Stabilization over power-constrained parallel Gaussian channels

This technical note is concerned with state-feedback stabilization of multi-input systems over parallel Gaussian channels subject to a total power constraint. Both continuous-time and discrete-time systems are treated under the framework of H2 control, and necessary/sufficient conditions for stabilizability are established in terms of inequalities involving unstable plant poles, transmitted power, and noise variances. These results are further used to clarify the relationship between channel capacity and stabilizability. Compared to single-input systems, a range of technical issues arise. In particular, in the multi-input case, the optimal controller has a separation structure, and the lower bound on channel capacity for some discrete-time systems is unachievable by linear time-invariant (LTI) encoders/decoder

Field methods for rapidly characterizing contaminant mobility in paint waste during bridge rehabilitation

Currently, the New York State Department of Transportation (NYSDOT) uses a conservative approach of classifying all paint waste as hazardous from bridges undergoing rehabilitation which were constructed before 1989. This practice stems from the fact that there is no approved reliable, fast, and efficient method for classifying paint waste in-situ as non-hazardous. The main objective of this study was to develop a model that can predict the leachability of trace metals in paint waste generated during bridge rehabilitation. A statistically significant number of bridge sites were sampled based on hypothesis testing. Samples were then evaluated for total concentration of Resource Conservation and Recovery Act (RCRA) metals (i.e., Ag, As, Ba, Cd, Cr, Hg, Pb, and Se), iron as well as zinc. Leaching studies included the U.S. Environmental Protection Agency (U.S. EPA) toxicity characteristic leaching procedure (TCLP) and the multiple extraction procedure (MEP). Interestingly, although elevated Pb (5 to 168,090 mg kg-1) and other metal concentrations were observed in the paint samples, leaching results revealed only up to 22.6 mg L-1 for Pb and 9.52 mg L-1 for Cr. The relatively low concentrations observed are attributed to the use of iron-based abrasives (steel grit) in the paint removal process. In New York State, steel grit is typically applied as an abrasive material to remove paint during bridge rehabilitation. Although magnetic separation is applied to collect and reuse the steel grit, the fraction remaining in the paint waste ranges from 5 to 80% by weight. Using the suite of analyses, ferrihyidrite was observed to be an important mineral surface on the steel grit; spherical particle aggregates ranged from 20 to 200 nm in diameter. In addition, sequential extraction revealed trace metal sorption to the iron oxide surface may be the dominant mechanism responsible for the reduced leaching observed. The sorption process was further modeled using the diffuse layer model. Based on an understanding of mechanistic processes along with a demonstrated analysis of variables through principal component analysis (PCA), statistically-based models for leaching from paint waste were developed. Results of this work assist in better understanding and predicting the mobility of trace metals as well as in addressing disposal and management of paint waste during bridge rehabilitation

Stability Analysis of Continuous-Time Switched Systems with a Random Switching Signal

This paper is concerned with the stability analysis of continuous-time switched systems with a random switching signal. The switching signal manifests its characteristics with that the dwell time in each subsystem consists of a fixed part and a random part. The stochastic stability of such switched systems is studied using a Lyapunov approach. A necessary and sufficient condition is established in terms of linear matrix inequalities. The effect of the random switching signal on system stability is illustrated by a numerical example and the results coincide with our intuition.Comment: 6 pages, 6 figures, accepted by IEEE-TA

Proportional fairness in wireless powered CSMA/CA based IoT networks

This paper considers the deployment of a hybrid wireless data/power access point in an 802.11-based wireless powered IoT network. The proportionally fair allocation of throughputs across IoT nodes is considered under the constraints of energy neutrality and CPU capability for each device. The joint optimization of wireless powering and data communication resources takes the CSMA/CA random channel access features, e.g. the backoff procedure, collisions, protocol overhead into account. Numerical results show that the optimized solution can effectively balance individual throughput across nodes, and meanwhile proportionally maximize the overall sum throughput under energy constraints.Comment: Accepted by Globecom 201

Topology Recoverability Prediction for Ad-Hoc Robot Networks: A Data-Driven Fault-Tolerant Approach

Faults occurring in ad-hoc robot networks may fatally perturb their topologies leading to disconnection of subsets of those networks. Optimal topology synthesis is generally resource-intensive and time-consuming to be done in real time for large ad-hoc robot networks. One should only perform topology re-computations if the probability of topology recoverability after the occurrence of any fault surpasses that of its irrecoverability. We formulate this problem as a binary classification problem. Then, we develop a two-pathway data-driven model based on Bayesian Gaussian mixture models that predicts the solution to a typical problem by two different pre-fault and post-fault prediction pathways. The results, obtained by the integration of the predictions of those pathways, clearly indicate the success of our model in solving the topology (ir)recoverability prediction problem compared to the best of current strategies found in the literature