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prediction-based control

Prediction-Based Control of Linear Systems by Compensating Input-Dependent Input Delay of Integral-Type

Prediction-Based Control of Linear Systems by Compensating Input-Dependent Input Delay of Integral-Type

... a prediction-based control law, we advocate a two-step method of disrupting the implicit loop, as proposed in our recent works on the topic [4, 6] and establish sufficient conditions for asymptotic ...

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Approximate Prediction-Based Control Method for Nonlinear Oscillatory Systems with Applications to Chaotic Systems

Approximate Prediction-Based Control Method for Nonlinear Oscillatory Systems with Applications to Chaotic Systems

... mate Prediction-Based Control (aPBC) with a methodology based on the implicit Runge-Kutta method and state estimation applied to predict future states for the free system in real-time ...

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Stabilization of periodic orbits of discrete-time dynamical systems using the Prediction-Based Control: New control law and practical aspects

Stabilization of periodic orbits of discrete-time dynamical systems using the Prediction-Based Control: New control law and practical aspects

... DFC control gain by optimization The design of the control gain for the DFC is done by choosing a constant matrix K that minimizes the largest, in modulus, Floquet multiplier |µ|max of the controlled ...

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Constant time horizon prediction-based control for linear systems with time-varying input delay

Constant time horizon prediction-based control for linear systems with time-varying input delay

... Numerous control systems have been developed to re- duce the influence of time-delays, as exposed in Gu and Niculescu (2003) and Richard ...system, prediction-based controllers are an interesting ...

7

Total variation regularization for fMRI-based prediction of behaviour.

Total variation regularization for fMRI-based prediction of behaviour.

... MRI (fMRI) data, that provide an indirect measure of task- related or spontaneous neuronal activity, are classically analyzed in a mass-univariate procedure yielding statistical parametric maps. This analysis framework ...

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Recovery and Prediction of Dynamic Precision Grip Force Control After Stroke

Recovery and Prediction of Dynamic Precision Grip Force Control After Stroke

... have described dynamic finger force control (i.e., the ability to appropriately generate dynamically scaled and directed force by the digits while grasping unstable objects), which is frequently affected after ...

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A velocity decomposition method for exergy-based drag prediction

A velocity decomposition method for exergy-based drag prediction

... The nonisentropic exergy-based drag coefficient field (related to viscous and shock wave losses) is shown in Fig. 18. This field is zero outside the boundary layer and the wake, as expected, since no ...

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Physical layer DVB-SH performance prediction based on mutual information

Physical layer DVB-SH performance prediction based on mutual information

... A major difficulty associated to this mechanism resides in its performance evaluation on sufficiently long distances in order to be able to tune its parameters. Indeed, the use of time slicing leads to a non stationary ...

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'Current City' prediction for coarse location based applications on Facebook

'Current City' prediction for coarse location based applications on Facebook

... II. R ELATED WORK User’s location becomes essential information in large- scale applications such as content-based delivery networks, location-based recommendation systems [3] and personalized services. ...

7

Physical layer DVB-SH performance prediction based on mutual information

Physical layer DVB-SH performance prediction based on mutual information

... A major difficulty associated to this mechanism resides in its performance evaluation on sufficiently long distances in order to be able to tune its parameters. Indeed, the use of time slicing leads to a non stationary ...

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A 3D insulin sensitivity prediction model enables more patient-specific prediction and model-based glycaemic control

A 3D insulin sensitivity prediction model enables more patient-specific prediction and model-based glycaemic control

... 1.0 Introduction: Critically ill patients in intensive care units (ICUs) often experience abnormally elevated blood glucose (BG) concentrations (hyperglycaemia), as a stress response to illness and injury [1-3]. ...

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KBAC: Knowledge-Based Admission Control

KBAC: Knowledge-Based Admission Control

... admission control in order to provide a sufficient level of Quality of Service (QoS) to accepted ...method based on a time- varying model that we refer to as Knowledge-Based Admission Control ...

9

Calibration-Free BCI Based Control

Calibration-Free BCI Based Control

... This control based on user’s assessments decoded from brain signals can be exemplified for a reaching task, where the user wants to reach a target position unknown by the ...

9

KBAC: Knowledge-Based Admission Control

KBAC: Knowledge-Based Admission Control

... solution based on Equivalent Capacity attempts to ensure that, for any link on the path between the source and the destination, the rate of the flow requesting admission summed to the actual Equivalent Capacity ...

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Adding sub-hourly stochastic occupancy prediction, occupancy-sensing control and stochastic manual control to ESP-r

Adding sub-hourly stochastic occupancy prediction, occupancy-sensing control and stochastic manual control to ESP-r

... occupancy-related control is required within the simulation and then occupancy levels are subsequently updated, followed by adjustments to occupancy-sensing controlled equipment and fixtures, if ...to ...

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Total Variation regularization enhances regression-based brain activity prediction

Total Variation regularization enhances regression-based brain activity prediction

... the prediction of a behavioral variable of interest (the ...a prediction function whose accuracy depends on its ability to use the relevant variables, ...good prediction performance and provide an ...

5

Lasso based feature selection for malaria risk exposure prediction

Lasso based feature selection for malaria risk exposure prediction

... are based on [9], [6], ...and prediction are generally linear models, generalized models, mixed models, generalized mixed models, multilevel modeling ...

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Adding sub-hourly occupancy prediction, occupancy-sensing control and manual environmental control to whole-building energy simulation

Adding sub-hourly occupancy prediction, occupancy-sensing control and manual environmental control to whole-building energy simulation

... One significant shortcoming of the RP-1093 diversity profiles, or any other similarly-derived profiles for that matter, is that they are derived independently of weather data. This may be a valid assumption when ...

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Caching strategies based on popularity prediction in content delivery networks

Caching strategies based on popularity prediction in content delivery networks

... Least Frequently Used (LFU) is a more complex strategy than LRU. It keeps track of the frequency of requests for every content to evaluate its popularity. It puts in the cache the contents having the highest request ...

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Prediction model of Parkinson's disease based on antiparkinsonian drug claims.

Prediction model of Parkinson's disease based on antiparkinsonian drug claims.

... studies, prediction models can be used in different ...the prediction model based on a given probability cutoff, and the relation between exposure and disease can be evaluated using different study ...

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