An instantaneous control model for flow control in an ATM network

This paper is concerned with the optimal flow control of an ATM switching element in a broadband-integrated services digital network. We model the switching element as a stochastic fluid flow system with a finite buffer, a constant output rate server, and a Gaussian process to characterize the input, which is a heterogeneous set of traffic sources. The fluid level should be maintained between two levels namely b1 and b2 with b1control on the ATM network is considered

Zn incorporation and band gap shrinkage in p-type GaAs

Dimethylzine (DMZn) was used as a p-type dopant in GaAs grown by low pressure metalorganic vapor phase epitaxy using trimethylgallium and arsine (AsH3) as source materials, The hole carrier concentrations and zinc (Zn) incorporation efficiency are studied by using the Hall effect, electrochemical capacitance voltage profiler and photoluminescence (PL) spectroscopy, The influence of growth parameters such as DMZn mole fraction, growth temperature, and AsH, mole fraction on the Zn incorporation have been studied. The hole concentration increases with increasing DMZn and AsH3 mole fraction and decreases with increasing growth temperature. This can be explained by vacancy control model. The PL experiments were carried out as a function of hole concentration (10(17)-1.5 x 10(20) cm(-3)). The main peak shifted to lower energy and the full width at half maximum (FWHM) increases with increasing hole concentrations. We have obtained an empirical relation for FWHM of PL, Delta E(p)(eV) = 1.15 x 10(-8)p(1/3). We also obtained an empirical relation for the band gap shrinkage, Delta E-g in Zn doped GaAs as a function of hole concentration. The value of Delta E-g(eV) = -2.75 x 10(-8)p(1/3), indicates a significant band gap shrinkage at high doping levels, These relations are considered to provide a useful tool to determine the hole concentration in Zn doped GaAs by low temperature PL measurement. The hole concentration increases with increasing AsH3 mole fraction and the main peak is shifted to a lower energy side. This can be explained also by the vacancy control model. As the hole concentration is increased above 3.8 x 10(18) cm(-3), a shoulder peak separated from the main peak was observed in the PL spectra and disappears at higher concentrations. (C) 1997 American Institute of Physics.

Si incorporation and Burstein-Moss shift in n-type GaAs

Silane (SiH4) was used as an n-type dopant in GaAs grown by low pressure metalorganic vapor phase epitaxy using trimethylgallium (TMGa) and arsine (AsH3) as source materials. The electron carrier concentrations and silicon (Si) incorporation efficiency are studied by using Hall effect, electrochemical capacitance voltage profiler and low temperature photoluminescence (LTPL) spectroscopy. The influence of growth parameters, such as SiH4 mole fraction, growth temperature, TMGa and AsH3 mole fractions on the Si incorporation efficiency have been studied. The electron concentration increases with increasing SIH4 mole fraction, growth temperature, and decreases with increasing TMGa and AsH3 mole fractions. The decrease in electron concentration with increasing TMGa can be explained by vacancy control model. The PL experiments were carried out as a function of electron concentration (10(17) - 1.5 x 10(18) cm(-3)). The PL main peak shifts to higher energy and the full width at half maximum (FWHM) increases with increasing electron concentrations. We have obtained an empirical relation for FWHM of PL, Delta E(n) (eV) = 1.4 x 10(-8) n(1/3). We also obtained an empirical relation for the band gap shrinkage, Delta E-g in Si-doped GaAs as a function of electron concentration. The value of Delta E-g (eV) = -2.75 x 10(-8) n(1/3), indicates a significant band gap shrinkage at high doping levels. These relations are considered to provide a useful tool to determine the electron concentration in Si-doped GaAs by low temperature PL measurement. The electron concentration decreases with increasing TMGa and AsH3 mole fractions and the main peak shifts to the lower energy side. The peak shifts towards the lower energy side with increasing TMGa variation can also be explained by vacancy control model. (C) 1999 Elsevier Science S.A. All rights reserved.

