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.     

Experimental investigation of impact of diesel particulate filter on smoke and NO<Subscript>x</Subscript> emissions of a Euro-I compression ignition engine with active and off-board regeneration

Old engines (Euro III or earlier) produce more emissions, and it will be difficult to entirely stop their usage especially in developing and under-developed nations; hence, it is desired that appropriate emission reduction technologies are tested on such engines to analyze their feasibility and economical acceptability. While most such studies have been conducted on constant speed stationary engines and modern engines, this study tried to analyze the effectiveness of an uncoated wall-flow type ceramic diesel particulate filter on a Euro-I, water-cooled, direct injection, variable speed, compression ignition engine in a laboratory set-up in India. Also, this study focused on diesel particulate filter regeneration by two methods: active regeneration by diesel injection in the particulate filter using an electronic control unit and off-board regeneration by taking out and heating the diesel particulate filter in an electrical resistance furnace at 650 °C for 10 h. The results, in the form of smoke emission, NO_x emission and engine performance, obtained using both the regeneration methods were analyzed, and conclusions were drawn. It was found that using diesel particulate filter, particulate matter emissions (smoke) were almost entirely eliminated. It was also found that off-board regeneration had numerous advantages compared to active regeneration. Since a furnace would be needed for off-board regeneration, an exchange process for diesel particulate filter is suggested.     

Polyacrylonitrile solution homogeneity study by dynamic shear rheology and the effect on the carbon fiber tensile strength

Poly(acrylonitrile‐co‐methacrylic acid) (PAN‐co‐MAA)/N,N‐dimethylformamide (DMF) solutions were prepared and dynamic shear rheology of these solutions were investigated. With increasing stirring time up to 72 h at 70°C, the polymer solution became less elastic (more liquid‐like) with a ～60% reduction in the zero‐shear viscosity. Relaxation spectra of the PAN‐co‐MAA/DMF solutions yield a decrease in relaxation time (disentanglement time, τ_d), corresponding to an about 8% decrease in viscosity average molecular weight. The log‐log plot of G′ (storage modulus) versus G″ (loss modulus) exhibited an increase in slope as a function of stirring time, suggesting that the molecular level solution homogeneity increased. In order to study the effect of solution homogeneity on the resulting carbon fiber tensile strength, multiple PAN‐co‐MAA/DMF solutions were prepared, and the precursor fibers were processed using gel‐spinning, followed by continuous stabilization and carbonization. The rheological properties of each solution were also measured and correlated with the tensile strength values of the carbon fibers. It was observed that with increasing the slope of the G′ versus G″ log‐log plot from 1.471 to 1.552, and reducing interfilament fiber friction during precursor fiber drawing through the addition of a fiber washing step prior to fiber drawing, the carbon fiber strength was improved (from 3.7 to 5.8 GPa). This suggests that along with precursor fiber manufacturing and carbonization, the solution homogeneity is also very important to obtain high strength carbon fiber. POLYM. ENG. SCI., 56:361–370, 2016. © 2016 Society of Plastics Engineers     

Quadtree-based eigendecomposition for pose estimation in the presence of occlusion and background clutter

Eigendecomposition-based techniques are popular for a number of computer vision problems, e.g., object and pose estimation, because they are purely appearance based and they require few on-line computations. Unfortunately, they also typically require an unobstructed view of the object whose pose is being detected. The presence of occlusion and background clutter precludes the use of the normalizations that are typically applied and significantly alters the appearance of the object under detection. This work presents an algorithm that is based on applying eigendecomposition to a quadtree representation of the image dataset used to describe the appearance of an object. This allows decisions concerning the pose of an object to be based on only those portions of the image in which the algorithm has determined that the object is not occluded. The accuracy and computational efficiency of the proposed approach is evaluated on 16 different objects with up to 50% of the object being occluded and on images of ships in a dockyard.

Heating rate effects during non-isothermal annealing of AIK steel

The effects of heating rate on microstructural size and shape parameters during annealing of cold rolled aluminum killed steel strips have been examined under non-isothermal condition. It is shown that decrease in the heating rate results in accelerated grain growth behavior compared with the prediction by quasi-isothermal based kinetics. The {111} and {112} crystallographic orientations, which enhance the normal anisotropy and deep drawability of cold rolled annealed sheets, are found to exhibit a strong correlation with the grain shape anisotropy. This grain shape anisotropy itself is strongly dependent on heating rates. Lower heating rates result in higher aspect ratios and thus better drawability of the cold rolled sheets. A Hall-Petch type relationship is observed between grain size and hardness of the annealed samples.     

Availability modeling of energy management systems

Energy management system (EMS) computer architectures have changed significantly over the recent past increasing the difficulty and the need for a priori assessment of system performance and dependability. The old practice based on measurements is no longer acceptable because of the flexibility accrued with the deployment of the new distributed computer-based systems. The number of “what if” questions increased since EMS systems are now implemented using multiple workstations that can be interconnected in various different ways.In this paper we show how alternative configurations can be modeled and analyzed, before proposing and purchasing any equipment, with the assistance of Markov reward models. We review the concept of Markov reward models and show how they can be applied in the availability analysis of SCADA/EMS computer systems. The paper also presents a software tool that facilitates automatic generation and solution of large Markov reward models. The input language of this modeling tool uses a variation of stochastic Petri nets called stochastic reward nets, which are also reviewed. We believe this is the first time a detailed quantitative model of a SCADA/EMS computer system is proposed and solved in the general literature.     

Buffer losses vs. deadline violations for ABR traffic in an ATM switch: A computational approach

The B‐ISDN will carry a variety of traffic types: the Variable Bit Rate traffic (VBR), of which compressed video is an example, Continuous Bit Rate traffic (CBR), of which telemetry is an example, Data traffic, and Available Bit Rate traffic (ABR) that represents aggregate data traffic with very limited guarantees on quality. Of these, VBR and CBR have timing constraints and need synchronous bandwidth; data traffic is relatively delay insensitive. In this paper, we consider the VBR, Data and ABR traffic types and obtain the cumulative distribution function (cdf) of the queueing delay experienced by a burst of ABR traffic in the output buffer of an ATM switch. The cdf is used to trade off buffer loss probabilities against deadline violation probabilities through adjusting the buffer size and (delay) deadline values. Large buffers result in low losses but queueing delays can become excessive and cause a high level of deadline violations. Both losses and violations are detrimental and an operating point must be chosen to achieve a balance. In this paper we study the nature of the trade off. We develop a stochastic Petri net model assuming periodic burst arrivals for VBR and Poisson arrival processes for the Data and ABR traffic types at the burst level, and solve the model analytically (numerically) using a decomposition approach. This decomposition, along with the inherent decomposability of the tagged customer approach for obtaining the cdf opens up a possibility of carrying out fast computations using a parallel machine for selecting the operating point each time that a call is admitted. This revised version was published online in June 2006 with corrections to the Cover Date.