Concepts of Static Var System Control For Enhancing Power Transfer in Long Transmission Lines

This paper is concerned with the influence of different levels of complexity in modelling various constituent subsystems on the dynamic stability of power systems compensated by static var systems (SVS) operating on pure voltage control. The system components investigated include thyristor controlled reactor (TCR) transients, SVS delays, network transients, the synchronous generator and automatic voltage regulator (AVR). An overall model is proposed which adequately describes the system performance for small signal perturbations. The SVS performance is validated through detailed nonlinear simulation on a physical simulator.

Decentralized Parallel Operation of Inverters Sharing Unbalanced and Nonlinear Loads

In this paper, a wireless control strategy for parallel operation of three-phase four-wire inverters is proposed. A generalized situation is considered where the inverters are of unequal power ratings and the loads are nonlinear and unbalanced in nature. The proposed control algorithm exploits the potential of sinusoidal domain proportional+multiresonant controller ( in the inner voltage regulation loop) to make the system suitable for nonlinear and unbalanced loads with a simple and generalized structure of virtual output-impedance loop. The decentralized operation is achieved by using three-phase P/Q droop characteristics. The overall control algorithm helps to limit the harmonic contents and the degree of unbalance in the output-voltage waveform and to achieve excellent power-sharing accuracy in spite of mismatch in the inverter output impedances. Moreover, a synchronized turn on with consequent change over to the droop mode is applied for the new incoming unit in order to limit the circulating current completely. The simulation and experimental results from-1 kVA and -0.5 kVA paralleled units validate the effectiveness of the scheme.

Nonlinear hydrodynamics of a hard-sphere fluid near the glass transition

We conduct a numerical study of the dynamic behavior of a dense hard-sphere fluid by deriving and integrating a set of Langevin equations. The statics of the system is described by a free-energy functional of the Ramakrishnan-Yussouff form. We find that the system exhibits glassy behavior as evidenced through a stretched exponential decay and a two-stage relaxation of the density correlation function. The characteristic times grow with increasing density according to the Vogel-Fulcher law. The wave-number dependence of the kinetics is extensively explored. The connection of our results with experiment, mode-coupling theory, and molecular-dynamics results is discussed.

On the Milito-Cruz adaptive control scheme for Markov chains

Milito and Cruz have introduced a novel adaptive control scheme for finite Markov chains when a finite parametrized family of possible transition matrices is available. The scheme involves the minimization of a composite functional of the observed history of the process incorporating both control and estimation aspects. We prove the a.s. optimality of a similar scheme when the state space is countable and the parameter space a compact subset ofR.

Composite material and piezoelectric coefficient uncertainty effects on structural health monitoring using feedback control gains as damage indicators

This article addresses uncertainty effect on the health monitoring of a smart structure using control gain shifts as damage indicators. A finite element model of the smart composite plate with surface-bonded piezoelectric sensors and actuators is formulated using first-order shear deformation theory and a matrix crack model is integrated into the finite element model. A constant gain velocity/position feedback control algorithm is used to provide active damping to the structure. Numerical results show that the response of the structure is changed due to matrix cracks and this change can be compensated by actively tuning the feedback controller. This change in control gain can be used as a damage indicator for structural health monitoring. Monte Carlo simulation is conducted to study the effect of material uncertainty on the damage indicator by considering composite material properties and piezoelectric coefficients as independent random variables. It is found that the change in position feedback control gain is a robust damage indicator.

Robust/Optimal Temperature Profile Control of a High-Speed Aerospace Vehicle Using Neural Networks

An approximate dynamic programming (ADP)-based suboptimal neurocontroller to obtain desired temperature for a high-speed aerospace vehicle is synthesized in this paper. A I-D distributed parameter model of a fin is developed from basic thermal physics principles. "Snapshot" solutions of the dynamics are generated with a simple dynamic inversion-based feedback controller. Empirical basis functions are designed using the "proper orthogonal decomposition" (POD) technique and the snapshot solutions. A low-order nonlinear lumped parameter system to characterize the infinite dimensional system is obtained by carrying out a Galerkin projection. An ADP-based neurocontroller with a dual heuristic programming (DHP) formulation is obtained with a single-network-adaptive-critic (SNAC) controller for this approximate nonlinear model. Actual control in the original domain is calculated with the same POD basis functions through a reverse mapping. Further contribution of this paper includes development of an online robust neurocontroller to account for unmodeled dynamics and parametric uncertainties inherent in such a complex dynamic system. A neural network (NN) weight update rule that guarantees boundedness of the weights and relaxes the need for persistence of excitation (PE) condition is presented. Simulation studies show that in a fairly extensive but compact domain, any desired temperature profile can be achieved starting from any initial temperature profile. Therefore, the ADP and NN-based controllers appear to have the potential to become controller synthesis tools for nonlinear distributed parameter systems.