Basin Scale Water Resources Systems Modeling Under Cascading Uncertainties

Global change in climate and consequent large impacts on regional hydrologic systems have, in recent years, motivated significant research efforts in water resources modeling under climate change. In an integrated future hydrologic scenario, it is likely that water availability and demands will change significantly due to modifications in hydro-climatic variables such as rainfall, reservoir inflows, temperature, net radiation, wind speed and humidity. An integrated regional water resources management model should capture the likely impacts of climate change on water demands and water availability along with uncertainties associated with climate change impacts and with management goals and objectives under non-stationary conditions. Uncertainties in an integrated regional water resources management model, accumulating from various stages of decision making include climate model and scenario uncertainty in the hydro-climatic impact assessment, uncertainty due to conflicting interests of the water users and uncertainty due to inherent variability of the reservoir inflows. This paper presents an integrated regional water resources management modeling approach considering uncertainties at various stages of decision making by an integration of a hydro-climatic variable projection model, a water demand quantification model, a water quantity management model and a water quality control model. Modeling tools of canonical correlation analysis, stochastic dynamic programming and fuzzy optimization are used in an integrated framework, in the approach presented here. The proposed modeling approach is demonstrated with the case study of the Bhadra Reservoir system in Karnataka, India.

Spiral-Wave Dynamics in a Mathematical Model of Human Ventricular Tissue with Myocytes and Fibroblasts

Cardiac fibroblasts, when coupled functionally with myocytes, can modulate the electrophysiological properties of cardiac tissue. We present systematic numerical studies of such modulation of electrophysiological properties in mathematical models for (a) single myocyte-fibroblast (MF) units and (b) two-dimensional (2D) arrays of such units; our models build on earlier ones and allow for zero-, one-, and two-sided MF couplings. Our studies of MF units elucidate the dependence of the action-potential (AP) morphology on parameters such as E-f, the fibroblast resting-membrane potential, the fibroblast conductance G(f), and the MF gap-junctional coupling G(gap). Furthermore, we find that our MF composite can show autorhythmic and oscillatory behaviors in addition to an excitable response. Our 2D studies use (a) both homogeneous and inhomogeneous distributions of fibroblasts, (b) various ranges for parameters such as G(gap), G(f), and E-f, and (c) intercellular couplings that can be zero-sided, one-sided, and two-sided connections of fibroblasts with myocytes. We show, in particular, that the plane-wave conduction velocity CV decreases as a function of G(gap), for zero-sided and one-sided couplings; however, for two-sided coupling, CV decreases initially and then increases as a function of G(gap), and, eventually, we observe that conduction failure occurs for low values of G(gap). In our homogeneous studies, we find that the rotation speed and stability of a spiral wave can be controlled either by controlling G(gap) or E-f. Our studies with fibroblast inhomogeneities show that a spiral wave can get anchored to a local fibroblast inhomogeneity. We also study the efficacy of a low-amplitude control scheme, which has been suggested for the control of spiral-wave turbulence in mathematical models for cardiac tissue, in our MF model both with and without heterogeneities.

Model Predictive Static Programming: A Computationally Efficient Technique For Suboptimal Control Design

Combining the philosophies of nonlinear model predictive control and approximate dynamic programming, a new suboptimal control design technique is presented in this paper, named as model predictive static programming (MPSP), which is applicable for finite-horizon nonlinear problems with terminal constraints. This technique is computationally efficient, and hence, can possibly be implemented online. The effectiveness of the proposed method is demonstrated by designing an ascent phase guidance scheme for a ballistic missile propelled by solid motors. A comparison study with a conventional gradient method shows that the MPSP solution is quite close to the optimal solution.

Self-tuning minimum-variance control of nonlinear systems of the Hammerstein model

Self-tuning is applied to the control of nonlinear systems represented by the Hammerstein model wherein the nonlinearity is any odd-order polynomial. But control costing is not feasible in general. Initial relay control is employed to contain the deviations.

