Improved methodology and set-point design for diagnosis of model-plant mismatch in control loops using plant-model ratio

Chattez avec Graph Search

Posez n’importe quelle question sur les cours, conférences, exercices, recherches, actualités, etc. de l’EPFL ou essayez les exemples de questions ci-dessous.

AVERTISSEMENT : Le chatbot Graph n'est pas programmé pour fournir des réponses explicites ou catégoriques à vos questions. Il transforme plutôt vos questions en demandes API qui sont distribuées aux différents services informatiques officiellement administrés par l'EPFL. Son but est uniquement de collecter et de recommander des références pertinentes à des contenus que vous pouvez explorer pour vous aider à répondre à vos questions.

Using (Formula presented) (Formula presented) events collected with the BESIII detector operating at the BEPCII collider, we have observed the decay (Formula presented) for the first time with a statistical significance of (Formula presented). Its branchin ...

In light of the challenges posed by climate change and the goals of the Paris Agreement, electricity generation is shifting to a more renewable and decentralized pattern, while the operation of systems like buildings is increasingly electrified. This calls ...

Information theory has allowed us to determine the fundamental limit of various communication and algorithmic problems, e.g., the channel coding problem, the compression problem, and the hypothesis testing problem. In this work, we revisit the assumptions ...

Quantum support vector machines employ quantum circuits to define the kernel function. It has been shown that this approach offers a provable exponential speedup compared to any known classical algorithm for certain data sets. The training of such models c ...

We study the problem of performance optimization of closed -loop control systems with unmodeled dynamics. Bayesian optimization (BO) has been demonstrated to be effective for improving closed -loop performance by automatically tuning controller gains or re ...

Cells are the smallest operational units of living systems. Through synthesis of various biomolecules and exchange of signals with the environment, cells tightly regulate their composition to realize a specific functional state. The transformation of a cel ...

Macroscopic fundamental diagrams (MFDs) have been widely adopted to model the traffic flow of large-scale urban networks. Coupling perimeter control and regional route guidance (PCRG) is a promising strategy to decrease congestion heterogeneity and reduce ...

The aircraft assembly system is highly complex involving different stakeholders from multiple domains. The design of such a system requires comprehensive consideration of various industrial scenarios aiming to optimize key performance indicators. Tradition ...

Computer simulations are often used as support material for science education, as they can engage students through inquiry-based learning, promote their active interaction in the experimentation phase, and help them visualize abstract concepts. For instanc ...

This paper proposes a data-driven control design method for nonlinear systems that builds upon the Koopman operator framework. In particular, the Koopman operator is used to lift the nonlinear dynamics to a higher-dimensional space where the so-called obse ...

The collimation system of the Future Circular Collider, operating with leptons (FCC-ee), must protect not only the experiments against backgrounds, but also the machine itself from beam losses. With a 17.8 MJ stored energy of the electron and positron beam ...

In this paper, we present the first results of a systematically designed multi-input multi-output gas-injection controller on Tokamak a Configuration Variable (TCV). We demonstrate the simultaneous real-time control of the NII emission front position and l ...

The fundamental role of any neuron within a network is to transform complex spatiotemporal synaptic input patterns into individual output spikes. These spikes, in turn, act as inputs for other neurons in the network. Neurons must execute this function acro ...

Despite the large body of academic work on machine learning security, little is known about the occurrence of attacks on machine learning systems in the wild. In this paper, we report on a quantitative study with 139 industrial practitioners. We analyze at ...

In control system networks, reconfiguration of the controller when agents are leaving or joining the network is still an open challenge, in particular when operation constraints that depend on each agent's behavior must be met. Drawing our motivation from ...

Control systems operating in real-world environments often face disturbances arising from measurement noise and model mismatch. These factors can significantly impact the perfor- mance and safety of the system. In this thesis, we aim to leverage data to de ...

In certain cases of astronomical data analysis, the meaningful physical quantity to extract is the ratio R between two data sets. Examples include the lensing ratio, the interloper rate in spectroscopic redshift samples, and the decay rate of gravitational ...

To build biophysically detailed models of brain cells, circuits, and regions, a data-driven approach is increasingly being adopted. This helps to obtain a simulated activity that reproduces the experimentally recorded neural dynamics as faithfully as possi ...

This work addresses the problem of sharing partial information within social learning strategies. In social learning, agents solve a distributed multiple hypothesis testing problem by performing two operations at each instant: first, agents incorporate inf ...

Machine learning is often cited as a new paradigm in control theory, but is also often viewed as empirical and less intuitive for students than classical model-based methods. This is particularly the case for reinforcement learning, an approach that does n ...

Improved methodology and set-point design for diagnosis of model-plant mismatch in control loops using plant-model ratio

Chattez avec Graph Search

Study of the decay (Formula presented)

Quantifying the Unknown: Data-Driven Approaches and Applications in Energy Systems

On Speed and Advantage : Results in Information Velocity and Monitoring Problems

The complexity of quantum support vector machines

Violation-aware contextual Bayesian optimization for controller performance optimization with unmodeled constraints

Deciphering the nature of cell state transitions in single cells using quantitative modeling of temporal dynamics

An Iterative Adaptive Dynamic Programming Approach for Macroscopic Fundamental Diagram-Based Perimeter Control and Route Guidance

An aircraft assembly process formalism and verification method based on semantic modeling and MBSE

Teacher-Mediated and Student-Led Interaction with a Physics Simulation: Effects on the Learning Experience

Data-Driven Control Synthesis using Koopman Operator: A Robust Approach

Collimation simulations for the FCC-ee

Systematic design of a multi-input multi-output controller by model-based decoupling: a demonstration on TCV using multi-species gas injection

Different responses of mice and rats hippocampus CA1 pyramidal neurons to in vitro and in vivo-like inputs

Machine Learning Security in Industry: A Quantitative Survey

Model Predictive Control for Multi-Agent Systems under Limited Communication and Time-Varying Network Topology

Data-Driven Control and Optimization under Noisy and Uncertain Conditions

An Unbiased Method of Measuring the Ratio of Two Data Sets

Online interoperable resources for building hippocampal neuron models via the Hippocampus Hub

Partial Information Sharing Over Social Learning Networks

Reinforcement learning approach to control an inverted pendulum: A general framework for educational purposes