Computational mechanisms of sensorimotor control.

In order to generate skilled and efficient actions, the motor system must find solutions to several problems inherent in sensorimotor control, including nonlinearity, nonstationarity, delays, redundancy, uncertainty, and noise. We review these problems and five computational mechanisms that the brain may use to limit their deleterious effects: optimal feedback control, impedance control, predictive control, Bayesian decision theory, and sensorimotor learning. Together, these computational mechanisms allow skilled and fluent sensorimotor behavior.

广义预测控制方法在网络遥操作机器人系统中的应用

Internet网络的时变时延及网络数据丢包严重影响了遥操作机器人系统的操作性能,甚至造成系统不稳定。为了解决这一问题,提出一种新的基于Internet的遥操作机器人系统控制结构。通过在主端对给定信息加入时间标签获得过去的系统回路时延,采用多元线性回归算法,预测下一时刻系统回路时延,然后在从端设计一个广义预测控制器控制远端机器人,从而改善时变时延对系统性能的影响。应用广义预测控制器产生的冗余控制信息,降低了网络数据丢包对系统的影响。最后根据预测控制稳定性定理,推导出系统的稳定性条件。仿真试验结果表明,该方法能有效解决时变时延以及网络数据丢包引起的性能下降问题。

Neural modelling, control and optimisation of an industrial grinding process

This paper describes the development of neural model-based control strategies for the optimisation of an industrial aluminium substrate disk grinding process. The grindstone removal rate varies considerably over a stone life and is a highly nonlinear function of process variables. Using historical grindstone performance data, a NARX-based neural network model is developed. This model is then used to implement a direct inverse controller and an internal model controller based on the process settings and previous removal rates. Preliminary plant investigations show that thickness defects can be reduced by 50% or more, compared to other schemes employed. (c) 2004 Elsevier Ltd. All rights reserved.

Evaluating the impact of network density, hidden nodes and capture effect for throughput guarantee in multi-hop wireless networks

To optimize the performance of wireless networks, one needs to consider the impact of key factors such as interference from hidden nodes, the capture effect, the network density and network conditions (saturated versus non-saturated). In this research, our goal is to quantify the impact of these factors and to propose effective mechanisms and algorithms for throughput guarantees in multi-hop wireless networks. For this purpose, we have developed a model that takes into account all these key factors, based on which an admission control algorithm and an end-to-end available bandwidth estimation algorithm are proposed. Given the necessary network information and traffic demands as inputs, these algorithms are able to provide predictive control via an iterative approach. Evaluations using analytical comparison with simulations as well as existing research show that the proposed model and algorithms are accurate and effective.

A Soft Sensor for Viscosity Control of Polymer Extrusion

Viscosity represents a key indicator of product quality in polymer extrusion but has traditionally been difficult to measure in-process in real-time. An innovative, yet simple, solution to this problem is proposed by a Prediction-Feedback observer mechanism. A `Prediction' model based on the operating conditions generates an open-loop estimate of the melt viscosity; this estimate is used as an input to a second, `Feedback' model to predict the pressure of the system. The pressure value is compared to the actual measured melt pressure and the error used to correct the viscosity estimate. The Prediction model captures the relationship between the operating conditions and the resulting melt viscosity and as such describes the specific material behavior. The Feedback model on the other hand describes the fundamental physical relationship between viscosity and extruder pressure and is a function of the machine geometry. The resulting system yields viscosity estimates within 1% error, shows excellent disturbance rejection properties and can be directly applied to model-based control. This is of major significance to achieving higher quality and reducing waste and set-up times in the polymer extrusion industry.

A greenhouse climate multivariable predictive controller

A multivariable predictive controller was implemented to regulate the air temperature, humidity and CO2 concentration for a greenhouse located in the north of Portugal. The controller outputs are computed in order to optimise the future behaviour of the greenhouse environment, concerning the set-point accuracy and the minimization of energy inputs.

