Dynamic control of laser-produced proton beams

The emission characteristics of intense laser driven protons are controlled using ultrastrong (of the order of 10(9) V/m) electrostatic fields varying on a few ps time scale. The field structures are achieved by exploiting the high potential of the target (reaching multi-MV during the laser interaction). Suitably shaped targets result in a reduction in the proton beam divergence, and hence an increase in proton flux while preserving the high beam quality. The peak focusing power and its temporal variation are shown to depend on the target characteristics, allowing for the collimation of the inherently highly divergent beam and the design of achromatic electrostatic lenses.

Dynamic control and enhancement of laser-accelerated protons using multiple laser pulses

The use of schemes involving multiple laser pulses to enhance and control the properties of beams of protons accelerated in ultra-intense laser irradiation of planar foil targets is discussed. Specifically, the schemes include the use of a second laser pulse to produce and control preplasma expansion of the target to enhance energy coupling to the proton beam; the use of a second laser pulse to drive shock deformation of the target to change the direction of the proton beam; and a scheme involving dual high intensity laser pulses to change the properties of the sheath field, with the aim of modifying the proton energy spectrum. An overview of our recent experimental and theoretical results is given. The overall aim of this work is to determine the extent to which the properties of the sheath-accelerated proton beam can be optically controlled, to enable beam delivery at high repetition rates. To cite this article: D.C. Carroll et al., C. R. Physique 10 (2009). (C) 2009 Academie des sciences. Published by Elsevier Masson SAS. All rights reserved.

Dynamic control of laser driven proton beams by exploiting self-generated, ultrashort electromagnetic pulses

As part of the ultrafast charge dynamics initiated by high intensity laser irradiations of solid targets,high amplitude EM pulses propagate away from the interaction point and are transported along anystalks and wires attached to the target. The propagation of these high amplitude pulses along a thinwire connected to a laser irradiated target was diagnosed via the proton radiography technique,measuring a pulse duration of 20 ps and a pulse velocity close to the speed of light. The strongelectric field associated with the EM pulse can be exploited for controlling dynamically the protonbeams produced from a laser-driven source. Chromatic divergence control of broadband laser drivenprotons (upto 75% reduction in divergence of >5 MeV protons) was obtained by winding the supportingwire around the proton beam axis to create a helical coil structure. In addition to providingfocussing and energy selection, the technique has the potential to post-accelerate the transiting protonsby the longitudinal component of the curved electric field lines produced by the helical coil lens.

Investigating autonomic control of the cardiovascular system: a battery of simple tests

Sympathetic and parasympathetic divisions of the autonomic nervous system constantly control the heart (sympathetic and parasympathetic divisions) and blood vessels (predominantly the sympathetic division) to maintain appropriate blood pressure and organ blood flow over sometimes widely varying conditions. This can be adversely affected by pathological conditions that can damage one or both branches of autonomic control. The set of teaching laboratory activities outlined here uses various interventions, namely, 1) the heart rate response to deep breathing, 2) the heart rate response to a Valsalva maneuver, 3) the heart rate response to standing, and 4) the blood pressure response to standing, that cause fairly predictable disturbances in cardiovascular parameters in normal circumstances, which serve to demonstrate the dynamic control of the cardiovascular system by autonomic nerves. These tests are also used clinically to help investigate potential damage to this control.

Dynamic Multivariate Statistical Process Control using Subspace Identification

This paper points out a serious flaw in dynamic multivariate statistical process control (MSPC). The principal component analysis of a linear time series model that is employed to capture auto- and cross-correlation in recorded data may produce a considerable number of variables to be analysed. To give a dynamic representation of the data (based on variable correlation) and circumvent the production of a large time-series structure, a linear state space model is used here instead. The paper demonstrates that incorporating a state space model, the number of variables to be analysed dynamically can be considerably reduced, compared to conventional dynamic MSPC techniques.

A novel approach to dynamic modelling of polymer extrusion for improved process control

Polymer extrusion is a complex process and the availability of good dynamic models is key for improved system operation. Previous modelling attempts have failed adequately to capture the non-linearities of the process or prove too complex for control applications. This work presents a novel approach to the problem by the modelling of extrusion viscosity and pressure, adopting a grey box modelling technique that combines mechanistic knowledge with empirical data using a genetic algorithm approach. The models are shown to outperform those of a much higher order generated by a conventional black box technique while providing insight into the underlying processes at work within the extruder.

Identification of dynamic systems under closed-loop control

This paper introduces a novel modelling framework for identifying dynamic models of systems that are under feedback control. These models are identified under closed-loop conditions and produce a joint representation that includes both the plant and controller models in state space form. The joint plant/controller model is identified using subspace model identification (SMI), which is followed by the separation of the plant model from the identified one. Compared to previous research, this work (i) proposes a new modelling framework for identifying closed-loop systems, (ii) introduces a generic structure to represent the controller and (iii) explains how that the new framework gives rise to a simplified determination of the plant models. In contrast, the use of the conventional modelling approach renders the separation of the plant model a difficult task. The benefits of using the new model method are demonstrated using a number of application studies.

