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.

Search on a Hypercubic Lattice using Quantum Random Walk

We investigate the spatial search problem on the two-dimensional square lattice, using the Dirac evolution operator discretized according to the staggered lattice fermion formalism. d=2 is the critical dimension for the spatial search problem, where infrared divergence of the evolution operator leads to logarithmic factors in the scaling behavior. As a result, the construction used in our accompanying article [ A. Patel and M. A. Rahaman Phys. Rev. A 82 032330 (2010)] provides an O(√NlnN) algorithm, which is not optimal. The scaling behavior can be improved to O(√NlnN) by cleverly controlling the massless Dirac evolution operator by an ancilla qubit, as proposed by Tulsi Phys. Rev. A 78 012310 (2008). We reinterpret the ancilla control as introduction of an effective mass at the marked vertex, and optimize the proportionality constants of the scaling behavior of the algorithm by numerically tuning the parameters.

Intruder detection over sensor placement in a hexagonal lattice

The problem of intrusion detection and location identification in the presence of clutter is considered for a hexagonal sensor-node geometry. It is noted that in any practical application,for a given fixed intruder or clutter location, only a small number of neighboring sensor nodes will register a significant reading. Thus sensing may be regarded as a local phenomenon and performance is strongly dependent on the local geometry of the sensor nodes. We focus on the case when the sensor nodes form a hexagonal lattice. The optimality of the hexagonal lattice with respect to density of packing and covering and largeness of the kissing number suggest that this is the best possible arrangement from a sensor network viewpoint. The results presented here are clearly relevant when the particular sensing application permits a deterministic placement of sensors. The results also serve as a performance benchmark for the case of a random deployment of sensors. A novel feature of our analysis of the hexagonal sensor grid is a signal-space viewpoint which sheds light on achievable performance.Under this viewpoint, the problem of intruder detection is reduced to one of determining in a distributed manner, the optimal decision boundary that separates the signal spaces SI and SC associated to intruder and clutter respectively. Given the difficulty of implementing the optimal detector, we present a low-complexity distributive algorithm under which the surfaces SI and SC are separated by a wellchosen hyperplane. The algorithm is designed to be efficient in terms of communication cost by minimizing the expected number of bits transmitted by a sensor.

Flux Partitioning of Species Approach in Binary Interdiffusion Process

Validation of the flux partitioning of species model has been illustrated. Various combinations of inequality expression for the fluxes of species A and B in two successively grown hypothetical intermetallic phases in the interdiffusion zone have been considered within the constraints of this concept. Furthermore, ratio of intrinsic diffusivities of the species A and B in those two phases has been correlated in four different cases. Moreover, complete and or partial validation or invalidation of this model with respect to both the species, has been proven theoretically and also discussed with the Co-Si system as an example.

Re-entrant behavior in dynamics of binary mixtures of soft hybrid nanocolloids and homopolymers

We present results of measurements of temperature and wavevector dependent dynamics in binary mixtures of soft polymer grafted nanoparticles and linear homopolymers. We find evidence of melting of the dynamically arrested state of the soft nanocolloids with addition of linear polymers followed by a re-entrant slowing down of the dynamics with further increase in polymer density, depending on the size ratio, delta, of the polymers and the nanocolloids. For higher delta the re-entrant behavior is not observed, even for the highest added polymer density, explored here. Possible explanation of the observed dynamics in terms of the presence of a double - glass phase is provided. (C) 2011 American Institute of Physics. [doi:10.1063/1.3644930]

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.