Retificador monofásico com fator de potência quase unitário

Dissertação para a obtenção do grau de Mestre em Engenharia Eletrotécnica Ramo de Automação e Eletrónica Industrial

Nonlinear dynamics of the patient’s response to drug effect during general anesthesia

In today’s healthcare paradigm, optimal sedation during anesthesia plays an important role both in patient welfare and in the socio-economic context. For the closed-loop control of general anesthesia, two drugs have proven to have stable, rapid onset times: propofol and remifentanil. These drugs are related to their effect in the bispectral index, a measure of EEG signal. In this paper wavelet time–frequency analysis is used to extract useful information from the clinical signals, since they are time-varying and mark important changes in patient’s response to drug dose. Model based predictive control algorithms are employed to regulate the depth of sedation by manipulating these two drugs. The results of identification from real data and the simulation of the closed loop control performance suggest that the proposed approach can bring an improvement of 9% in overall robustness and may be suitable for clinical practice.

Nonlinear dynamics of the patient’s response to drug effect during general anesthesia

In today’s healthcare paradigm, optimal sedation during anesthesia plays an important role both in patient welfare and in the socio-economic context. For the closed-loop control of general anesthesia, two drugs have proven to have stable, rapid onset times: propofol and remifentanil. These drugs are related to their effect in the bispectral index, a measure of EEG signal. In this paper wavelet time–frequency analysis is used to extract useful information from the clinical signals, since they are time-varying and mark important changes in patient’s response to drug dose. Model based predictive control algorithms are employed to regulate the depth of sedation by manipulating these two drugs. The results of identification from real data and the simulation of the closed loop control performance suggest that the proposed approach can bring an improvement of 9% in overall robustness and may be suitable for clinical practice.

Facteurs associés à la résilience des aidantes familiales d’un parent âgé en perte d’autonomie à domicile au Liban

Avec l’avancement en âge, les personnes âgées qui vivent à domicile ont besoin du soutien des membres de leur entourage, notamment d’un aidant familial dont le rôle n’est toutefois pas sans conséquence sur sa santé. Les écrits empiriques ont montré que certains aidants sont résilients, c’est-à-dire qu’ils s’adaptent à leur situation et continuent leur développement. Toutefois, aucune étude n’a été effectuée au Liban auprès des aidantes familiales pour expliquer la résilience dans ce contexte et, plus spécifiquement, pour déterminer les facteurs qui pourraient l’influencer. Cette étude à devis corrélationnel de prédiction avait pour but de vérifier certaines des relations postulées par un modèle empirique découlant des écrits, soit la contribution de facteurs personnels (stratégies de coping et auto-efficacité) et de facteurs contextuels (relations familiales, perception du soutien de l’entourage, et sens accordé au « prendre soin »),à la résilience des aidantes familiales libanaises qui prennent soin d’un proche âgé à domicile. L’étude a été effectuée au Liban auprès d’un échantillon de convenance composé de 140 aidantes familiales principales cohabitant à domicile avec un parent âgé de 65 ans et plus ayant une perte d’autonomie fonctionnelle ou cognitive. La collecte des données a été réalisée en arabe en utilisant un guide d’entrevue standardisé regroupant des instruments nord-américains traduits selon la méthode de traduction inversée parallèle, de même qu’une question ouverte portant sur la perception des aidantes de la résilience, soit des facteurs qui les aident à continuer à prendre soin de leur proche âgé tout en continuant à se développer. Une analyse de régression hiérarchique a permis de vérifier la contribution unique des facteurs personnels et contextuels à expliquer la résilience des aidantes familiales, en contrôlant pour l’âge et le niveau de scolarité des aidantes et pour le niveau de perte d’autonomie et la fréquence des comportements dysfonctionnels de leurs parents âgés. Une analyse de contenu a permis de décrire la perception des aidantes eu égard à la résilience. Les résultats ont montré que le modèle empirique, incluant les variables de contrôle explique 54% de la variance de la résilience et que quatre des facteurs considérés, soit les stratégies de coping centrées sur le problème, les stratégies de coping centrées sur les émotions, le sentiment d’auto-efficacité et le sens du « prendre soin » ont une contribution statistiquement significative à la résilience des aidantes. Parmi ces quatre facteurs, le sens du « prendre soin » et le sentiment d’auto-efficacité expliquent davantage de variance, soit 11% et 5% respectivement. L’analyse qualitative du discours des aidantes a montré qu’elles prennent soin de leur proche âgé surtout par souci de réciprocité, mais également parce qu’il s’agit d’un membre de la famille et par respect pour Dieu. Ce sont par ailleurs leurs croyances et la satisfaction liée au prendre soin qui les aident à continuer et à se développer. Cette étude offre une meilleure compréhension du concept de la résilience des aidantes familiales au Liban et de certains facteurs qui en sont des prédicteurs significatifs. Elle offre des pistes pour l’intervention infirmière dans le but de promouvoir la santé de la personne/famille en tant que partenaire de soins. Des recommandations pour la pratique, la formation et la recherche sont proposées.

