Nonlinear predictive control for a NNARX hydro plant model

A neural network (NN)-based nonlinear predictive control (NPC) is described for control of turbine power with variation in gate position. The studied plant includes the tunnel, surge tank and penstock effect dynamics. Multilayer perceptron neural network is chosen to represent a neural network nonlinear autoregressive with exogenous signal model of hydro power plant. With the said NN model configuration, quasi-Newton and Levenberg–Marquardt iterative optimization algorithms are applied in order to determine optimal predictive control parameters. The controlled response is simulated on different amplitude step function and trapezoidal shape reference signal. The study also discusses comparison with an approximate predictive control approach, being linearized around operating points. It is shown that NPC strategy gives impressive results in comparison to the approximated one.     

Fighting Bugs: Remove, Retry, Replicate, and Rejuvenate

Even if software developers don't fully understand the faults or know their location in the code, software rejuvenation can help avoid failures in the presence of aging-related bugs. This is good news because reproducing and isolating an aging-related bug can be quite involved, similar to other Mandelbugs. Moreover, monitoring for signs of software aging can even help detect software faults that were missed during the development and testing phases. If, on the other hand, a developer can detect a specific aging-related bug in the code, fixing it and distributing a software update might be worthwhile. In the case of the Patriot missile-defense system, a modified version of the software was indeed prepared and deployed to users. It arrived at Dhahran on 26 February 1991- a day after the fatal incident     

SOFT COMPUTING TECHNIQUES FOR PREDICTION OF BOILING HEAT TRANSFER COEFFICIENT OF LIQUIDS ON COPPER-COATED TUBES

In this article pool boiling heat transfer coefficient (HTC) of liquids (isopropanol, methanol, and distilled water) on copper-coated heating tubes over a wide range of pressure conditions is computed experimentally. The objective is to find the applicability of soft computing techniques, swarm-intelligence based neural network, and adaptive fuzzy models in the prediction of boiling HTC. The results are compared with those computed experimentally. The performance of models for prediction of HTC is analyzed in terms of root mean square of prediction error. The minimum/maximum value obtained by zero-order fuzzy model with six membership function is 0.0023/3.4383 among all the liquids considered. The model is found to predict HTC with a maximum error of ±0.5% for boiling of liquids over all the coated tubes with pressure varying from atmospheric to subatmospheric levels. The study shows an excellent agreement between the experimental and predicted data.     

On the dynamic loading of gear teeth as affected by journal motion in a hydrodynamic bearing-rotor-gear pair system

The paper is an attempt to include the effect of journal motion and the oil film forces on the determination of dynamic gear tooth loading in a hydrodynamic bearing-rotor-gear pair system. A mathematical model has been developed which relates dynamic loads on the teeth of an involute spur gear pair to the instantaneous state of the pinion journal centre in the oil film space and various bearing parameters. The direction of instantaneous line of action is determined from kinematic considerations. effects of both the full-film (360 degrees) and the cavitated π-film models of the journal bearing are used to arrive at the aforementioned relationships. Dynamic loads on gear teeth as well as on bearing film have been calculated when the journal traces certain specified paths in the clearance space. Some of the results emphasize the importance of coupling gear analysis with bearing analysis.     

A dynamic simulation of a nuclear power station for control analysis

Nonlinear simulation has been applied to the control study of an organic-cooled Canadian CANDU reactor. The study was carried out as an integral part of an overall design study. The control characteristics of the power plant were studied for reactor start-up, pump failures, reactor trips and various rates of power change. The response of the power plant to these disturbances is discussed.     

Wind induced damage observations and their implications for design practice

A synopsis of wind induced damage observations is presented, along with a commentary on damage documentation experiences and remarks on design implications. The paper concludes with a discussion on problem areas concerning wind effects and the performance of buildings in windstorms.     

Solar assisted biogas plant IIA: Experimental validation of the mathematical models for floating drum type biogas plant

The theoretical predictions presented in an earlier paper for the performance of solar assisted biogas plants are compared with experimental measurements made on four separate systems. There is good agreement between the results and the theoretical predictions.     

Interpolation of images using discrete wavelet transform to simulate image resizing as in human vision

This paper presents discrete wavelet transform (DWT) and its inverse (IDWT) with Haar wavelets as tools to compute the variable size interpolated versions of an image at optimum computational load. As a human observer moves closer to or farther from a scene, the retinal image of the scene zooms in or out, respectively. This zooming in or out can be modeled using variable scale interpolation. The paper proposes a novel way of applying DWT and IDWT in a piecewise manner by non-uniform down- or up-sampling of the images to achieve partially sampled versions of the images. The partially sampled versions are then aggregated to achieve the final variable scale interpolated images. The non-uniform down- or up-sampling here is a function of the required scale of interpolation. Appropriate zero padding is used to make the images suitable for the required non-uniform sampling and the subsequent interpolation to the required scale. The concept of zeroeth level DWT is introduced here, which works as the basis for interpolating the images to achieve bigger size than the original one. The main emphasis here is on the computation of variable size images at less computational load, without compromise of quality of images. The interpolated images to different sizes and the reconstructed images are benchmarked using the statistical parameters and visual comparison. It has been found that the proposed approach performs better as compared to bilinear and bicubic interpolation techniques.