A Question of Legitimacy? A Dynamic Perspective on Multinational Firm Control

The control and coordination of a network of geographically and culturally dispersed subsidiaries is one of the most prominent challenges in international management. However, many empirical findings on the effectiveness of various control mechanisms and combinations thereof are still counterintuitive. This study uses longitudinal case studies and cross-sectional interview data to extend control theory by examining why, how, and in what sequence large multinational firms (MNCs) implement controls in their networks of foreign subsidiaries. Our analysis draws from literature on institutional theory, embeddedness, and organizational power to demonstrate that MNC headquarters need to overcome institutional duality when implementing their controls abroad. We find that headquarters do so by using social controls, primarily as a way of legitimizing and institutionalizing their process and output controls that are implemented subsequently.

Multiloop robust H∞ control design based on the dynamic PLS approach to chemical processes

In this paper, a multiloop robust control strategy is proposed based on H∞ control and a partial least squares (PLS) model (H∞_PLS) for multivariable chemical processes. It is developed especially for multivariable systems in ill-conditioned plants and non-square systems. The advantage of PLS is to extract the strongest relationship between the input and the output variables in the reduced space of the latent variable model rather than in the original space of the highly dimensional variables. Without conventional decouplers, the dynamic PLS framework automatically decomposes the MIMO process into multiple single-loop systems in the PLS subspace so that the controller design can be simplified. Since plant/model mismatch is almost inevitable in practical applications, to enhance the robustness of this control system, the controllers based on the H∞ mixed sensitivity problem are designed in the PLS latent subspace. The feasibility and the effectiveness of the proposed approach are illustrated by the simulation results of a distillation column and a mixing tank process. Comparisons between H∞_PLS control and conventional individual control (either H∞ control or PLS control only) are also made

Proprioceptive acuity predicts muscle co-contraction of the tibalis anterior and gastrocnemius medialis in older adults’ dynamic postural control

Older adults use a different muscle strategy to cope with postural instability, in which they ‘co-contract’ the muscles around the ankle joint. It has been suggested that this is a compensatory response to age-related proprioceptive decline however this view has never been assessed directly. The current study investigated the association between proprioceptive acuity and muscle co-contraction in older adults. We compared muscle activity, by recording surface EMG from the bilateral tibalis anterior and gastrocnemius medialis muscles, in young (aged 18-34) and older adults (aged 65-82) during postural assessment on a fixed and sway-referenced surface at age-equivalent levels of sway. We performed correlations between muscle activity and proprioceptive acuity, which was assessed using an active contralateral matching task. Despite successfully inducing similar levels of sway in the two age groups, older adults still showed higher muscle co-contraction. A stepwise regression analysis showed that proprioceptive acuity measured using variable error was the best predictor of muscle co-contraction in older adults. However, despite suggestions from previous research, proprioceptive error and muscle co-contraction were negatively correlated in older adults, suggesting that better proprioceptive acuity predicts more co-contraction. Overall, these results suggest that although muscle co-contraction may be an age-specific strategy used by older adults, it is not to compensate for age-related proprioceptive deficits.

A two-stage algorithm for identification of nonlinear dynamic systems

This paper investigates the two-stage stepwise identification for a class of nonlinear dynamic systems that can be described by linear-in-the-parameters models, and the model has to be built from a very large pool of basis functions or model terms. The main objective is to improve the compactness of the model that is obtained by the forward stepwise methods, while retaining the computational efficiency. The proposed algorithm first generates an initial model using a forward stepwise procedure. The significance of each selected term is then reviewed at the second stage and all insignificant ones are replaced, resulting in an optimised compact model with significantly improved performance. The main contribution of this paper is that these two stages are performed within a well-defined regression context, leading to significantly reduced computational complexity. The efficiency of the algorithm is confirmed by the computational complexity analysis, and its effectiveness is demonstrated by the simulation results.

Fault reconstruction in linear dynamic systems using multivariate statistics

Treasure et al. (2004) recently proposed a new sub space-monitoring technique, based on the N4SID algorithm, within the multivariate statistical process control framework. This dynamic-monitoring method requires considerably fewer variables to be analysed when compared with dynamic principal component analysis (PCA). The contribution charts and variable reconstruction, traditionally employed for static PCA, are analysed in a dynamic context. The contribution charts and variable reconstruction may be affected by the ratio of the number of retained components to the total number of analysed variables. Particular problems arise if this ratio is large and a new reconstruction chart is introduced to overcome these. The utility of such a dynamic contribution chart and variable reconstruction is shown in a simulation and by application to industrial data from a distillation unit.