Drosophila indirect flight muscle specific Act88F actin mutants as a model system for studying congenital myopathies of the human ACTA1 skeletal muscle actin gene

Most human ACTA1 skeletal actin gene mutations cause dominant, congenital myopathies often with severely reduced muscle function and neonatal mortality. High sequence conservation of actin means many mutated ACTA1 residues are identical to those in the Drosophila Act88F, an indirect flight muscle specific sarcomeric actin. Four known Act88F mutations occur at the same actin residues mutated in ten ACTA1 nemaline mutations, A138D/P, R256H/L, G268C/D/R/S and R372C/S. These Act88F mutants were examined for similar muscle phenotypes. Mutant homozygotes show phenotypes ranging from a lack of myofibrils to almost normal sarcomeres at eclosion. Aberrant Z-disc-like structures and serial Z-disc arrays, ‘zebra bodies’, are observed in homozygotes and heterozygotes of all four Act88F mutants. These electron-dense structures show homologies to human nemaline bodies/rods, but are much smaller than those typically found in the human myopathy. We conclude that the Drosophila indirect flight muscles provide a good model system for studying ACTA1 mutations.

Effective treatment of infectious diseases: A nonlinear adaptive control theoretic approach

A nonlinear adaptive system theoretic approach is presented in this paper for effective treatment of infectious diseases that affect various organs of the human body. The generic model used does not represent any specific disease. However, it mimics the generic immunological dynamics of the human body under pathological attack, including the response to external drugs. From a system theoretic point of view, drugs can be interpreted as control inputs. Assuming a set of nominal parameters in the mathematical model, first a nonlinear controller is designed based on the principle of dynamic inversion. This treatment strategy was found to be effective in completely curing "nominal patients". However, in some cases it is ineffective in curing "realistic patients". This leads to serious (sometimes fatal) damage to the affected organ. To make the drug dosage design more effective, a model-following neuro-adaptive control design is carried out using neural networks, which are trained (adapted) online. From simulation studies, this adaptive controller is found to be effective in killing the invading microbes and healing the damaged organ even in the presence of parameter uncertainties and continuing pathogen attack.

Some experiments on human memory and a new neural model

An associative memory with parallel architecture is presented. The neurons are modelled by perceptrons having only binary, rather than continuous valued input. To store m elements each having n features, m neurons each with n connections are needed. The n features are coded as an n-bit binary vector. The weights of the n connections that store the n features of an element has only two values -1 and 1 corresponding to the absence or presence of a feature. This makes the learning very simple and straightforward. For an input corrupted by binary noise, the associative memory indicates the element that is closest (in terms of Hamming distance) to the noisy input. In the case where the noisy input is equidistant from two or more stored vectors, the associative memory indicates two or more elements simultaneously. From some simple experiments performed on the human memory and also on the associative memory, it can be concluded that the associative memory presented in this paper is in some respect more akin to a human memory than a Hopfield model.

Optimal management of beaver population using a reduced-order distributed parameter model and single network adaptive critics

Beavers are often found to be in conflict with human interests by creating nuisances like building dams on flowing water (leading to flooding), blocking irrigation canals, cutting down timbers, etc. At the same time they contribute to raising water tables, increased vegetation, etc. Consequently, maintaining an optimal beaver population is beneficial. Because of their diffusion externality (due to migratory nature), strategies based on lumped parameter models are often ineffective. Using a distributed parameter model for beaver population that accounts for their spatial and temporal behavior, an optimal control (trapping) strategy is presented in this paper that leads to a desired distribution of the animal density in a region in the long run. The optimal control solution presented, imbeds the solution for a large number of initial conditions (i.e., it has a feedback form), which is otherwise nontrivial to obtain. The solution obtained can be used in real-time by a nonexpert in control theory since it involves only using the neural networks trained offline. Proper orthogonal decomposition-based basis function design followed by their use in a Galerkin projection has been incorporated in the solution process as a model reduction technique. Optimal solutions are obtained through a "single network adaptive critic" (SNAC) neural-network architecture.

Scroll-Wave Dynamics in Human Cardiac Tissue: Lessons from a Mathematical Model with Inhomogeneities and Fiber Architecture