Fluctuation quench and hydrophobic collapse of polymers and biopolymers in water-DMSO binary mixture at low DMSO concentration

Binary mixtures have strong influence on activities of polymers and biopolymers even at low cosolvent concentration. Among the several aqueous binary mixtures studied, water-DMSO especially stands out for its unusual behavior at certain specific concentrations of DMSO. In the present work, we study the effect of water-DMSO binary mixture on polymers and biopolymers by taking a simple linear hydrocarbon chain of intermediate length (n = 30) and the protein lysozyme, respectively. We find that at a mole fraction of 0.05 of DMSO (x(DMSO) = 0.05) in aqueous solution, the hydrocarbon chain adopts the collapsed conformation as the most stable and rigid state. In this case of 0.05 mole fraction of DMSO in bulk, the DMSO concentration in the first hydration layer around the polymer is found to be as large as 17%. Formation of such hydrophobic environment around the polymer is the reason for the collapsed state gaining so much stability. Interestingly, similar quench of conformational fluctuation is also observed for the protein investigated. It is observed that in the case of alkane polymer chains, long wavelength fluctuation gets easily quenched, the polymer being purely hydrophobic. However, in case of the protein, quench of fluctuation is prominent only at the hydrophobic surface, and quench of long wavelength fluctuation becomes insignificant for the full protein. As protein contains both hydrophobic and hydrophilic moieties, the extent of quench of conformational fluctuation with respect to that in pure water is almost half for the biopolymer complex (16.83%) than the same for pure hydrophobic polymer chain (32.43%).

Electrocatalysis and redox behavior of Pt(2+) ion in CeO(2) and Ce(0.85)Ti(0.15)O(2): XPS evidence of participation of lattice oxygen for high activity

Electronic states of CeO(2), Ce(1 -aEuro parts per thousand x) Pt (x) O(2 -aEuro parts per thousand delta) , and Ce(1 -aEuro parts per thousand x -aEuro parts per thousand y) Ti (y) Pt (x) O(2 -aEuro parts per thousand delta) electrodes have been investigated by X-ray photoelectron spectroscopy as a function of applied potential for oxygen evolution and formic acid and methanol oxidation. Ionically dispersed platinum in Ce(1 -aEuro parts per thousand x) Pt (x) O(2 -aEuro parts per thousand delta) and Ce(1 -aEuro parts per thousand x -aEuro parts per thousand y) Ti (y) Pt (x) O(2 -aEuro parts per thousand delta) is active toward these reactions compared with CeO(2) alone. Higher electrocatalytic activity of Pt(2+) ions in CeO(2) and Ce(1 -aEuro parts per thousand x) Ti (x) O(2) compared with the same amount of Pt(0) in Pt/C is attributed to Pt(2+) ion interaction with CeO(2) and Ce(1 -aEuro parts per thousand x) Ti (x) O(2) to activate the lattice oxygen of the support oxide. Utilization of this activated lattice oxygen has been demonstrated in terms of high oxygen evolution in acid medium with these catalysts. Further, ionic platinum in CeO(2) and Ce(1 -aEuro parts per thousand x) Ti (x) O(2) does not suffer from CO poisoning effect unlike Pt(0) in Pt/C due to participation of activated lattice oxygen which oxidizes the intermediate CO to CO(2). Hence, higher activity is observed toward formic acid and methanol oxidation compared with same amount of Pt metal in Pt/C.

Effect of Electromagnetic Stirring on Macrosegregation during Solidification of a Binary Alloy

The effect of electromagnetic stirring of melt on the final macrosegregation in the continuous casting of an aluminium alloy billet is studied numerically. A continuum mixture model for solidification in presence of electromagnetic stirring is presented. As a case study, simulations are performed for direct chill (DC) casting of an Al-Cu alloy and the effect of electromagnetic stirring on macrosegregation is analysed. The model predicts the temperature, velocity, and species distribution in the mold. As a special case, we have also studied the case in which dendritic particles are fragmented at the interface due to vigorous electromagnetic stirring. For this case, an additional conservation equation for the transport of solid fraction is solved. For modeling the resistance offered by moving solid crystals, a switching function in the momentum equations is used for variation of viscosity. The fragmentation and transport of dendritic particles has a profound effect on the final macrosegregation and microstructure of the solidified billet. It is found that the application of electromagnetic stirring in continuous casting of billets results in better temperature uniformity and macrosegregation pattern.