1,126 research outputs found
Space-Time Sampling for Network Observability
Designing sparse sampling strategies is one of the important components in
having resilient estimation and control in networked systems as they make
network design problems more cost-effective due to their reduced sampling
requirements and less fragile to where and when samples are collected. It is
shown that under what conditions taking coarse samples from a network will
contain the same amount of information as a more finer set of samples. Our goal
is to estimate initial condition of linear time-invariant networks using a set
of noisy measurements. The observability condition is reformulated as the frame
condition, where one can easily trace location and time stamps of each sample.
We compare estimation quality of various sampling strategies using estimation
measures, which depend on spectrum of the corresponding frame operators. Using
properties of the minimal polynomial of the state matrix, deterministic and
randomized methods are suggested to construct observability frames. Intrinsic
tradeoffs assert that collecting samples from fewer subsystems dictates taking
more samples (in average) per subsystem. Three scalable algorithms are
developed to generate sparse space-time sampling strategies with explicit error
bounds.Comment: Submitted to IEEE TAC (Revised Version
Integrated design and control of chemical processes : part I : revision and clasification
[EN] This work presents a comprehensive classification of the different methods and procedures for integrated synthesis, design and control of chemical processes, based on a wide revision of recent literature. This classification fundamentally differentiates between “projecting methods”, where controllability is monitored during the process design to predict the trade-offs between design and control, and the “integrated-optimization methods” which solve the process design and the control-systems design at once within an optimization framework. The latter are revised categorizing them according to the methods to evaluate controllability and other related properties, the scope of the design problem, the treatment of uncertainties and perturbations, and finally, the type the optimization problem formulation and the methods for its resolution.[ES] Este trabajo presenta una clasificación integral de los diferentes métodos y procedimientos para la síntesis integrada, diseño y control de procesos químicos. Esta clasificación distingue fundamentalmente entre los "métodos de proyección", donde se controla la controlabilidad durante el diseño del proceso para predecir los compromisos entre diseño y control, y los "métodos de optimización integrada" que resuelven el diseño del proceso y el diseño de los sistemas de control a la vez dentro de un marco de optimización. Estos últimos se revisan clasificándolos según los métodos para evaluar la controlabilidad y otras propiedades relacionadas, el alcance del problema de diseño, el tratamiento de las incertidumbres y las perturbaciones y, finalmente, el tipo de la formulación del problema de optimización y los métodos para su resolución
Optimal Sensor Placement with Adaptive Constraints for Nuclear Digital Twins
Given harsh operating conditions and physical constraints in reactors,
nuclear applications cannot afford to equip the physical asset with a large
array of sensors. Therefore, it is crucial to carefully determine the placement
of sensors within the given spatial limitations, enabling the reconstruction of
reactor flow fields and the creation of nuclear digital twins. Various design
considerations are imposed, such as predetermined sensor locations, restricted
areas within the reactor, a fixed number of sensors allocated to a specific
region, or sensors positioned at a designated distance from one another. We
develop a data-driven technique that integrates constraints into an
optimization procedure for sensor placement, aiming to minimize reconstruction
errors. Our approach employs a greedy algorithm that can optimize sensor
locations on a grid, adhering to user-defined constraints. We demonstrate the
near optimality of our algorithm by computing all possible configurations for
selecting a certain number of sensors for a randomly generated state space
system. In this work, the algorithm is demonstrated on the Out-of-Pile Testing
and Instrumentation Transient Water Irradiation System (OPTI-TWIST) prototype
vessel, which is electrically heated to mimic the neutronics effect of the
Transient Reactor Test facility (TREAT) at Idaho National Laboratory (INL). The
resulting sensor-based reconstruction of temperature within the OPTI-TWIST
minimizes error, provides probabilistic bounds for noise-induced uncertainty
and will finally be used for communication between the digital twin and
experimental facility
Emergency Flight Planning for a Generalized Transport Aircraft with Left Wing Damage
Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/77332/1/AIAA-2007-6873-998.pd
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