Sliding mode control-based algorithms for consensus in connected swarms

In this article, finite-time consensus algorithms for a swarm of self-propelling agents based on sliding mode control and graph algebraic theories are presented. Algorithms are developed for swarms that can be described by balanced graphs and that are comprised of agents with dynamics of the same order. Agents with first and higher order dynamics are considered. For consensus, the agents' inputs are chosen to enforce sliding mode on surfaces dependent on the graph Laplacian matrix. The algorithms allow for the tuning of the time taken by the swarm to reach a consensus as well as the consensus value. As an example, the case when a swarm of first-order agents is in cyclic pursuit is considered.

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.

Quantum Algorithms with Fixed Points: The Case of Database Search

The standard quantum search algorithm lacks a feature, enjoyed by many classical algorithms, of having a fixed-point, i.e. a monotonic convergence towards the solution. Here we present two variations of the quantum search algorithm, which get around this limitation. The first replaces selective inversions in the algorithm by selective phase shifts of $\frac{\pi}{3}$. The second controls the selective inversion operations using two ancilla qubits, and irreversible measurement operations on the ancilla qubits drive the starting state towards the target state. Using $q$ oracle queries, these variations reduce the probability of finding a non-target state from $\epsilon$ to $\epsilon^{2q+1}$, which is asymptotically optimal. Similar ideas can lead to robust quantum algorithms, and provide conceptually new schemes for error correction.

Nature of Electronic States in Atomically Thin MoS(2) Field-Effect Transistors

We present low-temperature electrical transport experiments in five field-effect transistor devices consisting of monolayer, bilayer, and trilayer MoS(2) films, mechanically exfoliated onto Si/SiO(2) substrate. Our experiments reveal that the electronic states In all films are localized well up to room temperature over the experimentally accessible range of gate voltage. This manifests in two-dimensional (2D) variable range hopping (VRH) at high temperatures, while below similar to 30 K, the conductivity displays oscillatory structures In gate voltage arising from resonant tunneling at the localized sites. From the correlation energy (T(0)) of VRH and gate voltage dependence of conductivity, we suggest that Coulomb potential from trapped charges In the substrate is the dominant source of disorder in MoS(2) field-effect devices, which leads to carrier localization, as well.

Multigrid algorithms for symmetric discontinuous Galerkin methods on graded meshes

We study a class of symmetric discontinuous Galerkin methods on graded meshes. Optimal order error estimates are derived in both the energy norm and the L 2 norm, and we establish the uniform convergence of V-cycle, F-cycle and W-cycle multigrid algorithms for the resulting discrete problems. Numerical results that confirm the theoretical results are also presented.

Swarm intelligence algorithms for integrated optimization of piezoelectric actuator and sensor placement and feedback gains

Swarm intelligence algorithms are applied for optimal control of flexible smart structures bonded with piezoelectric actuators and sensors. The optimal locations of actuators/sensors and feedback gain are obtained by maximizing the energy dissipated by the feedback control system. We provide a mathematical proof that this system is uncontrollable if the actuators and sensors are placed at the nodal points of the mode shapes. The optimal locations of actuators/sensors and feedback gain represent a constrained non-linear optimization problem. This problem is converted to an unconstrained optimization problem by using penalty functions. Two swarm intelligence algorithms, namely, Artificial bee colony (ABC) and glowworm swarm optimization (GSO) algorithms, are considered to obtain the optimal solution. In earlier published research, a cantilever beam with one and two collocated actuator(s)/sensor(s) was considered and the numerical results were obtained by using genetic algorithm and gradient based optimization methods. We consider the same problem and present the results obtained by using the swarm intelligence algorithms ABC and GSO. An extension of this cantilever beam problem with five collocated actuators/sensors is considered and the numerical results obtained by using the ABC and GSO algorithms are presented. The effect of increasing the number of design variables (locations of actuators and sensors and gain) on the optimization process is investigated. It is shown that the ABC and GSO algorithms are robust and are good choices for the optimization of smart structures.

Nature and Properties of a Repulsive Fermi Gas in the Upper Branch of the Energy Spectrum

We generalize the Nozieres-Schmitt-Rink method to study the repulsive Fermi gas in the absence of molecule formation, i.e., in the so-called ``upper branch.'' We find that the system remains stable except close to resonance at sufficiently low temperatures. With increasing scattering length, the energy density of the system attains a maximum at a positive scattering length before resonance. This is shown to arise from Pauli blocking which causes the bound states of fermion pairs of different momenta to disappear at different scattering lengths. At the point of maximum energy, the compressibility of the system is substantially reduced, leading to a sizable uniform density core in a trapped gas. The change in spin susceptibility with increasing scattering length is moderate and does not indicate any magnetic instability. These features should also manifest in Fermi gases with unequal masses and/or spin populations.

Discrete control algorithms for a tubular ammonia reactor

The specific objective of this paper is to develop direct digital control strategies for an ammonia reactor using quadratic regulator theory and compare the performance of the resultant control system with that under conventional PID regulators. The controller design studies are based on a ninth order state-space model obtained from the exact nonlinear distributed model using linearization and lumping approximations. The evaluation of these controllers with reference to their disturbance rejection capabilities and transient response characteristics, is carried out using hybrid computer simulation.

On the athermal nature of the beta to omega transformation

One characteristic feature of the athermal beta -> omega transformation is the short time scale of the transformation. So far, no clear understanding of this issue exists. Here we construct a model that includes contributions from a Landau sixth-order free energy density, kinetic energy due to displacement, and the Rayleigh dissipation function to account for the dissipation arising from the rapid movement of the parent product interface during rapid nucleation. We also include the contribution from omega-like fluctuations to local stress. The model shows that the transformation is complete on a time scale comparable to the velocity of sound. The estimated nucleation rate is several orders higher than that for diffusion-controlled transformations. The model predicts that the athermal omega phase is limited to a certain range of alloying composition. The estimated nucleation rate and the size of ``isothermal'' particles beyond 17% Nb are also consistent with experimental results. The model provides an explanation for the reprecipitation process of the omega particles in the ``cleared'' channels formed during deformation of omega-forming alloys. The model also predicts that acoustic emission should be detectable during the formation of the athermal phase. (C) 2011 Acta Materialia Inc. Published by Elsevier Ltd. All rights reserved.

Nanocrystalline TiO(2) preparation by microwave route and nature of anatase-rutile phase transition in nano TiO(2)

Nanopowders of TiO(2) has been prepared using a microwave irradiation-assisted route, starting from a metalorganic precursor, bis(ethyl-3-oxo-butanoato)oxotitanium (IV), [TiO(etob)(2)](2). Polyvinylpyrrolidone (PVP) was used as a capping agent. The as-prepared amorphous powders crystallize into anatase phase, when calcined. At higher calcination temperature, the rutile phase is observed to form in increasing quantities as the calcination temperature is raised. The structural and physicochemical properties were measured using XRD, FT-IR, SEM, TEM and thermal analyses. The mechanisms of formation of nano-TiO(2) from the metal-organic precursor and the irreversible phase transformation of nano TiO(2) from anatase to rutile structure at higher temperatures have been discussed. It is suggested that a unique step of initiation of transformation takes place in Ti(1/2)O layers in anatase which propagates. This mechanism rationalizes several key observations associated with the anatase rutile transformation.