Red light violations (RLV) at ramp meters undermine the purpose of controlling the number of vehicles entering a freeway and the goal of dispersing platoons of vehicles. The effectiveness of ramp metering systems is a...
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Red light violations (RLV) at ramp meters undermine the purpose of controlling the number of vehicles entering a freeway and the goal of dispersing platoons of vehicles. The effectiveness of ramp metering systems is assumed to decreases with a growing rate of RLV. Therefore the goal of the study was to examine the types of RLV and the causes that provoke them. It was found, that the most important influence is the variation of the length of the red interval. Most of the results can be transferred to ramp metering in general. Furthermore a high rate of false alarm of the automatic RLV-detection was revealed and examined. Recommendations for the examined entrances are given.
Practically, some intermediary realizations are used in order to simulate, numerically, dynamic systems. One of the most popular is the state-space realization. It reveals to be very useful to study the impact of Fini...
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Practically, some intermediary realizations are used in order to simulate, numerically, dynamic systems. One of the most popular is the state-space realization. It reveals to be very useful to study the impact of Finite Word Length implementation, especially in the case of embedded controller. Numerous works concerned the design of the “best” realization concerning parameterisation, numerical noise minimisation or saving computation. This paper points out however that a standard state-space realization is too basic to take into account some interesting realizations. On the contrary, it highlights that implicit state-space realizations allows a more direct link with the macroscopic computations to be performed. It is necessary to describe some popular algorithms simulating LTI systems. Moreover, such a representation has the important property to unify different ways of research considering differently the possibilities offered by using the shift, δ or γ operators.
Hyperglycaemia is a prevalent complication in the neonatal intensive care unit (NICU) and is associated with worsened outcomes. It occurs as a result of prematurity, under developed endogenous glucose regulatory syste...
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Hyperglycaemia is a prevalent complication in the neonatal intensive care unit (NICU) and is associated with worsened outcomes. It occurs as a result of prematurity, under developed endogenous glucose regulatory systems and clinical stress. The stochastic targeting (STAR) framework provides patient-specific, model-based glycaemic control with a clinically proven level of confidence on the outcome of treatment interventions, thus directly managing the risk of hypo- and hyper- glycaemia. However, the stochastic models that are over conservative can limit control performance. Clinical data from 61 episodes (25 retrospective and 36 from a prospective BG control study), of insulin therapy in very-low birth weight (VLBW) and extremely-low birth weight (ELBW) neonates are used to create a new stochastic model of model-based insulin sensitivity (S I ). Sub-cohort models based on gestational age (GA) and birth weight (BW) are also created. Performance is assessed by the percentage of patients who have 90% of actual intra-patient variability in S I captured by the 90% confidence bands of the cohort based (inter-patient) stochastic variability model created. This assessment measures per-patient accuracy for any given cohort model. Per-patient coverage trends were very similar between prospective and retrospective cohorts, providing a measure of external validation of cohort similarity. Per patient coverage was improved though the use of BW and GA dependent stochastic models, which ensures that the stochastic models more accurately capture both inter- and intra- patient variability. Stochastic forecasting is limited by significant inter-patient variability, which implies that more patient specific methods will be required to improve forecasting and glycaemic control.
The ACCEZZ ramp metering algorithm is an adaptive control approach based on Fuzzy Logic. Results from its calibration and validation as well as its evaluation using a microscopic simulation show how different control ...
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The ACCEZZ ramp metering algorithm is an adaptive control approach based on Fuzzy Logic. Results from its calibration and validation as well as its evaluation using a microscopic simulation show how different control strategies can improve traffic conditions especially during peak hours. To evaluate the potential of ramp metering the ramp metering software TRANSRAMP has been developed, implemented and tested at a demonstration site in Munich (Germany). Since December 1st, 2005 TRANSRAMP controls traffic at two consecutive on ramps successfully with the ACCEZZ algorithm. Data for a cross-algorithm (with ALINEA) and a cross-site evaluation will be collected until April 2006 within the European research project EURAMP.
Motions of multibody linkages over a horizontal plane with dry friction are considered. Linkages consist of several rigid bodies connected by revolute joints with vertical axes. control torques are created by actuator...
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Motions of multibody linkages over a horizontal plane with dry friction are considered. Linkages consist of several rigid bodies connected by revolute joints with vertical axes. control torques are created by actuators installed at the joints. Under the proposed control laws, the linkages can perform variuos motions over a plane. The dependence of the average speed of motion on mass and geometric parameters is investigated. Optimal parameters are obtained which maximize the average speed.
Robust model-predictive controllers use an estimate of model uncertainty in the on-line controller calculation and can be overly conservative for some uncertainty descriptions. This paper discusses the various causes ...
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Robust model-predictive controllers use an estimate of model uncertainty in the on-line controller calculation and can be overly conservative for some uncertainty descriptions. This paper discusses the various causes of conservative control with particular emphasis given to the concept of 'closed-loop' probabilistic predictions. A multi-input-multi-output MPC is proposed in which an off-line, non-convex calculation is used to characterize the closed-loop uncertainty a priori. This uncertainty information is incorporated into a convex, quadratic program resulting in a MPC formulation that can be efficiently solved on-line. A distillation column case study demonstrates the benefits of the proposed robust MPC.
The paper is concerned with simulation of continuous-discrete production systems using the computer application software for metallurgy. The concepts are formulated for creating simulation systems, software and databa...
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The paper is concerned with simulation of continuous-discrete production systems using the computer application software for metallurgy. The concepts are formulated for creating simulation systems, software and databases. The examples of solution of control and project application problems using the developed simulation systems are described in this paper.
This paper considers the first version of a real time control algorithms software package. The package allows the user to choice a control algorithm (univariable or multivariable) from a predefined set. Up to eight pr...
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This paper considers the first version of a real time control algorithms software package. The package allows the user to choice a control algorithm (univariable or multivariable) from a predefined set. Up to eight process variables can be controlled by one microcomputer (current implementation in Epson QX-10) and each microcomputer can be considered a basic controller in a computer network, i. e. a node in a distributed digital control system (DDC and centralized data logging). The package is particularly user-friendly and is currently programmed in C language. Personal computers have been incorporated in this way to handle control and data logging tasks. This fact represents considerably lower costs compared to conventional systems performing the same tasks.
Over the past decade, an intense effort has brought together theoretical and laboratory tools for controlling molecular motion with tailored laser pulses. Various means for designing laser pulses are available, but pr...
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Over the past decade, an intense effort has brought together theoretical and laboratory tools for controlling molecular motion with tailored laser pulses. Various means for designing laser pulses are available, but presently, the most viable general procedure for achieving successful control over quantum systems in the laboratory is through the use of closed loop learning algorithms. The logic behind the operation of such algorithms is discussed, along with a summary of several recent laboratory achievements exploiting closed loop learning to control quantum and nonlinear optical phenomena.
This paper describes the control of quasi-resonant converters. Because of control difficulties caused by the high nonlinearity of converter components, an adaptive fuzzy control algorithm is proposed. The results of c...
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This paper describes the control of quasi-resonant converters. Because of control difficulties caused by the high nonlinearity of converter components, an adaptive fuzzy control algorithm is proposed. The results of computer simulation is presented to show the effectiveness of the proposed control.
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