Output feedback adaptive command following and disturbance rejection for nonminimum phase uncertain dynamical systems

In this paper, we develop an output feedback adaptive control framework for continuous‐time nonminimum phase multivariable systems for output stabilization, command following, and disturbance rejection. The approach is based on a nonminimal state space realization that generates an expanded set of states using the filtered inputs and filtered outputs and their derivatives of the original system. Specifically, a direct adaptive controller for the nonminimal state space model is constructed using the expanded states of the nonminimal realization and is shown to be effective for multi‐input, multi‐output nonminimum phase systems with unstable dynamics. The adaptive controller does not require any model information nor does it require information of the system poles and system zeros or estimation of the system Markov parameters. Several illustrative numerical examples are provided to demonstrate the efficacy of the proposed approach. Copyright © 2010 John Wiley & Sons, Ltd.     

Wear estimation by testing the elastic behavior of tool surface

Impedance and Lamb wave structural health monitoring (SHM) techniques are two common approaches used to successfully monitor the integrity of a variety of structures. In this paper, the feasibility of applying both methods for monitoring tool wear is investigated. Additionally, the surface response to excitation (SuRE) was investigated using spectrum analyzers an alternative to the costlier impedance method. Three approaches were used to monitor the condition of both new and artificially worn drill bits. Artificial degradation of the drill bit cutting edges was necessary to avoid any possible data contamination from accidental damage to the sensors or wiring in a harsh machining environment. The estimated magnitude characteristics found from the impedance and spectrum analyzers correctly distinguished between new and worn tools. Lamb wave characteristics were represented by the envelopes of the propagated signal. The S-transformation was then used to obtain the envelope of the harmonic component of the signal at the excitation frequency. The envelopes were nearly identical at similar tool wear levels, and envelope characteristics changed significantly when Lamb wave reflections reached the sensor from the worn cutting edges. The study indicated that each of the three approaches used successfully detected tool wear.     

Taguchi Method–GONNS integration: Complete procedure covering from experimental design to complex optimization

Determination of the optimal operating conditions from the experimental data without fitting any analytical or empirical models is very convenient for manufacturing applications. In this paper, integration of Taguchi Method and Genetically Optimized Neural Networks (GONNS) is proposed. The proposed procedure covers all the steps from experimental design to complex optimization. The feasibility of the approach was evaluated by estimating the optimal cutting conditions for the milling of Ti6Al4V titanium alloy with PVD coated inserts. The test conditions were determined by the Taguchi Method. The optimal cutting condition and influences of the cutting speed, feed rate and cutting depth on the surface roughness were analyzed with the same method. GONNS estimated that the optimal cutting conditions were very close to the Taguchi Method when the same criterion was used. GONNS was also capable to minimize or maximize one of the output parameters while the others were kept within the desired range. Study demonstrated that Taguchi Method and GONNS complement each other for creation of a robust procedure for determination of the test conditions, analysis of the quality of the collected data, estimation of the influence of each parameter on the output(s) and estimation of optimal conditions with complex optimization objective functions.     

Baking kinetics of muffins in convection and steam assisted hybrid ovens (baking kinetics of muffin…)

Effects of oven type and baking temperature on acrylamide concentration, surface browning, temperature profiles and drying rates of muffins were investigated. Muffins were baked in convection and steam assisted hybrid ovens at 145, 160 and 175 °C for different baking times. For all oven types, the acrylamide concentration of muffins increased with increasing baking time and temperature (p < 0.05). The formation was considered as the first order reaction kinetics except for the lowest baking temperature at natural convection and steam assisted hybrid ovens. The reaction rate constant, k was found to be in the range of 0.027–0.078 (min⁻¹). For the forced convection oven, the effect of baking temperature on acrylamide concentration followed the Arrhenius type of equation; with activation energy of 36.35 kJ/mol. The minimum drying rate was observed by the steam assisted hybrid oven, at all conditions. Steam assisted baking resulted in lower acrylamide concentration at all baking temperatures, while providing the average moisture content not significantly different.     

