9,305 research outputs found
Sub-6GHz Assisted MAC for Millimeter Wave Vehicular Communications
Sub-6GHz vehicular communications (using DSRC, ITS-G5 or C-V2X) have been
developed to support active safety applications. Future connected and automated
driving applications can require larger bandwidth and higher data rates than
currently supported by sub-6GHz V2X technologies. This has triggered the
interest in developing mmWave vehicular communications. However, solutions are
necessary to solve the challenges resulting from the use of high-frequency
bands and the high mobility of vehicles. This paper contributes to this active
research area by proposing a sub-6GHz assisted mmWave MAC that decouples the
mmWave data and control planes. The proposal offloads mmWave MAC control
functions (beam alignment, neighbor identification and scheduling) to a
sub-6GHz V2X technology, and reserves the mmWave channel for the data plane.
This approach improves the operation of the MAC as the control functions
benefit from the longer range, and the broadcast and omnidirectional
transmissions of sub-6GHz V2X technologies. This simulation study demonstrates
that the proposed sub-6GHz assisted mmWave MAC reduces the control overhead and
delay, and increases the spatial sharing compared to a mmWave-only
configuration (IEEE 802.11ad tailored to vehicular networks). The proposed MAC
is here evaluated for V2V communications using 802.11p for the control plane
and 802.11ad for the data plane. However, the proposal is not restricted to
these technologies, and can be adapted to other technologies such as C-V2X and
5G NR.Comment: 8 pages, 5 figure
An intelligent framework and prototype for autonomous maintenance planning in the rail industry
This paper details the development of the AUTONOM project, a project that aims to provide an enterprise system tailored to the planning needs of the rail industry. AUTONOM extends research in novel sensing, scheduling, and decision-making strategies customised for the automated planning of maintenance activities within the rail industry. This paper sets out a framework and software prototype and details the current progress of the project. In the continuation of the AUTONOM project it is anticipated that the combination of techniques brought together in this work will be capable of addressing a wider range of problem types, offered by Network rail and organisations in different industries
Integer programming for building robust surgery schedules.
This paper proposes and evaluates a number of models for building robust cyclic surgery schedules. The developed models involve two types of constraints. Demand constraints ensure that each surgeon (or surgical group) obtains a specific number of operating room (OR) blocks. Capacity con- straints limit the available OR blocks on each day. Furthermore, the number of operated patients per block and the length of stay (LOS) of each operated patient are dependent on the type of surgery. Both are considered stochas- tic, following a multinomial distribution. We develop a number of MIP-based heuristics and a metaheuristic to minimize the expected total bed shortage and present computational results.Constraint; Demand; Distribution; Expected; Heuristic; Integer programming; Model; Models; Resource leveling; Surgery scheduling;
Online identification and nonlinear control of the electrically stimulated quadriceps muscle
A new approach for estimating nonlinear models of the electrically stimulated quadriceps muscle group under nonisometric conditions is investigated. The model can be used for designing controlled neuro-prostheses. In order to identify the muscle dynamics (stimulation pulsewidth-active knee moment relation) from discrete-time angle measurements only, a hybrid model structure is postulated for the shank-quadriceps dynamics. The model consists of a relatively well known time-invariant passive component and an uncertain time-variant active component. Rigid body dynamics, described by the Equation of Motion (EoM), and passive joint properties form the time-invariant part. The actuator, i.e. the electrically stimulated muscle group, represents the uncertain time-varying section. A recursive algorithm is outlined for identifying online the stimulated quadriceps muscle group. The algorithm requires EoM and passive joint characteristics to be known a priori. The muscle dynamics represent the product of a continuous-time nonlinear activation dynamics and a nonlinear static contraction function described by a Normalised Radial Basis Function (NRBF) network which has knee-joint angle and angular velocity as input arguments. An Extended Kalman Filter (EKF) approach is chosen to estimate muscle dynamics parameters and to obtain full state estimates of the shank-quadriceps dynamics simultaneously. The latter is important for implementing state feedback controllers. A nonlinear state feedback controller using the backstepping method is explicitly designed whereas the model was identified a priori using the developed identification procedure
Nonlinear and adaptive control
The primary thrust of the research was to conduct fundamental research in the theories and methodologies for designing complex high-performance multivariable feedback control systems; and to conduct feasibiltiy studies in application areas of interest to NASA sponsors that point out advantages and shortcomings of available control system design methodologies
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