A Neuro-Adaptive Approach for Robust Control of High Performance Aircrafts with Parameter Inaccuracies

For high performance aircrafts, the flight control system needs to be quite effective in both assuring accurate tracking of pilot commands, while simultaneously assuring overall stability of the aircraft. In addition, the control system must also be sufficiently robust to cater to possible parameter variations. The primary aim of this paper is to enhance the robustness of the controller for a HPA using neuro-adaptive control design. Here the architecture employs a network of Gaussian Radial basis functions to adaptively compensate for the ignored system dynamics. A stable weight mechanism is determined using Lyapunov theory. The network construction and performance of the resulting controller are illustrated through simulations with a low-fidelity six –DOF model of F16 that is available in open literature.

Ecological Assessment of Lentic Water Bodies of Bangalore

The restoration, conservation and management of water resources require a thorough understanding of what constitutes a healthy ecosystem. Monitoring and assessment provides the basic information on the condition of our waterbodies. The present work details the study carried out at two waterbodies, namely, the Chamarajasagar reservoir and the Madiwala Lake. The waterbodies were selected on the basis of their current use and locations. Chamarajasagar reservoir serves the purpose of supplying drinking water to Bangalore city and is located on the outskirts of the city surrounded by agricultural and forest land. On the other hand, Madiwala lake is situated in the heart of Bangalore city receiving an influx of pollutants from domestic and industrial sewage. Comparative assessment of the surface water quality of both were carried out by instituting the various physico–chemical and biological parameters. The physico-chemical analyses included temperature, transparency, pH, electrical conductivity, dissolved oxygen, alkalinity, total hardness, calcium hardness, magnesium hardness, nitrates, phosphates, sodium, potassium and COD measurements of the given waterbody. The analysis was done based on the standard methods prescribed (or recommended) by (APHA) and NEERI. The biological parameter included phytoplankton analysis. The detailed investigations of the parameters, which are well within the tolerance limits in Chamarajasagar reservoir, indicate that it is fairly unpolluted, except for the pH values, which indicate greater alkalinity. This may be attributed to the natural causes and the agricultural runoff from the catchment. On the contrary, the limnology of Madiwala lake is greatly influenced by the inflow of sewage that contributes significantly to the dissolved solids of the lake water, total hardness, alkalinity and a low DO level. Although, the two study areas differ in age, physiography, chemistry and type of inflows, they still maintain a phytoplankton distribution overwhelmingly dominated by Cyanophyceae members,specifically Microcystis aeruginosa. These blue green algae apparently enter the waterbodies from soil, which are known to harbour a rich diversity of blue green flora with several species common to limnoplankton, a feature reported to be unique to the south Indian lakes.Chamarajasagar water samples revealed five classes of phytoplankton, of which Cyanophyceae (92.15 percent) that dominated other algal forms comprised of one single species of Microcystis aeruginosa. The next major class of algae was Chlorophyceae (3.752 percent) followed by Dinophyceae (3.51 percent), Bacillariophyceae (0.47 percent) and a sparsely available and unidentified class (0.12 percent).Madiwala Lake phytoplankton, in addition to Cyanophyceae (26.20 percent), revealed a high density of Chlorophyceae members (73.44 percent) dominated by Scenedesmus sp.,Pediastrum sp., and Euglena sp.,which are considered to be indicators of organic pollution. The domestic and industrial sewage, which finds its way into the lake, is a factor causing organic pollution. As compared to the other classes, Euglenophyceae and Bacillariophyceae members were the lowest in number. Thus, the analysis of various parameters indicates that Chamarajasagar reservoir is relatively unpolluted except for the high percentage of Microcystis aeruginosa, and a slightly alkaline nature of water. Madiwala lake samples revealed eutrophication and high levels of pollution, which is clarified by the physico–chemical analysis, whose values are way above the tolerance limits. Also, the phytoplankton analysis in Madiwala lake reveals the dominance of Chlorophyceae members, which indicate organic pollution (sewage being the causative factor).

