METHOD FOR ASSESSING EFFECTS OF CIRCUMFERENTIAL FLOW DISTORTION ON COMPRESSOR STABILITY.

This paper describes the development of a new analysis to predict the onset of flow instability for an axial compressor operating in a circumferentially distorted inlet flow. A relatively simple model is used to examine the influence of various distortions in setting this instability point. It is found that the model reproduces known experimental trends for the loss of stability margin with increasing distortion amplitude and with changes in reduced frequency.

Effects of rotating inlet distortion on multistage compressor stability

In multi-spool engines, rotating stall in an upstream compressor will impose a rotating distortion on the downstream compressor, thereby affecting its stability margin. In this paper experiments are described in which this effect was simulated by a rotating screen upstream of several multistage low-speed compressors. The measurements are complemented by, and compared with, a theoretical model of multistage compressor response to speed and direction of rotation of an inlet distortion. For co-rotating distortions (i.e., distortions rotating in the same direction as rotor rotation), experiments show that the compressors exhibited significant loss in stability margin and that they could be divided into two groups according to their response. The first group exhibited a single peak in stall margin degradation when the distortion speed corresponded to roughly 50% of rotor speed. The second group showed two peaks in stall margin degradation corresponding to distortion speeds of approximately 25-35% and 70-75% of rotor speed. These new results demonstrate that multistage compressors can have more than a single resonant response. Detailed measurements suggest that the two types of behavior are linked to differences between the stall inception processes observed for the two groups of compressors and that a direct connection thus exists between the observed forced response and the unsteady flow phenomena at stall onset. For counter-rotational distortions, all the compressors tested showed minimal loss of stability margin. The results imply that counter-rotation of the fan and core compressor, or LP and HP compressors, could be a worthwhile design choice. Calculations based on the two-dimensional theoretical model show excellent agreement for the compressors which had a single peak for stall margin degradation. We take this first-of-a-kind comparison as showing that the model, though simplified, captures the essential fluid dynamic features of the phenomena. Agreement is not good for compressors which had two peaks in the curve of stall margin shift versus distortion rotation speed. The discrepancy is attributed to the three-dimensional and short length scale nature of the stall inception process in these machines; this includes phenomena that have not yet been addressed in any model.

IGBT series connection under active voltage control

In this paper an Active Voltage Control (AVC) technique is presented, for series connection of insulated-gate-bipolar-transistors (IGBT) and control of diode recovery. The AVC technique can control the switching trajectory of an IGBT according to a pre-set reference signal. In series connections, every series connected IGBT follows the reference and so that the dynamic voltage sharing is achieved. For the static voltage balancing, the AVC technique can clamp the highest collector-to-emitter voltage to a pre-set clamping voltage level. By selecting the value of the clamping voltage, the difference among series connected IGBTs can be controlled in an accepted range. Another key advantage for AVC is that by changing the reference signal at turn-on, the diode recovery can be optimized. © 2011 EPE Association - European Power Electr.

IGBT series connection under Active Voltage Control with temporary clamp

This paper presents the use of an Active Voltage Control (AVC) technique for balancing the voltages in a series connection of Insulated Gate Bipolar Transistors (IGBTs). The AVC technique can control the switching trajectory of an IGBT according to a pre-set reference signal. In series connections, every series connected IGBT follows the reference and so that the dynamic voltage sharing is achieved. For the static voltage balancing, a temporary clamp technique is introduced. The temporary clamp technique clamps the collector-emitter voltage of all the series connected IGBTs at the ideal voltage so that the IGBTs will share the voltage evenly. © 2012 IEEE.

The Effect of Inlet Guide Vanes on Inlet Flow Distortion Transfer and Transonic Fan Stability

An investigation was carried out into the effects of variable inlet guide vanes (VIGVs) on the performance and stability margin of a transonic fan in the presence of inlet flow distortion. The study was carried out using computational fluid dynamics (CFD) and validated with experimental data. The capability of CFD to predict the changes in performance with or without VIGVs in the presence of an inlet flow distortion is assessed. Results show that the VIGVs improve the performance and stability margin and do so by reducing the amount of swirl at inlet to the rotor component of the fan.

Generalization in Adaptation to Stable and Unstable Dynamics

Humans skillfully manipulate objects and tools despite the inherent instability. In order to succeed at these tasks, the sensorimotor control system must build an internal representation of both the force and mechanical impedance. As it is not practical to either learn or store motor commands for every possible future action, the sensorimotor control system generalizes a control strategy for a range of movements based on learning performed over a set of movements. Here, we introduce a computational model for this learning and generalization, which specifies how to learn feedforward muscle activity in a function of the state space. Specifically, by incorporating co-activation as a function of error into the feedback command, we are able to derive an algorithm from a gradient descent minimization of motion error and effort, subject to maintaining a stability margin. This algorithm can be used to learn to coordinate any of a variety of motor primitives such as force fields, muscle synergies, physical models or artificial neural networks. This model for human learning and generalization is able to adapt to both stable and unstable dynamics, and provides a controller for generating efficient adaptive motor behavior in robots. Simulation results exhibit predictions consistent with all experiments on learning of novel dynamics requiring adaptation of force and impedance, and enable us to re-examine some of the previous interpretations of experiments on generalization. © 2012 Kadiallah et al.

Lyapunov's stability and operational margin of grid-connected photovoltaic modules

Analyses of photovoltaic power generation based on Lyapunov's theorems are presented. The characteristics of the photovoltaic module and the power conditioning unit are analyzed in order to establish energy functions that assess the stability of solutions and define safe regions of operation. Furthermore, it is shown that grid-connected photovoltaic modules driven at maximum power may become unstable under normal grid transients. In such cases, stability can be maintained by allowing an operational margin defined as the energy difference between the stable and the unstable solutions of the system. Simulations show that modules cope well with grid transients when a sufficiently large margin is used.

Uniform stability of a particle approximation of the optimal filter derivative

Sequential Monte Carlo methods, also known as particle methods, are a widely used set of computational tools for inference in non-linear non-Gaussian state-space models. In many applications it may be necessary to compute the sensitivity, or derivative, of the optimal filter with respect to the static parameters of the state-space model; for instance, in order to obtain maximum likelihood model parameters of interest, or to compute the optimal controller in an optimal control problem. In Poyiadjis et al. [2011] an original particle algorithm to compute the filter derivative was proposed and it was shown using numerical examples that the particle estimate was numerically stable in the sense that it did not deteriorate over time. In this paper we substantiate this claim with a detailed theoretical study. Lp bounds and a central limit theorem for this particle approximation of the filter derivative are presented. It is further shown that under mixing conditions these Lp bounds and the asymptotic variance characterized by the central limit theorem are uniformly bounded with respect to the time index. We demon- strate the performance predicted by theory with several numerical examples. We also use the particle approximation of the filter derivative to perform online maximum likelihood parameter estimation for a stochastic volatility model.