In this paper, we consider the performance of distributed control algorithms for networked robotic systems when one or more robots fail to execute the optimal policy. In particular, we investigate the performance of t...
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ISBN:
(纸本)9781467363563
In this paper, we consider the performance of distributed control algorithms for networked robotic systems when one or more robots fail to execute the optimal policy. In particular, we investigate the performance of the circumcenter algorithm with connectivity maintenance [1]-[3] when one or more adversarial agents act maliciously to maximally disrupt convergence of the remaining, cooperative agents. To this end, we formulate a performance objective for each adversary node in terms of the circumradii of its cooperative neighbors in a communication graph which does not require omniscience of adversaries as is often assumed in the literature (e.g., [4], [5]). We provide an optimization algorithm based on finite-horizon dynamic programming, and obtain solutions through numerical simulation. Our results show that in general adversarial nodes are able not only to impede convergence toward consensus, but can also affect global changes in the topology of the communication graph for the cooperative agents.
Algorithmic efficiency is essential to reducing energy use and time taken for computational problems. Optimizing efficiency is important for tasks involving multiple resources, for example in stochastic calculations w...
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This paper introduces a preconditioned convex splitting algorithm enhanced with line search techniques for nonconvex optimization problems. The algorithm utilizes second-order backward differentiation formulas (BDF) f...
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The branch current state estimators available in the existing literature consider the distribution networks as composed of lines and cables. In this paper, a general technique is demonstrated in order to handle other ...
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ISBN:
(纸本)9781479913022
The branch current state estimators available in the existing literature consider the distribution networks as composed of lines and cables. In this paper, a general technique is demonstrated in order to handle other key distribution network components such as transformers and voltage regulators. It is also demonstrated how to consider the tap positions of transformers and regulators as state variables in the estimation process given that they are rarely telemetered. The performance of iterative optimization algorithms depends strongly on the initial solution. In this paper, the load allocation algorithm is used in order to obtain an initial solution and associate loads with pseudo-measurements. The latter step is necessary in order to assure observability of the network. The load allocation algorithm used in this study is a straightforward tool based on ladder iterative algorithm.
In this paper we investigate low complexity joint transmit and receive antenna selection (JTRAS) algorithms for wireless spatial multiplexing (SM) systems. Unlike the conventional JTRAS algorithms that mainly use capa...
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ISBN:
(纸本)9781467363365
In this paper we investigate low complexity joint transmit and receive antenna selection (JTRAS) algorithms for wireless spatial multiplexing (SM) systems. Unlike the conventional JTRAS algorithms that mainly use capacity maximization based criterion, we propose a general method for joint transmit and receive antenna selection according to different selection criteria, including minimum mean square error (MMSE), maximum minimum signal-to-interference-plus-noise ratio (SINR), and maximum capacity. The proposed method for different selection criteria is based on the calculation of matrix inverse and the recursive matrix inverse update is developed to reduce computational complexity. Extensive simulation results show that our algorithms perform very close to the optimal exhaustive search algorithms and better than or equivalent to the suboptimal algorithms in terms of bit error rate (BER) and ergodic capacity in both the uncorrelated and highly correlated MIMO channels, while the computational complexity is much lower than the optimal algorithms.
The contribution of this paper is in two-folds: 1) If more predictive and intelligent control of the thermostat setpoints with no explicit models of Root Top Units (RTUs) yet with simplistic lumped parameter thermal m...
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ISBN:
(纸本)9781479917730
The contribution of this paper is in two-folds: 1) If more predictive and intelligent control of the thermostat setpoints with no explicit models of Root Top Units (RTUs) yet with simplistic lumped parameter thermal models of buildings can be effective in reducing a small commercial buildings summer-time peak load while adequately maintaining comfort levels, and 2) how this simplistic indirect control approach to RTUs compare to more sophisticated direct control approaches in terms of peak-load reduction and cost. First, the model-predictive control approach is presented. Second, the results of cloud-based implementation of the optimization algorithm at the two demonstration commercial buildings owned by General Electric (GE), optimizer characteristics, different set point trajectories and their implication with regards to peak load and comfort, and observations are described. On average, the savings from the indirect optimal control strategy utilized in our approach through a cloud-based control implementation architecture is shown to be comparable to previously stated savings in literature from more sophisticated direct optimal control of RTUs while the comfort levels are the same as the non-optimal strategy or slightly better in some cases.
Under low-carbon scheduling, to solve the hybrid lot-streaming flowshop scheduling (HLFS) problem, an improved migrating birds optimisation (IMBO) algorithm is proposed to minimise the total flow time. The neighbourho...
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ISBN:
(数字)9781728197388
ISBN:
(纸本)9781728197395
Under low-carbon scheduling, to solve the hybrid lot-streaming flowshop scheduling (HLFS) problem, an improved migrating birds optimisation (IMBO) algorithm is proposed to minimise the total flow time. The neighbourhood solution of the population is generated by insertion and exchange, and the population is further optimised by a local search method. In addition, a reset mechanism is added to avoid falling into a local optimum. Extensive computational results demonstrate the feasibility and effectiveness of the proposed algorithm.
We present Cyclades, a general framework for parallelizing stochastic optimization algorithms in a shared memory setting. Cyclades is asynchronous during model updates, and requires no memory locking mechanisms, simil...
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ISBN:
(纸本)9781510838819
We present Cyclades, a general framework for parallelizing stochastic optimization algorithms in a shared memory setting. Cyclades is asynchronous during model updates, and requires no memory locking mechanisms, similar to Hog-??wild!-type algorithms. Unlike HOGWILD!, Cyclades introduces no conflicts during parallel execution, and offers a black-box analysis for provable speedups across a large family of algorithms. Due to its inherent cache locality and conflict-??free nature, our multi-core implementation of Cyclades consistently outperforms Hogwild!-type algorithms on sufficiently sparse datasets, leading to up to 40% speedup gains compared to Hogwild!, and up to 5× gains over asynchronous implementations of variance reduction algorithms.
In contrast to the muscle recruitment during voluntary walking, only a limited number of muscles are activated during functional electrical stimulation (FES) based walking. This implies that a trajectory designed or r...
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ISBN:
(纸本)9781424441211
In contrast to the muscle recruitment during voluntary walking, only a limited number of muscles are activated during functional electrical stimulation (FES) based walking. This implies that a trajectory designed or recorded from the normal human walking data may not be the best choice for tracking control. Another major challenge during FES-based walking is the rapid onset of muscle fatigue. Two methods to reduce fatigue during FES-based walking are employing an orthosis and minimizing muscle activations. To deal with these aforementioned challenges, this paper presents firstly a dynamic model representing FES-elicited walking constrained by an orthosis and a walker. Secondly, this paper deals with the design of optimal stimulation and force profiles (instead of gait-trajectories from ablebodied humans) that minimize muscle activations via FES and arm reaction forces from the walker. Ten walking steps are simulated to show the feasibility of the walking model and optimization algorithm.
Curvature properties of convex objects, such as strong convexity, are important in designing and analyzing convex optimization algorithms in the Hilbertian or Riemannian settings. In the case of the Hilbertian setting...
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