Cardiac arrhythmias, such as ventricular tachycardia (VT) and ventricular fibrillation (VF), are among the leading causes of death in the industrialized world. These are associated with the formation of spiral and scroll waves of electrical activation in cardiac tissue; single spiral and scroll waves are believed to be associated with VT whereas their turbulent analogs are associated with VF. Thus, the study of these waves is an important biophysical problem. We present a systematic study of the combined effects of muscle-fiber rotation and inhomogeneities on scroll-wave dynamics in the TNNP (ten Tusscher Noble Noble Panfilov) model for human cardiac tissue. In particular, we use the three-dimensional TNNP model with fiber rotation and consider both conduction and ionic inhomogeneities. We find that, in addition to displaying a sensitive dependence on the positions, sizes, and types of inhomogeneities, scroll-wave dynamics also depends delicately upon the degree of fiber rotation. We find that the tendency of scroll waves to anchor to cylindrical conduction inhomogeneities increases with the radius of the inhomogeneity. Furthermore, the filament of the scroll wave can exhibit drift or meandering, transmural bending, twisting, and break-up. If the scroll-wave filament exhibits weak meandering, then there is a fine balance between the anchoring of this wave at the inhomogeneity and a disruption of wave-pinning by fiber rotation. If this filament displays strong meandering, then again the anchoring is suppressed by fiber rotation; also, the scroll wave can be eliminated from most of the layers only to be regenerated by a seed wave. Ionic inhomogeneities can also lead to an anchoring of the scroll wave; scroll waves can now enter the region inside an ionic inhomogeneity and can display a coexistence of spatiotemporal chaos and quasi-periodic behavior in different parts of the simulation domain. We discuss the experimental implications of our study.

Chain folding and A:T pairing in human telomeric DNA: a model-building and molecular dynamics study

The various types of chain folding and possible intraloop as well as interloop base pairing in human telomeric DNA containing d(TTAG(3)) repeats have been investigated by model-building, molecular mechanics, and molecular dynamics techniques. Model-building and molecular mechanics studies indicate that it is possible to build a variety of energetically favorable folded-back structures with the two TTA loops on same side and the 5' end thymines in the two loops forming TATA tetrads involving a number of different intraloop as well as interloop A:T pairing schemes. In these folded-back structures, although both intraloop and interloop Watson-Crick pairing is feasible, no structure is possible with interloop Hoogsteen pairing. MD studies of representative structures indicate that the guanine-tetraplex stem is very rigid and, while the loop regions are relatively much more flexible, most of the hydrogen bonds remain intact throughout the 350-ps in vacuo simulation. The various possible TTA loop structures, although they are energetically similar, have characteristic inter proton distances, which could give rise to unique cross-peaks in two-dimensional nuclear Overhauser effect spectroscopy (NOESY) experiments. These folded-back structures with A:T pairings in the loop region help in rationalizing the data from chemical probing and other biochemical studies on human telomeric DNA.

Model-following Neuro-adaptive approach for robust control of high performance aircrafts

Based on dynamic inversion, a relatively straightforward approach is presented in this paper for nonlinear flight control design of high performance aircrafts, which does not require the normal and lateral acceleration commands to be first transferred to body rates before computing the required control inputs. This leads to substantial improvement of the tracking response. Promising results are obtained from six degree-offreedom simulation studies of F-16 aircraft, which are found to be superior as compared to an existing approach (which is also based on dynamic inversion). The new approach has two potential benefits, namely reduced oscillatory response (including elimination of non-minimum phase behavior) and reduced control magnitude. Next, a model-following neuron-adaptive design is augmented the nominal design in order to assure robust performance in the presence of parameter inaccuracies in the model. Note that in the approach the model update takes place adaptively online and hence it is philosophically similar to indirect adaptive control. However, unlike a typical indirect adaptive control approach, there is no need to update the individual parameters explicitly. Instead the inaccuracy in the system output dynamics is captured directly and then used in modifying the control. This leads to faster adaptation, which helps in stabilizing the unstable plant quicker. The robustness study from a large number of simulations shows that the adaptive design has good amount of robustness with respect to the expected parameter inaccuracies in the model.

Convergence problems in a class of model reference adaptive control systems

A class of model reference adaptive control system which make use of an augmented error signal has been introduced by Monopoli. Convergence problems in this attractive class of systems have been investigated in this paper using concepts from hyperstability theory. It is shown that the condition on the linear part of the system has to be stronger than the one given earlier. A boundedness condition on the input to the linear part of the system has been taken into account in the analysis - this condition appears to have been missed in the previous applications of hyperstability theory. Sufficient conditions for the convergence of the adaptive gain to the desired value are also given.