Related papers: A new approach in modeling the response of RPC det…
Results from the gas gain monitoring (GGM) system for the muon detector using RPC in the CMS experiment at the LHC is presented. The system is designed to provide fast and accurate determination of any shift in the working point of the…
The Resistive Plate Chambers (RPC) detector of the CMS experiment at the LHC proton collider (CERN, Switzerland) will employ an online gas analysis and monitoring system of the freon-based gas mixture used. We give an overview of the CMS…
The Gas Gain Monitoring (GGM) system of the Resistive Plate Chamber (RPC) muon detector in the Compact Muon Solenoid (CMS) experiment provides fast and accurate determination of the stability in the working point conditions due to gas…
The muon system of the CERN Compact Muon Solenoid (CMS) experiment includes more than a thousand Resistive Plate Chambers (RPC). They are gaseous detectors operated in the hostile environment of the CMS underground cavern on the Large…
The RPC muon detector of the CMS experiment at the LHC (CERN, Geneva, Switzerland) is equipped with a Gas Gain Monitoring (GGM) system. A report on the stability of the system during the 2011-2012 data taking run is given, as well as the…
For systems with uncertain linear models, bounded additive disturbances and state and control constraints, a robust model predictive control algorithm incorporating online model adaptation is proposed. Sets of model parameters are…
A robust adaptive model predictive control (MPC) algorithm is presented for linear, time invariant systems with unknown dynamics and subject to bounded measurement noise. The system is characterized by an impulse response model, which is…
This paper presents a streamlined framework for real-time processing and analysis of condition data from the CMS experiment Resistive Plate Chambers (RPC). Leveraging data streaming, it uncovers correlations between RPC performance metrics,…
The Multigap Resistive Plate Chamber (MRPC) is a gaseous detector; the performance depends very much on the gas mixture as well as the design. MRPCs are used as a timing device in several collider experiments and cosmic ray experiments…
The recent advancement in vehicular networking technology provides novel solutions for designing intelligent and sustainable vehicle motion controllers. This work addresses a car-following task, where the feedback linearisation method is…
Autonomous driving is a complex and highly dynamic process that ensures controlling the coupled longitudinal and lateral vehicle dynamics. Model predictive control, distinguished by its predictive feature, optimal performance, and ability…
We propose a robust adaptive Model Predictive Control (MPC) strategy with online set-based estimation for constrained linear systems with unknown parameters and bounded disturbances. A sample-based test applied to predicted trajectories is…
This paper addresses the design of an event-triggered, data-based, and performance-oriented adaption method for model predictive control (MPC). The performance of such a strategy strongly depends on the accuracy of the prediction model,…
Large Resistive Plate Chamber systems have their roots in High Energy Physics experiments at the European Organization for Nuclear Research: ATLAS, CMS and ALICE, where hundreds of square meters of both trigger and timing RPCs have been…
In this research, computerized maintenance management will be investigated. The rise of maintenance cost forced the research community to look for more effective ways to schedule maintenance operations. Using computerized models to come up…
A novel instrument has been developed to monitor and record the ambient pa- rameters such as temperature, atmospheric pressure and relative humidity. These parameters are very essential for understanding the characteristics such as gain of…
Self-driving cars operate in constantly changing environments and are exposed to a variety of uncertainties and disturbances. These factors render classical controllers ineffective, especially for lateral control. Therefore, an adaptive MPC…
Robots and automated systems are increasingly being introduced to unknown and dynamic environments where they are required to handle disturbances, unmodeled dynamics, and parametric uncertainties. Robust and adaptive control strategies are…
Environmental acoustic sensing involves the retrieval and processing of audio signals to better understand our surroundings. While large-scale acoustic data make manual analysis infeasible, they provide a suitable playground for machine…
In this paper, we present a novel information processing architecture for safe deep learning-based visual navigation of autonomous systems. The proposed information processing architecture is used to support a perceptual attention-based…