A disturbance model for the optimization of control/structure interactions for flexible dynamic systems

In many optical trapping experiments, exogenous forces are estimated by assuming the exogenous force is balanced with the optical force. These optical forces are measured using Hooke’s law, and the displacement of the particle is low-pass filtered to minimize the effects of Brownian noise. This paper explores a different approach that uses a disturbance model approach for estimating exogenous forces using a Kalman filter. The state estimate is then used in a LQG structure to manipulate the relative position of a dielectric particle within an optical trap. The exogenous force estimate using a Kalman filter has been shown to have a higher SNR than the force estimation using Hooke’s Law. In addition to force estimation, the control structure can also manipulate the relative displacement of the particle to satisfy experimental conditions. A simulation is presented to demonstrate the performance of the LQG control structure.

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An improved inverse neural control structure for nonlinear dynamic systems

ICECS'99. Proceedings of ICECS '99. 6th IEEE International Conference on Electronics, Circuits and Systems (Cat. No.99EX357) ◽

10.1109/icecs.1999.813398 ◽

2003 ◽

Author(s):

G. Puscasu ◽

V. Palade

Keyword(s):

Dynamic Systems ◽

Nonlinear Dynamic ◽

Neural Control ◽

Control Structure ◽

Nonlinear Dynamic Systems

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Strategy Synthesis for Data-Aware Dynamic Systems with Multiple Actors

Proceedings of the Seventeenth International Conference on Principles of Knowledge Representation and Reasoning ◽

10.24963/kr.2020/32 ◽

2020 ◽

Author(s):

Massimiliano de Leoni ◽

Paolo Felli ◽

Marco Montali

Keyword(s):

Dynamic Systems ◽

Control Structure ◽

State Control ◽

Infinite Domain ◽

Modeling And Analysis ◽

Finite State ◽

Finite Set ◽

The One ◽

Data Evolution ◽

Finite State Control

The integrated modeling and analysis of dynamic systems and the data they manipulate has been long advocated, on the one hand, to understand how data and corresponding decisions affect the system execution, and on the other hand to capture how actions occurring in the systems operate over data. KR techniques proved successful in handling a variety of tasks over such integrated models, ranging from verification to online monitoring. In this paper, we consider a simple, yet relevant model for data-aware dynamic systems (DDSs), consisting of a finite-state control structure defining the executability of actions that manipulate a finite set of variables with an infinite domain. On top of this model, we consider a data-aware version of reactive synthesis, where execution strategies are built by guaranteeing the satisfaction of a desired linear temporal property that simultaneously accounts for the system dynamics and data evolution.

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A disturbance model for control/structure optimization with output feedback control

Structural Optimization ◽

10.1007/bf01743345 ◽

1993 ◽

Vol 6 (2) ◽

pp. 123-133 ◽

Cited By ~ 3

Author(s):

M. D. McLaren ◽

G. L. Slater

Keyword(s):

Feedback Control ◽

Output Feedback ◽

Control Structure ◽

Output Feedback Control ◽

Structure Optimization ◽

Disturbance Model

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Phase behavior of cationic and anionic surfactants at low concentrations

Proceedings, annual meeting, Electron Microscopy Society of America ◽

10.1017/s0424820100123878 ◽

1992 ◽

Vol 50 (1) ◽

pp. 694-695

Author(s):

E. Naranjo

Keyword(s):

Phase Behavior ◽

Structural Characterization ◽

Dynamic Systems ◽

Anionic Surfactants ◽

Intermolecular Forces ◽

Stable Form ◽

Surfactant Mixtures ◽

Low Concentrations ◽

Cationic And Anionic Surfactants ◽

General Method

Equilibrium vesicles, those which are the stable form of aggregation and form spontaneously on mixing surfactant with water, have never been demonstrated in single component bilayers and only rarely in lipid or surfactant mixtures. Designing a simple and general method for producing spontaneous and stable vesicles depends on a better understanding of the thermodynamics of aggregation, the interplay of intermolecular forces in surfactants, and an efficient way of doing structural characterization in dynamic systems.

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Improving Feeding Outcomes in the NICU: Moving From Volume-Driven to Infant-Driven Feeding

Perspectives on Swallowing and Swallowing Disorders (Dysphagia) ◽

10.1044/sasd19.3.68 ◽

2010 ◽

Vol 19 (3) ◽

pp. 68-74 ◽

Cited By ~ 9

Author(s):

Catherine S. Shaker

Keyword(s):

Intensive Care Unit ◽

Dynamic Systems ◽

Neonatal Intensive Care ◽

Well Being ◽

Dynamic Systems Theory ◽

Feeding Problems ◽

Care Giving ◽

Extremely Preterm ◽

Extremely Preterm Infants

Current research on feeding outcomes after discharge from the neonatal intensive care unit (NICU) suggests a need to critically look at the early underpinnings of persistent feeding problems in extremely preterm infants. Concepts of dynamic systems theory and sensitive care-giving are used to describe the specialized needs of this fragile population related to the emergence of safe and successful feeding and swallowing. Focusing on the infant as a co-regulatory partner and embracing a framework of an infant-driven, versus volume-driven, feeding approach are highlighted as best supporting the preterm infant's developmental strivings and long-term well-being.

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