Micro-end-milling-III. Wear estimation and tool breakage detection using acoustic emission signals

Acoustic Emission (AE) signals have been used to monitor tool condition in conventional machining operations. In this paper, new procedures are proposed to detect tool breakage and to estimate tool condition (wear) by using AE. The proposed procedure filters the AE signals with a narrow band-width, band-pass filter and obtains the upper envelope of the harmonic signal by using analog hardware. The envelope is digitized, encoded and classified to monitor the machining operation. The characteristics of the envelope of the AE were evaluated to detect tool breakage. The encoded parameters of the envelope of the AE signals were classified by using the Adaptive Resonance Theory (ART2) and Abductory Induction Mechanism (AIM) to estimate wear. The proposed tool breakage and wear estimation techniques were tested on the experimental data. Both methods were found to be acceptable. However, the reliability of the tool breakage detection system was higher than the wear estimation method.     

Boron‐based hydrides for chemical hydrogen storage

The development of the hydrogen economy is hampered by many issues connected with production, storage, distribution, and end‐use. Although the hydrogen storage problem is particularly difficult, there are several attractive solutions under investigation, and chemical hydrogen storage (involving hydrogen‐rich materials) has shown much promising properties. The boron‐based materials are typical examples. They have high hydrogen densities, with up to four reactive B ? H bonds. Most of the works have focused on dehydrogenation by hydrolysis or thermolysis so that it takes place in high extent in mild conditions. The first materials studied have been lithium borohydride, sodium borohydride, and ammonia borane. However, their development has been hindered by technical issues such as very high dehydrogenation temperatures, incomplete reaction, and purity of the produced hydrogen. To get round such problems, new materials have been proposed since the mid‐2000s. Interestingly, those materials present attractive attributes, but also drawbacks. This is illustrated in the present review. We believe that boron‐based hydrides have a significant potential in chemical hydrogen storage, but their implementation depends on the recyclability of the solid by‐products; this seems to be the key factor. Copyright © 2013 John Wiley & Sons, Ltd.     

Effect of Steam-Assisted Hybrid Cooking on Textural Quality Characteristics,Cooking Loss,and Free Moisture Content of Beef

Semitendinosus muscles were cooked in a steam-assisted hybrid oven and also convection ovens at three different oven temperatures (180, 210, and 240°C) until three different end point temperatures [65°C (medium-rare), 72°C (medium), 80°C (medium-well)] were reached. Textural properties of cooked beef were investigated by the Warner Bratzler shear test and texture profile analysis. Cooking loss and free moisture content of muscle tissue was determined for each cooking condition. In addition, sensory analysis was carried out in order to compare with the instrumental results and correlations between instrumental texture parameters and sensory results. Steam-assisted hybrid oven cooking of beef resulted in a tougher texture, higher cooking loss, and lower free moisture content than convection cooking. High correlation coefficients (r² > 0.70) were observed between instrumental texture measurements and sensory results for all ovens, especially in terms of tenderness. The free moisture content and adhesiveness values were also correlated well with juiciness (r² > 0.70) for all oven types.     

Nickel-based bimetallic nanocatalysts in high-extent dehydrogenation of hydrazine borane

Hydrazine borane N₂H₄BH₃ (HB) is a promising chemical hydrogen storage material but its development is highly dependent on the catalyst that will be used to dehydrogenate it, that is, to hydrolyze the BH₃ group and then to decompose selectively the N₂H₄ moiety into H₂ and N₂. Finding a reactive and selective catalyst is thus crucial. This is the topic of the present work, where we mainly focused on nickel-based bimetallic nanoparticles synthesized using a hexadecyltrimethylammonium bromide-aided co-reduction method (sodium borohydride or ammonia borane as reducing agent). The second metal, in amounts from 0.03 to 0.23 mol%, was chosen to be ruthenium, rhodium, platinum and iridium. With the 49 nanocatalysts prepared, discrepant results were found; the mol number of H₂ + N₂ per mol of HB varied from 3.1 to 5.1. The best bimetallic systems were then characterized by XRD, TEM, and XPS. Our main results are reported and discussed herein.     

Tree network 1-median location with interval data: a parameter space-based approach

We consider a family of 1-median location problems on a tree network where the vertex weights are ranges rather than point values. We define a new framework for making sound decisions under uncertainty which is primarily based on the interplay between the points in the tree and the data that induce the family of problems. An important feature of this framework is that it provides a novel understanding of the problem under uncertainty by collectively handling all possible realizations of the weights. The key element is the notion of a region of a optimality. Based on the regions of optimality, we define three optimality criteria and give low-order polynomial methods to compute the associated solution sets.