Prediction of glucose excursions under uncertain parameters and food intake in intensive insulin therapy for type 1 diabetes mellitus

Considering the difficulty in the insulin dosage selection and the problem of hyper- and hypoglycaemia episodes in type 1 diabetes, dosage-aid systems appear as tremendously helpful for these patients. A model-based approach to this problem must unavoidably consider uncertainty sources such as the large intra-patient variability and food intake. This work addresses the prediction of glycaemia for a given insulin therapy face to parametric and input uncertainty, by means of modal interval analysis. As result, a band containing all possible glucose excursions suffered by the patient for the given uncertainty is obtained. From it, a safer prediction of possible hyper- and hypoglycaemia episodes can be calculated

Probabilistic models to assist maintenance of multiple instruments

The paper discusses maintenance challenges of organisations with a huge number of devices and proposes the use of probabilistic models to assist monitoring and maintenance planning. The proposal assumes connectivity of instruments to report relevant features for monitoring. Also, the existence of enough historical registers with diagnosed breakdowns is required to make probabilistic models reliable and useful for predictive maintenance strategies based on them. Regular Markov models based on estimated failure and repair rates are proposed to calculate the availability of the instruments and Dynamic Bayesian Networks are proposed to model cause-effect relationships to trigger predictive maintenance services based on the influence between observed features and previously documented diagnostics

Prevalencia de alteraciones audiométricas y su relación con exposición a ruido ocupacional y extra ocupacional, en una cohorte de trabajadores de Santander, Colombia, Años 2014-2015

La hipoacusia neurosensorial inducida por ruido (HNIR) definida como la pérdida de la capacidad auditiva secundaria a la exposición ocupacional continua o intermitente a ruido en el lugar de trabajo, es la cuarta enfermedad ocupacional en prevalencia en Colombia. Objetivo: Determinar la prevalencia de alteraciones audiométricas y su relación con exposición a ruido ocupacional y extra ocupacional, en un grupo de trabajadores que asistieron a una IPS de la ciudad de Bucaramanga en el periodo comprendido entre agosto de 2014 y agosto de 2015. Diseño: Se realizó un estudio de corte transversal con 2725 registros de las historias clínicas de fonoaudiología realizadas a los trabajadores con audiometría tonal como parte de los exámenes ocupacionales, entre el 1 de agosto de 2014 al 31 de agosto de 2015, en una Institución Prestadora de Salud (IPS) ocupacional, en la ciudad de Bucaramanga, Santander. Resultados: El 17.2% de los trabajadores presentaron alteraciones audiométricas, de estos el 33,1%, cumplió con los criterios definidos en el estudio para ser calificados como casos probables de hipoacusia neurosensorial inducida por ruido, de estos el 87,8% fueron clasificados como leves, 10,8% como moderados y el 1,2% como moderado severo, no se registraron casos de HNIR severa o profunda. El 62,7% se clasificaron como no HNIR y el 4% correspondió a hipoacusias con afectación de frecuencias conversacionales. Conclusiones: Al aplicar un modelo de regresión logística para controlar las variables de confusión, no se encontró asociación con ninguna de las variables anteriormente descritas. A pesar de esto, existe suficiente evidencia de la relación entre algunas ocupaciones y la HNIR.

Weighted input predictive controller

A discrete-time algorithm is presented which is based on a predictive control scheme in the form of dynamic matrix control. A set of control inputs are calculated and made available at each time instant, the actual input applied being a weighted summation of the inputs within the set. The algorithm is directly applicable in a self-tuning format and is therefore suitable for slowly time-varying systems in a noisy environment.

Adaptive control: an insight

In this article, an overview is given of some of the more common approaches taken in applying adaptive control. Gain scheduling, model reference control and self-tuning control are all discussed and in each case suggestions are given for further reading.