20,798 research outputs found
Neural Network Control of a Laboratory Magnetic Levitator
Magnetic levitation (maglev) systems are nowadays employed in applications ranging from non-contact
bearings and vibration isolation of sensitive machinery to high-speed passenger trains. In this chapter
a mathematical model of a laboratory maglev system was derived using the Lagrangian approach. A
linear pole-placement controller was designed on the basis of specifications on peak overshoot and
settling time. A 3-layer feed-forward Artificial Neural Network (ANN) controller comprising 3-input
nodes, a 5-neuron hidden layer, and 1-neuron output layer was trained using the linear state feedback
controller with a random reference signal. Simulations to investigate the robustness of the ANN control
scheme with respect to parameter variations, reference step input magnitude variations, and sinusoidal
input tracking were carried out using SIMULINK. The obtained simulation results show that the ANN
controller is robust with respect to good positioning accuracy
Molecular Network Control Through Boolean Canalization
Boolean networks are an important class of computational models for molecular
interaction networks. Boolean canalization, a type of hierarchical clustering
of the inputs of a Boolean function, has been extensively studied in the
context of network modeling where each layer of canalization adds a degree of
stability in the dynamics of the network. Recently, dynamic network control
approaches have been used for the design of new therapeutic interventions and
for other applications such as stem cell reprogramming. This work studies the
role of canalization in the control of Boolean molecular networks. It provides
a method for identifying the potential edges to control in the wiring diagram
of a network for avoiding undesirable state transitions. The method is based on
identifying appropriate input-output combinations on undesirable transitions
that can be modified using the edges in the wiring diagram of the network.
Moreover, a method for estimating the number of changed transitions in the
state space of the system as a result of an edge deletion in the wiring diagram
is presented. The control methods of this paper were applied to a mutated
cell-cycle model and to a p53-mdm2 model to identify potential control targets
The AMSC network control system
The American Mobile Satellite Corporation (AMSC) is going to construct, launch, and operate a satellite system in order to provide mobile satellite services to the United States. AMSC is going to build, own, and operate a Network Control System (NCS) for managing the communications usage of the satellites, and to control circuit switched access between mobile earth terminals and feeder-link earth stations. An overview of the major NCS functional and performance requirements, the control system physical architecture, and the logical architecture is provided
Wireless network control of interacting Rydberg atoms
We identify a relation between the dynamics of ultracold Rydberg gases in
which atoms experience a strong dipole blockade and spontaneous emission, and a
stochastic process that models certain wireless random-access networks. We then
transfer insights and techniques initially developed for these wireless
networks to the realm of Rydberg gases, and explain how the Rydberg gas can be
driven into crystal formations using our understanding of wireless networks.
Finally, we propose a method to determine Rabi frequencies (laser intensities)
such that particles in the Rydberg gas are excited with specified target
excitation probabilities, providing control over mixed-state populations.Comment: 6 pages, 7 figures; includes corrections and improvements from the
peer-review proces
Stable Wireless Network Control Under Service Constraints
We consider the design of wireless queueing network control policies with
particular focus on combining stability with additional application-dependent
requirements. Thereby, we consequently pursue a cost function based approach
that provides the flexibility to incorporate constraints and requirements of
particular services or applications. As typical examples of such requirements,
we consider the reduction of buffer underflows in case of streaming traffic,
and energy efficiency in networks of battery powered nodes. Compared to the
classical throughput optimal control problem, such requirements significantly
complicate the control problem. We provide easily verifyable theoretical
conditions for stability, and, additionally, compare various candidate cost
functions applied to wireless networks with streaming media traffic. Moreover,
we demonstrate how the framework can be applied to the problem of energy
efficient routing, and we demonstrate the aplication of our framework in
cross-layer control problems for wireless multihop networks, using an advanced
power control scheme for interference mitigation, based on successive convex
approximation. In all scenarios, the performance of our control framework is
evaluated using extensive numerical simulations.Comment: Accepted for publication in IEEE Transactions on Control of Network
Systems. arXiv admin note: text overlap with arXiv:1208.297
Traffic Network Control from Temporal Logic Specifications
We propose a framework for generating a signal control policy for a traffic
network of signalized intersections to accomplish control objectives
expressible using linear temporal logic. By applying techniques from model
checking and formal methods, we obtain a correct-by-construction controller
that is guaranteed to satisfy complex specifications. To apply these tools, we
identify and exploit structural properties particular to traffic networks that
allow for efficient computation of a finite state abstraction. In particular,
traffic networks exhibit a componentwise monotonicity property which allows
reach set computations that scale linearly with the dimension of the continuous
state space
Optimal Network Control in Partially-Controllable Networks
The effectiveness of many optimal network control algorithms (e.g.,
BackPressure) relies on the premise that all of the nodes are fully
controllable. However, these algorithms may yield poor performance in a
partially-controllable network where a subset of nodes are uncontrollable and
use some unknown policy. Such a partially-controllable model is of increasing
importance in real-world networked systems such as overlay-underlay networks.
In this paper, we design optimal network control algorithms that can stabilize
a partially-controllable network. We first study the scenario where
uncontrollable nodes use a queue-agnostic policy, and propose a low-complexity
throughput-optimal algorithm, called Tracking-MaxWeight (TMW), which enhances
the original MaxWeight algorithm with an explicit learning of the policy used
by uncontrollable nodes. Next, we investigate the scenario where uncontrollable
nodes use a queue-dependent policy and the problem is formulated as an MDP with
unknown queueing dynamics. We propose a new reinforcement learning algorithm,
called Truncated Upper Confidence Reinforcement Learning (TUCRL), and prove
that TUCRL achieves tunable three-way tradeoffs between throughput, delay and
convergence rate
Traffic-responsive urban network control using multivariable regulators
The paper presents the philosophy, the aim, the development, the advantages, and the potential shortcomings of the TUC (Traffic-responsive Urban Control) strategy. Based on a store-and-forward modeling approach and using well-known methods of the Automatic Control Theory, the approach followed by TUC designs (off-line) and employs (on-line) a multivariable regulator for traffic-responsive co-ordinated network-wide signal control. Simulation investigations are used to demonstrate the efficiency of the proposed approach. Based on the presented investigations, summarising conclusions are drawn and future work is outlined
Wireless Network Control with Privacy Using Hybrid ARQ
We consider the problem of resource allocation in a wireless cellular
network, in which nodes have both open and private information to be
transmitted to the base station over block fading uplink channels. We develop a
cross-layer solution, based on hybrid ARQ transmission with incremental
redundancy. We provide a scheme that combines power control, flow control, and
scheduling in order to maximize a global utility function, subject to the
stability of the data queues, an average power constraint, and a constraint on
the privacy outage probability. Our scheme is based on the assumption that each
node has an estimate of its uplink channel gain at each block, while only the
distribution of the cross channel gains is available. We prove that our scheme
achieves a utility, arbitrarily close to the maximum achievable utility given
the available channel state information
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