Fractional-order feedback control of a poorly damped system

This study presents the design of a fractional-order proportional-integral (FOPI) controller for a mass-spring-damper system which is poorly damped. A model based design technique is used to design a FOPI controller for this system. A good performance of the closed loop control of a high order oscillatory system, such as the mass-spring-damper system, is with traditional proportional-integral (PI) controllers difficult to achieve. Therefore, a comparison between a traditional PI controller and a FOPI controller is performed by simulation. The simulation results show that the FOPI controller outperforms the classical PI controller resulting in an increased damping of the oscillations while maintaining a reasonable control effort

A medical information system for monitoring respiratory function and related nonlinear dynamics

In this paper the nonlinear effects in the respiratory systems at low frequencies are measured and evaluated in healthy children and healthy adults. To this aim forced oscillations technique (FOT) has been used to non-invasively measure the lung tissue mechanics. FOT does not require any special effort from the patient in contrast with standardized tests where maneuvers are necessary. Hence, FOT is an ideal lung function test for extreme ages, more specifically children and elderly, given the simpleness of measurement technique. Hitherto, measurements at low frequencies (i.e. close to the breathing frequency similar to 0.3 Hz) have been invasively performed in sacrificed animals and on anesthetized humans. Here we measure in the frequency interval 0.1-2 Hz a total number of 94 volunteers (37 adults with ages between 25-35 years and 57 children with ages between 8-11 years). To evaluate the nonlinear contributions of the respiratory tissue, a novel T-index has been introduced. We have tested the hypothesis whether the nonlinear distortions are changing with growth/development of the respiratory tree and aim to quantify its dependence to biometric values. The results obtained indicate that the proposed index can differentiate between the two analyzed groups and that there is a dependence to age, height and weight. A medical information system may use this information to update predictions of respiratory function and provide aid in decision-making process of drug therapy

A fractional order impedance individualised model of nociceptor stimulation

This paper introduces a mathematical model and methodology for detecting and analysing nociceptor stimulation effects by means of non-invasive evaluation of the skin impedance in the hand palm. The derivation of the model is based on multi-scale physiological stages during perception of pain in awake individuals and contains elements of fractional calculus. The result is a lumped fractional order impedance model, to be used in a personalised way, i.e. per individual and not per population distribution data. A measurement device and a protocol have been determined in collaboration with Ghent University Hospital pain specialists. The experiments support our claim that changes occur in skin impedance during stimulation, i.e. when perceived as pain in one awake healthy volunteer. Following this proof of concept study, the model enables simulation of how nociceptor stimulation enters the systemic process of pain, for further analysis and development within the regulatory loops of pain management practices. (C) 2018, IFAC (International Federation of Automatic Control) Hosting by Elsevier Ltd. All rights reserved

Online weight estimation in a robotic gripper arm

This paper presents a novel methodology for online, fast and accurate weight estimation technique in a robotic gripper arm. The laboratory setup is inspired from several real life applications of weight estimation in moving cranes, e.g. loading containers in a shipyard, iron scrapping in steel industry, etc. The weight needs to be estimated within a specified time interval and within a tolerance interval for accuracy. The results indicate that the proposed method is suitable for this kind of application and an improvement of 30% has been achieved compared to the current state of work

Fractional order impedance models as rising tools for quantification of unconscious analgesia

This research focuses on modeling the diffusion process that occurs in the human body when an analgesic drug is taken up, by using fractional-order impedance models (FOIMs). We discuss the measurement of a suitable feedback signal that can be used in a model-based control strategy. With this knowledge an early dawn concept of a pain sensor is presented. The major challenges that are encountered during this development consist of identification of the patient model, validation of the pain sensor and validation of the effect of the analgesic drug