Model Hamiltonians for nonlinear optical properties of conjugated polymers

Quantum cell models for delocalized electrons provide a unified approach to the large NLO responses of conjugated polymers and pi-pi* spectra of conjugated molecules. We discuss exact NLO coefficients of infinite chains with noninteracting pi-electrons and finite chains with molecular Coulomb interactions V(R) in order to compare exact and self-consistent-field results, to follow the evolution from molecular to polymeric responses, and to model vibronic contributions in third-harmonic-generation spectra. We relate polymer fluorescence to the alternation delta of transfer integrals t(1+/-delta) along the chain and discuss correlated excited states and energy thresholds of conjugated polymers.

Optimal control of a stochastic hybrid system with discounted cost

We address the optimal control problem of a very general stochastic hybrid system with both autonomous and impulsive jumps. The planning horizon is infinite and we use the discounted-cost criterion for performance evaluation. Under certain assumptions, we show the existence of an optimal control. We then derive the quasivariational inequalities satisfied by the value function and establish well-posedness. Finally, we prove the usual verification theorem of dynamic programming.

Synthesis of nonlinear controller to recover an unstable aircraft from poststall regime

Dynamics of the aircraft configuration considered in this paper show a unique characteristic in that there are no stable attractors in the entire high angle-of-attack flight envelope. As a result, once the aircraft has departed from the normal flight regime, no standard technique can be applied to recover the aircraft. In this paper, using feedback linearization technique, a nonlinear controller is designed at high angles of attack, which is engaged after the aircraft departs from normal flight regime. This controller stabilizes the aircraft into a stable spin. Then a set of synthetic pilot inputs is applied to cause an automatic transition from the spin equilibrium to low angles of attack where the second controller is connected. This controller is a normal gain-scheduled controller designed to have a large domain of attraction at low angles of attack. It traps the aircraft into a low angle-of-attack level flight. This entire concept of recovery has been verified using six-degrees-of-freedom nonlinear simulation. Feedback linearization technique used to design a controller ensures internal stability only if the nonlinear plant has stable zero dynamics. Because zero dynamics depend on the selection of outputs, a new method of choosing outputs is described to obtain a plant that has stable zero dynamics. Certain important aspects pertaining to the implementation of a feedback linearization-based controller are also discussed.

Non-Fermi-liquid theory for disordered metals near two dimensions

We consider the Finkelstein action describing a system of spin-polarized or spinless electrons in 2+2epsilon dimensions, in the presence of disorder as well as the Coulomb interactions. We extend the renormalization-group analysis of our previous work and evaluate the metal-insulator transition of the electron gas to second order in an epsilon expansion. We obtain the complete scaling behavior of physical observables like the conductivity and the specific heat with varying frequency, temperature, and/or electron density. We extend the results for the interacting electron gas in 2+2epsilon dimensions to include the quantum critical behavior of the plateau transitions in the quantum Hall regime. Although these transitions have a very different microscopic origin and are controlled by a topological term in the action (theta term), the quantum critical behavior is in many ways the same in both cases. We show that the two independent critical exponents of the quantum Hall plateau transitions, previously denoted as nu and p, control not only the scaling behavior of the conductances sigma(xx) and sigma(xy) at finite temperatures T, but also the non-Fermi-liquid behavior of the specific heat (c(v)proportional toT(p)). To extract the numerical values of nu and p it is necessary to extend the experiments on transport to include the specific heat of the electron gas.