Stochastic Algorithms for Discrete Parameter Simulation Optimization

We present two efficient discrete parameter simulation optimization (DPSO) algorithms for the long-run average cost objective. One of these algorithms uses the smoothed functional approximation (SFA) procedure, while the other is based on simultaneous perturbation stochastic approximation (SPSA). The use of SFA for DPSO had not been proposed previously in the literature. Further, both algorithms adopt an interesting technique of random projections that we present here for the first time. We give a proof of convergence of our algorithms. Next, we present detailed numerical experiments on a problem of admission control with dependent service times. We consider two different settings involving parameter sets that have moderate and large sizes, respectively. On the first setting, we also show performance comparisons with the well-studied optimal computing budget allocation (OCBA) algorithm and also the equal allocation algorithm. Note to Practitioners-Even though SPSA and SFA have been devised in the literature for continuous optimization problems, our results indicate that they can be powerful techniques even when they are adapted to discrete optimization settings. OCBA is widely recognized as one of the most powerful methods for discrete optimization when the parameter sets are of small or moderate size. On a setting involving a parameter set of size 100, we observe that when the computing budget is small, both SPSA and OCBA show similar performance and are better in comparison to SFA, however, as the computing budget is increased, SPSA and SFA show better performance than OCBA. Both our algorithms also show good performance when the parameter set has a size of 10(8). SFA is seen to show the best overall performance. Unlike most other DPSO algorithms in the literature, an advantage with our algorithms is that they are easily implementable regardless of the size of the parameter sets and show good performance in both scenarios.

Temperature variation of the grüneisen parameter in magnesium oxide

The thermal expansion of magnesium oxide has been measured below room temperature from 140°K to 284.5°K, using an interferometric method. The accuracy of measurement is better than 3% in the temperature range studied. The agreement of these results with Durand's is quite good, but consistently higher over most of the range by 2 or 3%, for the most part within the estimated experimental error. The Grüneisen parameter remains constant at about 1.51 over the present experimental range; but an isolated measurement of Durand at 85°K suggests that at lower temperatures it rises quite sharply above this value. This possibility is therefore investigated theoretically. With a non-central force model to represent MgO, γ(−3) and γ(2) are calculated and it is found that γ(−3) > γ(2), again suggesting that the Grüneisen parameter increases with falling temperature. Of the two reported experimental values for the infra-red absorption frequency, correlation with the heat capacity strongly indicates a wavelength of 25.26μm rather than 17.3μm. Thermal expansion measurements at still lower temperatures must be carried out to confirm definitely the rise in the Grüneisen parameter.

Controls on intense silicate weathering in a tropical river, southwestern India

The Silicate Weathering Rate (SWR) and associated Carbon dioxide Consumption Rate (CCR) in tropical silicate terrain is assessed through a study of the major ion chemistry in a small west flowing river of Peninsular India, the Nethravati River. The specific features of the river basin are high mean annual rainfall and temperature, high runoff and a Precambrian basement composed of granitic-gneiss, charnockite and minor metasediments. The water samples (n = 56) were collected from three locations along the Nethravati River and from two of its tributaries over a period of twelve months. Chemical Weathering Rate (CWR) for the entire watershed is calculated by applying rainwater correction using river chloride as a tracer. Chemical Weathering Rate in the Nethravati watershed is estimated to 44 t.km(-2).y(-1) encompassing a SWR of 42 t.km(-2).y(-1) and a maximum carbonate contribution of 2 t.km(-2).y(-1). This SWR is among the highest reported for granito-gneissic terrains. The assessed CCR is 2.9 . 10(5) mol.km(-2).y(-1). The weathering index (Re). calculated from molecular ratios of dissolved cations and silica in the river, suggests an intense silicate weathering leading to kaolinite-gibbsite precipitation in the weathering covers. The intense SWR and CCR could be due to the combination of high runoff and temperature along with the thickness and nature of the weathering cover. The comparison of silicate weathering fluxes with other watersheds reveals that under similar morpho-climatic settings basalt weathering would be 2.5 times higher than the granite-gneissic rocks. (C) 2012 Elsevier B.V. All rights reserved.