3,125,568 research outputs found
Practical Distributed Control Synthesis
Classic distributed control problems have an interesting dichotomy: they are
either trivial or undecidable. If we allow the controllers to fully
synchronize, then synthesis is trivial. In this case, controllers can
effectively act as a single controller with complete information, resulting in
a trivial control problem. But when we eliminate communication and restrict the
supervisors to locally available information, the problem becomes undecidable.
In this paper we argue in favor of a middle way. Communication is, in most
applications, expensive, and should hence be minimized. We therefore study a
solution that tries to communicate only scarcely and, while allowing
communication in order to make joint decision, favors local decisions over
joint decisions that require communication.Comment: In Proceedings INFINITY 2011, arXiv:1111.267
Distributed environmental control
We present an architecture of distributed, independent control agents designed to work with the Computer Aided System Engineering and Analysis (CASE/A) simulation tool. CASE/A simulates behavior of Environmental Control and Life Support Systems (ECLSS). We describe a lattice of agents capable of distributed sensing and overcoming certain sensor and effector failures. We address how the architecture can achieve the coordinating functions of a hierarchical command structure while maintaining the robustness and flexibility of independent agents. These agents work between the time steps of the CASE/A simulation tool to arrive at command decisions based on the state variables maintained by CASE/A. Control is evaluated according to both effectiveness (e.g., how well temperature was maintained) and resource utilization (the amount of power and materials used)
Distributed Access Control with Blockchain
The specification and enforcement of network-wide policies in a single
administrative domain is common in today's networks and considered as already
resolved. However, this is not the case for multi-administrative domains, e.g.
among different enterprises. In such situation, new problems arise that
challenge classical solutions such as PKIs, which suffer from scalability and
granularity concerns. In this paper, we present an extension to Group-Based
Policy -- a widely used network policy language -- for the aforementioned
scenario. To do so, we take advantage of a permissioned blockchain
implementation (Hyperledger Fabric) to distribute access control policies in a
secure and auditable manner, preserving at the same time the independence of
each organization. Network administrators specify polices that are rendered
into blockchain transactions. A LISP control plane (RFC 6830) allows routers
performing the access control to query the blockchain for authorizations. We
have implemented an end-to-end experimental prototype and evaluated it in terms
of scalability and network latency.Comment: 7 pages, 9 figures, 2 table
Distributed control in virtualized networks
The increasing number of the Internet connected devices requires novel solutions to control the next generation network resources. The cooperation between the Software Defined Network (SDN) and the Network Function Virtualization (NFV) seems to be a promising technology paradigm. The bottleneck of current SDN/NFV implementations is the use of a centralized controller. In this paper, different scenarios to identify the pro and cons of a distributed control-plane were investigated. We implemented a prototypal framework to benchmark different centralized and distributed approaches. The test results have been critically analyzed and related considerations and recommendations have been reported. The outcome of our research influenced the control plane design of the following European R&D projects: PLATINO, FI-WARE and T-NOVA
Distributed Control of Positive Systems
A system is called positive if the set of non-negative states is left
invariant by the dynamics. Stability analysis and controller optimization are
greatly simplified for such systems. For example, linear Lyapunov functions and
storage functions can be used instead of quadratic ones. This paper shows how
such methods can be used for synthesis of distributed controllers. It also
shows that stability and performance of such control systems can be verified
with a complexity that scales linearly with the number of interconnections.
Several results regarding scalable synthesis and verfication are derived,
including a new stronger version of the Kalman-Yakubovich-Popov lemma for
positive systems. Some main results are stated for frequency domain models
using the notion of positively dominated system. The analysis is illustrated
with applications to transportation networks, vehicle formations and power
systems
Information embedding meets distributed control
We consider the problem of information embedding where the encoder modifies a
white Gaussian host signal in a power-constrained manner to encode the message,
and the decoder recovers both the embedded message and the modified host
signal. This extends the recent work of Sumszyk and Steinberg to the
continuous-alphabet Gaussian setting. We show that a dirty-paper-coding based
strategy achieves the optimal rate for perfect recovery of the modified host
and the message. We also provide bounds for the extension wherein the modified
host signal is recovered only to within a specified distortion. When
specialized to the zero-rate case, our results provide the tightest known lower
bounds on the asymptotic costs for the vector version of a famous open problem
in distributed control -- the Witsenhausen counterexample. Using this bound, we
characterize the asymptotically optimal costs for the vector Witsenhausen
problem numerically to within a factor of 1.3 for all problem parameters,
improving on the earlier best known bound of 2.Comment: 19 pages, 7 figures. Presented at ITW'10. Submitted to IEEE
Transactions on Information Theor
Distributed control design for underwater vehicles
The vast majority of control applications are based on non-interacting decentralized control designs. Because of their single-loop structure, these controllers cannot suppress interactions of the system. It would be useful to tackle the undesirable effects of the interactions at the design stage. A novel model predictive control scheme based on Nash optimality is presented to achieve this goal. In this algorithm, the control problem is decomposed into that of several small-coupled mixed integer optimisation problems. The relevant computational convergence, closed-loop performance and the effect of communication failures on the closed-loop behaviour are analysed. Simulation results are presented to illustrate the effectiveness and practicality of the proposed control algorithm
Distributed Bio-inspired Humanoid Posture Control
This paper presents an innovative distributed bio-inspired posture control
strategy for a humanoid, employing a balance control system DEC (Disturbance
Estimation and Compensation). Its inherently modular structure could
potentially lead to conflicts among modules, as already shown in literature. A
distributed control strategy is presented here, whose underlying idea is to let
only one module at a time perform balancing, whilst the other joints are
controlled to be at a fixed position. Modules agree, in a distributed fashion,
on which module to enable, by iterating a max-consensus protocol. Simulations
performed with a triple inverted pendulum model show that this approach limits
the conflicts among modules while achieving the desired posture and allows for
saving energy while performing the task. This comes at the cost of a higher
rise time.Comment: 2019 41st Annual International Conference of the IEEE Engineering in
Medicine & Biology Society (EMBC
Distributed Control by Lagrangian Steepest Descent
Often adaptive, distributed control can be viewed as an iterated game between
independent players. The coupling between the players' mixed strategies,
arising as the system evolves from one instant to the next, is determined by
the system designer. Information theory tells us that the most likely joint
strategy of the players, given a value of the expectation of the overall
control objective function, is the minimizer of a Lagrangian function of the
joint strategy. So the goal of the system designer is to speed evolution of the
joint strategy to that Lagrangian minimizing point, lower the expectated value
of the control objective function, and repeat. Here we elaborate the theory of
algorithms that do this using local descent procedures, and that thereby
achieve efficient, adaptive, distributed control.Comment: 8 page
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