Nonlinear measures of QT interval series: novel indices of cardiac repolarization lability: MEDqthr and LLEqthr

In this study, we investigated nonlinear measures of chaos of QT interval time series in 28 normal control subjects, 36 patients with panic disorder and 18 patients with major depression in supine and standing postures. We obtained the minimum embedding dimension (MED) and the largest Lyapunov exponent (LLE) of instantaneous heart rate (HR) and QT interval series. MED quantifies the system's complexity and LLE predictability. There was a significantly lower MED and a significantly increased LLE of QT interval time series in patients. Most importantly, nonlinear indices of QT/HR time series, MEDqthr (MED of QT/HR) and LLEqthr (LLE of QT/HR), were highly significantly different between controls and both patient groups in either posture. Results remained the same even after adjusting for age. The increased LLE of QT interval time, series in patients with anxiety and depression is in line with our previous findings of higher QTvi (QT variability index, a log ratio of QT variability corrected for mean QT squared divided by heart rate variability corrected for mean heart rate squared) in these patients, using linear techniques. Increased LLEqthr (LLE of QT/HR) may be a more sensitive tool to study cardiac repolarization and a valuable addition to the time domain measures such as QTvi. This is especially important in light of the finding that LLEqthr correlated poorly and nonsignificantly with QTvi. These findings suggest an increase in relative cardiac sympathetic activity and a decrease in certain aspects of cardiac vagal function in patients with anxiety as well as depression. The lack of correlation between QTvi and LLEqthr suggests that this nonlinear index is a valuable addition to the linear measures. These findings may also help to explain the higher incidence of cardiovascular mortality in patients with anxiety and depressive disorders. (C) 2002 Elsevier Science Ireland Ltd. All rights reserved.

Bit Steering In The Minimization Of Control Memory In Microprogrammed Digital-Computers

This correspondence presents an algorithm for microprogram control memory width minimization with the bit steering technique. The necessary and sufficient conditions to detect the steerability of two mutually exclusive sets of microcommands are established. The algorithm encodes the microcommands of the sets with a bit steering common part and also extends the theory to multiple (more than two) sets of microcommands.

Geometrically Nonlinear Dynamics of Composite Four-Bar Mechanisms

This work intends to demonstrate the importance of geometrically nonlinear crosssectional analysis of certain composite beam-based four-bar mechanisms in predicting system dynamic characteristics. All component bars of the mechanism are made of fiber reinforced laminates and have thin rectangular cross-sections. They could, in general, be pre-twisted and/or possess initial curvature, either by design or by defect. They are linked to each other by means of revolute joints. We restrict ourselves to linear materials with small strains within each elastic body (beam). Each component of the mechanism is modeled as a beam based on geometrically nonlinear 3-D elasticity theory. The component problems are thus split into 2-D analyses of reference beam cross-sections and nonlinear 1-D analyses along the four beam reference curves. For thin rectangular cross-sections considered here, the 2-D cross-sectional nonlinearity is overwhelming. This can be perceived from the fact that such sections constitute a limiting case between thin-walled open and closed sections, thus inviting the nonlinear phenomena observed in both. The strong elastic couplings of anisotropic composite laminates complicate the model further. However, a powerful mathematical tool called the Variational Asymptotic Method (VAM) not only enables such a dimensional reduction, but also provides asymptotically correct analytical solutions to the nonlinear cross-sectional analysis. Such closed-form solutions are used here in conjunction with numerical techniques for the rest of the problem to predict multi-body dynamic responses, more quickly and accurately than would otherwise be possible. The analysis methodology can be viewed as a three-step procedure: First, the cross-sectional properties of each bar of the mechanism is determined analytically based on an asymptotic procedure, starting from Classical Laminated Shell Theory (CLST) and taking advantage of its thin strip geometry. Second, the dynamic response of the nonlinear, flexible fourbar mechanism is simulated by treating each bar as a 1-D beam, discretized using finite elements, and employing energy-preserving and -decaying time integration schemes for unconditional stability. Finally, local 3-D deformations and stresses in the entire system are recovered, based on the 1-D responses predicted in the previous step. With the model, tools and procedure in place, we shall attempt to identify and investigate a few problems where the cross-sectional nonlinearities are significant. This will be carried out by varying stacking sequences and material properties, and speculating on the dominating diagonal and coupling terms in the closed-form nonlinear beam stiffness matrix. Numerical examples will be presented and results from this analysis will be compared with those available in the literature, for linear cross-sectional analysis and isotropic materials as special cases.

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.