53,225 research outputs found
An Alternating Trust Region Algorithm for Distributed Linearly Constrained Nonlinear Programs, Application to the AC Optimal Power Flow
A novel trust region method for solving linearly constrained nonlinear
programs is presented. The proposed technique is amenable to a distributed
implementation, as its salient ingredient is an alternating projected gradient
sweep in place of the Cauchy point computation. It is proven that the algorithm
yields a sequence that globally converges to a critical point. As a result of
some changes to the standard trust region method, namely a proximal
regularisation of the trust region subproblem, it is shown that the local
convergence rate is linear with an arbitrarily small ratio. Thus, convergence
is locally almost superlinear, under standard regularity assumptions. The
proposed method is successfully applied to compute local solutions to
alternating current optimal power flow problems in transmission and
distribution networks. Moreover, the new mechanism for computing a Cauchy point
compares favourably against the standard projected search as for its activity
detection properties
Evolutionary design of a full-envelope full-authority flight control system for an unstable high-performance aircraft
The use of an evolutionary algorithm in the framework of H1 control theory is being considered as a means for synthesizing controller gains that minimize a weighted combination of the infinite norm of the sensitivity function (for disturbance attenuation requirements) and complementary sensitivity function (for robust stability requirements) at the same time. The case study deals with a complete full-authority longitudinal control system for an unstable high-performance jet aircraft featuring (i) a stability and control augmentation system and (ii) autopilot functions (speed and altitude hold). Constraints on closed-loop response are enforced, that representing typical requirements on airplane handling qualities, that makes the control law synthesis process more demanding. Gain scheduling is required, in order to obtain satisfactory performance over the whole flight envelope, so that the synthesis is performed at different reference trim conditions, for several values of the dynamic pressure, used as the scheduling parameter. Nonetheless, the dynamic behaviour of the aircraft may exhibit significant variations when flying at different altitudes, even for the same value of the dynamic pressure, so that a trade-off is required between different feasible controllers synthesized at different altitudes for a given equivalent airspeed. A multiobjective search is thus considered for the determination of the best suited solution to be introduced in the scheduling of the control law. The obtained results are then tested on a longitudinal non-linear model of the aircraft
Real-time dynamic spectrum management for multi-user multi-carrier communication systems
Dynamic spectrum management is recognized as a key technique to tackle
interference in multi-user multi-carrier communication systems and networks.
However existing dynamic spectrum management algorithms may not be suitable
when the available computation time and compute power are limited, i.e., when a
very fast responsiveness is required. In this paper, we present a new paradigm,
theory and algorithm for real-time dynamic spectrum management (RT-DSM) under
tight real-time constraints. Specifically, a RT-DSM algorithm can be stopped at
any point in time while guaranteeing a feasible and improved solution. This is
enabled by the introduction of a novel difference-of-variables (DoV)
transformation and problem reformulation, for which a primal coordinate ascent
approach is proposed with exact line search via a logarithmicly scaled grid
search. The concrete proposed algorithm is referred to as iterative power
difference balancing (IPDB). Simulations for different realistic wireline and
wireless interference limited systems demonstrate its good performance, low
complexity and wide applicability under different configurations.Comment: 14 pages, 9 figures. This work has been submitted to the IEEE for
possible publicatio
Self-optimizing Uplink Outer Loop Power Control for WCDMA Network
The increasing demands for high data rates, drives the efforts for more efficient usage of the finite natural radio spectrum resources. Existing wideband code division multiple access (WCDMA) uplink outer loop power control has difficulty to answer to the new load on air interface. The main reason is that the maximum allowed noise rise per single user is fixed value. In worst case uplink load can be so high that all services, including conversational service, could be blocked. In this paper investigation has been performed to present correlation of main system parameters, used by uplink outer loop power control, to uplink load. Simulation has been created and executed to present difference in current implementation of uplink outer loop power control against proposed changes. Proposed solution is self-optimizing uplink outer loop power control in a way that maximum allowed noise rise per single user would be dynamically changed based on current uplink load on cell
Benchmarking Practical RRM Algorithms for D2D Communications in LTE Advanced
Device-to-device (D2D) communication integrated into cellular networks is a
means to take advantage of the proximity of devices and allow for reusing
cellular resources and thereby to increase the user bitrates and the system
capacity. However, when D2D (in the 3rd Generation Partnership Project also
called Long Term Evolution (LTE) Direct) communication in cellular spectrum is
supported, there is a need to revisit and modify the existing radio resource
management (RRM) and power control (PC) techniques to realize the potential of
the proximity and reuse gains and to limit the interference at the cellular
layer. In this paper, we examine the performance of the flexible LTE PC tool
box and benchmark it against a utility optimal iterative scheme. We find that
the open loop PC scheme of LTE performs well for cellular users both in terms
of the used transmit power levels and the achieved
signal-to-interference-and-noise-ratio (SINR) distribution. However, the
performance of the D2D users as well as the overall system throughput can be
boosted by the utility optimal scheme, because the utility maximizing scheme
takes better advantage of both the proximity and the reuse gains. Therefore, in
this paper we propose a hybrid PC scheme, in which cellular users employ the
open loop path compensation method of LTE, while D2D users use the utility
optimizing distributed PC scheme. In order to protect the cellular layer, the
hybrid scheme allows for limiting the interference caused by the D2D layer at
the cost of having a small impact on the performance of the D2D layer. To
ensure feasibility, we limit the number of iterations to a practically feasible
level. We make the point that the hybrid scheme is not only near optimal, but
it also allows for a distributed implementation for the D2D users, while
preserving the LTE PC scheme for the cellular users.Comment: 30 pages, submitted for review April-2013. See also: G. Fodor, M.
Johansson, D. P. Demia, B. Marco, and A. Abrardo, A joint power control and
resource allocation algorithm for D2D communications, KTH, Automatic Control,
Tech. Rep., 2012, qC 20120910,
http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-10205
A Fast Algorithm for Sparse Controller Design
We consider the task of designing sparse control laws for large-scale systems
by directly minimizing an infinite horizon quadratic cost with an
penalty on the feedback controller gains. Our focus is on an improved algorithm
that allows us to scale to large systems (i.e. those where sparsity is most
useful) with convergence times that are several orders of magnitude faster than
existing algorithms. In particular, we develop an efficient proximal Newton
method which minimizes per-iteration cost with a coordinate descent active set
approach and fast numerical solutions to the Lyapunov equations. Experimentally
we demonstrate the appeal of this approach on synthetic examples and real power
networks significantly larger than those previously considered in the
literature
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