. This paper deals with the problems which may arise in the practical use of the RLS identification technique. These issues are the summary of several years' experience of designing self-tuning controllers with RLS identification technique for power system applications. Although some of these issues are difficult to analyse, they are quite effective in dealing with the practical problems.

A real-time digital control environment for research and development of digital controllers A real-time digital control environment, based on Intel iSBC386/21, to implement digital controllers is described. A human-machine interface package developed on a PC AT computer allows the operator to monitor the controller under development. Illustrative results for an adaptive power system stabilizer implemented and tested in this environment are given.

Dual-mode control is applied to the problem of power generation control. The proposed controller is simple in structure and easily implementable. The effect of changes in some important system parameters like self-regulation parameter, turbine time constant and generation rate constraints, on the dynamic performance of the system for reheat and non-reheat type steam turbines is also studied

Power system stabilizers (PSSs) have been widely used in electric power systems to provide extra damping for synchronous generators. An H∞-optimization-based robust control design methodology is presented in this paper for PSS design. The proposed technique takes into account system uncertainties due to incomplete knowledge of the physical parameters, neglected high-frequency dynamics and invalid assumptions made in the model formulation process. It also focuses on power system stabilizer design using a normal design model with an uncertainty description which represents the possible perturbation of a synchronous generator around its nominal operating point. The proposed excitation controller enables the power system to be stable over a wide range of operating conditions. The robust PSS has been tested on a single machine and on a multimachine system. © 1997 John Wiley & Sons, Ltd.

Reliability is one of the fundamental considerations in the design of industrial control equipment. The microprocessor-based hybrid duplex fault-tolerant system (HDS) proposed in this paper has high reliability to meet this demand although its hardware structure is simple. The hardware configuration of HDS and the fault tolerance of this system are described. The switching control strategies in HDS are studied in detail. Disputes between two subsystems are avoided due to the highly modular structure and the efficient fault detection. Reliability estimation methods for this system are also developed. The implementation of fault tolerance in HDS is software intensive. This system is specially designed for industrial process control.

The intelligent self-improving control strategy, containing a controller with variable structure and parameters, a knowledge base and a detector/identifier, has been developed and implemented on a multiprocessor-based system. A digital emulator was built to test the control strategy. The proposed control strategy has been applied to a hydro-turbine governing system. Test results show that the proposed control strategy realized self-improvement for start-up, no-load and load operation.

A sensitivity concept, the sensitivity-of-regulator's effect, is used to analyze the regulator's effect on power system damping. Various types of regulators, including automatic voltage regulators, power system stabilizers and speed governors, are investigated in a one-machine infinite bus system and a 13-machine power system. The results are compared with those obtained by the torque concept.

The application of differential dynamic programming or hybrid quasilinearization technique to the solution of non-linear optimization problems in power systems has encountered the problem of computational instability, particularly in higher order systems. This paper describes the application of a continuation procedure to alleviate this difficulty. Sixth order non-linear systems have been optimized with and without constraints on control variables. Both open-loop and, for the first time, closed-loop systems including both exciter and governor dynamics, are analysed. The studies presented show that this technique is quite effective in obtaining accurate solutions for non-linear boundary-value-problems in power systems.

Integration of capacitor banks (CBs) and distributed generation units (DGs) in distribution systems aims to elevate the system performance. Optimal sizing and placement of CBs and DGs using Spring Search Algorithm (SSA) is proposed. The SSA aims to attain economic, technical, and environmental advantages. Various objective functions: total emissions produced by generation sources, voltage deviation, total electrical energy cost, and power losses are evaluated. SSA simulates Hawk’s Law among weights and springs. In SSA, agents are weights connected to each other by springs. Performance of the proposed method is evaluated on the IEEE 33-bus system. The results indicate superiority of SSA compared with other optimization algorithms.

A case of acute demyelinating encephalomyelitis (ADEM) in a patient with HIV infection is reported. Although the diagnosis of ADEM is based on clinical and radiological findings, the potential for full recovery, with appropriate treatment, is highlighted by this case. A concise review of the subject is given in the discussion.

Patients with multi-system rheumatic conditions may have disease affecting the central and peripheral nervous systems. Early assessment is often helpful in averting the development of serious complications, which in some conditions can be prevented by the prompt institution of treatment. We review the spectrum of neurological disease in patients with a rheumatological diagnosis. The wide variety of associated neurological complications is discussed in the context of specific rheumatic conditions, varying from spinal cord involvement in rheumatoid arthritis, to neuropsychiatric involvement in systemic lupus erythematosus and neurological sequelae in vasculitic disorders. We discuss diagnostic criteria and recommended management options (where available), and describe the role of new tools such as functional brain imaging in the diagnosis and monitoring of disease. We also discuss the potential for development of neurological complications from the use of anti-rheumatic drugs.

Twelve compounds of type (IV) and four compounds of type (VI) are prepared and tested for in vitro antifungal activity.