Presence Of Strong Perturbations Research Articles

Emulating bistabilities in turning to devise gain tuning strategies to actively damp them using a hardware-in-the-loop simulator

Bistabilities in turning are characterized by the process being stable for small perturbations and unstable for larger ones. These bistabilities occur due to nonlinearities in cutting force characteristics. Characterizing these bistabilities can guide selection of cutting parameters to lie outside these zones of conditional instabilities. However, if cutting is targeted in the bistable regions, or in regions that are globally unstable, active damping methods may need to be pursued to improve the stability envelopes. Since gain tuning for active damping of chatter vibrations is usually based on linear stability analysis, it would be useful to know if those gains are adequate for damping chatter in the presence of bistabilities that occur in processes prone to strong perturbations. However, experimentation on machines to investigate these bistabilities and/or tune gains to meet targeted productivity levels with active damping is difficult due to the destructive nature of chatter. This paper hence discusses the use of a hardware-in-the-loop (HiL) simulator to emulate bistabilities and to serve as a test bench for gain tuning in the presence of bistabilities. The HiL simulator has a hardware layer comprising a flexure representing a flexible workpiece, and two actuators. One emulates the cutting force calculated in real-time in the software layer. Another serves as the active damper operating with a velocity feedback control law. Bistabilities for three different nonlinear force models are experimentally illustrated on this HiL simulator. We show that active damping can stabilize these bistable regions. Since the width of the bistable regions depend on the nonlinear force characteristics, our investigations reveal that gains must be tuned for the force model and the static chip thickness under consideration. These results are useful and can instruct active damping strategies during more realistic cutting processes with nonlinear force characteristics that exhibit conditional instabilities in the presence of strong perturbations.

Soft Quantum Control for Highly Selective Interactions among Joint Quantum Systems.

We propose a quantum control scheme aimed at interacting systems that gives rise to highly selective coupling among their near-to-resonance constituents. Our protocol implements temporal control of the interaction strength, switching it on and off again adiabatically. This soft temporal modulation significantly suppresses off-resonant contributions in the interactions. Among the applications of our method we show that it allows us to perform an efficient rotating-wave approximation in a wide parameter regime, the elimination of side peaks in quantum sensing experiments, and selective high-fidelity entanglement gates on nuclear spins with close frequencies. We apply our theory to nitrogen-vacancy centers in diamond and demonstrate the possibility for the detection of weak electron-nuclear coupling under the presence of strong perturbations.

An online secondary path modeling method with regularized step size and self-tuning power scheduling.

This paper investigates the active noise control algorithms and improves them by using online secondary path modeling. The proposed method uses three adaptive filters to track the convergence of the system as well as reduce the target noise. By theoretical analysis, the optimized step size and injected random noise gain are derived. The step size is varied according to the convergence of three adaptive filters and the gain of injected random noise is proportional to the power of modeling error, which makes the method more stable even in the presence of strong perturbation. Compared with previous methods, the proposed method improves the convergence rate and estimation accuracy for both the active control system and the secondary path modeling process with less increase of computational complexity. The simulation results verify the above analysis by controlling three different kinds of noise.

High resolution coherent three dimensional spectroscopy of NO2.

Expansion from coherent 2D spectroscopy to coherent 3D spectroscopy can provide significant advantages when studying molecules that have heavily perturbed energy levels. This paper illustrates such advantages by demonstrating how high resolution coherent 3D (HRC3D) spectroscopy can be used to study a portion of the visible spectrum of nitrogen dioxide. High resolution coherent 2D spectra usually contain rotational and vibrational patterns that are easy to analyze, but severe congestion and complexity preclude its effective use for many parts of the NO2 spectrum. HRC3D spectroscopy appears to be much more effective; multidimensional rotational and vibrational patterns produced by this new technique are easy to identify even in the presence of strong perturbations. A method for assigning peaks, which is based upon analyzing the resulting multidimensional patterns, has been developed. The higher level of multidimensionality is useful for reducing uncertainty in peak assignments, improving spectral resolution, providing simultaneous information on multiple levels and states, and predicting, verifying, and categorizing peaks.

THE ROLE OF ROTATION AND POLAR-CAP CURRENTS ON PULSAR RADIO EMISSION AND POLARIZATION

The perturbations such as rotation and PC--current have been believed to be greatly affecting the pulsar radio emission and polarization. The two effects have not been considered simultaneously in the literature, however, each one of these has been considered separately and deduced the picture by simply superposing them, but such an approach can lead to spurious results. Hence by considering pulsar rotation and PC--current perturbations together instead of one at a time we have developed a single particle curvature radiation model, which is expected to be much more realistic. By simulating a set of typical pulse profiles we have made an attempt to explain most of the observational results on pulsar radio emission and polarization. The model predicts that due to the perturbations leading side component can become either stronger or weaker than the corresponding trailing one in any given cone depending on the passage of sight line and modulation (nonuniform source distribution). Further we find that the phase delay of polarization angle inflection point with respect to the core component greatly depends upon the viewing geometry. The correlation between the sign reversal of circular polarization and the polarization angle swing in the case of core dominated pulsars become obscure once the perturbations and modulation become significant. However the correlation that the negative circular polarization associates with the increasing polarization angle and vice versa shows up very clearly in the case of conal-double pulsars. The `kinky' type distortions in polarization angle swing could be due to the incoherent superposition of modulated emissions in the presence of strong perturbations.

Robust Auxiliary-Noise-Power Scheduling in Active Noise Control Systems With Online Secondary Path Modeling

This paper deals with the auxiliary noise-based methods for active noise control (ANC) systems with online secondary path modeling (SPM). The proposed method comprises two adaptive filters: the modified Filtered-X normalized least-mean-square algorithm-based ANC filter, and the normalized least-mean-square algorithm-based SPM filter excited by auxiliary noise. The auxiliary noise injected for online SPM, degrades the noise-reduction performance of the ANC system. A two-stage gain scheduling strategy is proposed to vary power of the auxiliary noise. In the first stage the gain is varied on the basis of power of the error signal of SPM filter, and in the second stage the gain is varied on the basis of the correlation estimate of the two adjacent samples of the error signal of SPM filter. The main idea is to inject large-power auxiliary noise at the start up or when a change in the acoustic paths is detected, and to reduce the power as the system converges. The proposed method achieves a fast convergence of the SPM filter and gives a robust performance in the presence of strong perturbation in acoustic paths. Furthermore, the proposed method improves the noise-reduction performance at steady-state even in the presence of an uncorrelated disturbance at the error microphone. Moreover, the improved performance is achieved at a lower computational cost as compared with a recent method proposed in [A. Carini, and S. Malatini, “Optimal variable step-size NLMS algorithms with auxiliary noise power scheduling for feedforward active noise control,”IEEE Trans. Audio, Speech Lang. Process., vol. 16, no. 8, pp. 1383-1395, Nov. 2008]. Extensive simulations are carried out to verify the effectiveness of the proposed method.

A new neural network concept for the control of nuclear reactor systems

In this work the novel approach to artificial neural networks based on the design of task-specific networks and on a neuron model with multiple synapses developed by Baptista, Cabral and Soares (1998) is extended to accommodate external perturbations. As an example of this new development t he neural network is applied to control the fluid temperature of a natural circulation loop. The learning and the action processes are made through simulations. The natural circulation loop simulation model i s based on physical equations and on experimentally identified p arameters. The results s how that besides the e xcellent l earning capability and g eneralization, the new improvements are suitable to accommodate e xternal perturbations s o that t he network is able to maintain the controlled variable within allowable limits even in the presence of strong perturbations.