An event-based approach to understanding decadal fluctuations in the Atlantic meridional overturning circulation

Many previous studies have shown that unforced climate model simulations exhibit decadal-scale fluctuations in the Atlantic meridional overturning circulation (AMOC), and that this variability can have impacts on surface climate fields. However, the robustness of these surface fingerprints across different models is less clear. Furthermore, with the potential for coupled feedbacks that may amplify or damp the response, it is not known whether the associated climate signals are linearly related to the strength of the AMOC changes, or if the fluctuation events exhibit nonlinear behaviour with respect to their strength or polarity. To explore these questions, we introduce an objective and flexible method for identifying the largest natural AMOC fluctuation events in multicentennial/multimillennial simulations of a variety of coupled climate models. The characteristics of the events are explored, including their magnitude, meridional coherence and spatial structure, as well as links with ocean heat transport and the horizontal circulation. The surface fingerprints in ocean temperature and salinity are examined, and compared with the results of linear regression analysis. It is found that the regressions generally provide a good indication of the surface changes associated with the largest AMOC events. However, there are some exceptions, including a nonlinear change in the atmospheric pressure signal, particularly at high latitudes, in HadCM3. Some asymmetries are also found between the changes associated with positive and negative AMOC events in the same model. Composite analysis suggests that there are signals that are robust across the largest AMOC events in each model, which provides reassurance that the surface changes associated with one particular event will be similar to those expected from regression analysis. However, large differences are found between the AMOC fingerprints in different models, which may hinder the prediction and attribution of such events in reality.

Observer-based control of multi-agent systems under decentralized information structure

This paper addresses the problem of decentralized implementation of a global state feedback controller for multi-agent systems. The system is assumed to be under the constraint of a complete decentralized information structure. The decentralization of the control task is achieved through the construction of low-order decentralized functional observers with the purpose of generating the required corresponding control signal for each local control station. A design procedure is developed for obtaining an approximate solution to the design of the observers. Stability analysis is provided for the global system using the proposed observer-based approach. A numerical example is given to illustrate the design procedure and cases when the observers' order increases from the lowest value.

Realistic grasping of rigid virtual objects through event-based haptics

This research presents a novel haptic grasping interface and demonstrates its ability within multi-point event-based feedback. Through experimental methodology, the dynamics involved in grasp contact interactions are modelled based on first principles. The proposed approach demonstrates a method of realistically representing grasp contact with rigid virtual objects through multi-point interaction.

Power-cycle-library-based control strategy for plug-in hybrid electric vehicles

It has been demonstrated that considering the knowledge of drive cycle as a priori in the PHEV control strategy can improve its performance. The concept of power cycle instead of drive cycle is introduced to consider the effect of noise factors in the prediction of future drivetrain power demand. To minimize the effect of noise factors, a practical solution for developing a power-cycle library is introduced. A control strategy is developed using the predicted power cycle which inherently improves the optimal operation of engine and consequently improves the vehicle performance. Since the control strategy is formed exclusively for each PHEV rather than a preset strategy which is designed by OEM, the effect of different environmental and geographic conditions, driver behavior, aging of battery and other components are considered for each PHEV. Simulation results show that the control strategy based on the driver library of power cycle would improve both vehicle performance and battery health.

A simulation-based control interface layer for a high-fidelity anthropomorphic training simulator

Deakin University’s futuristic Universal Motion simulator will overcome the limitations of current motion simulator platforms by employing an anthropomorphic robot arm to provide the motion fidelity necessary to exploit the potential of modern simulation environments. Full motion simulators frequently utilize Stewart platforms to mimic the movement of vehicles during simulation. However, due to the limited motion range and dexterity of such systems, and their inability to convey realistic accelerations, they are unable to represent accurate motion characteristics. The Universal Motion Simulation aims to close the gap between the limitations of the current motion technology and real world, by introducing a flexible, modular, high-fidelity motion system that can be used for a variety of immersive training applications. The modular nature of the design allows interchangeable and configurable simulation pods to be attached to the end effectors.

Detecting SMS-based control commands in a Botnet from infected android devices

An increasing number of Android devices are being infected and at risk of becoming part of a botnet. Among all types of botnets, control and cornmand based botnets are very popular. In this paper we introduce an effective and efficient method to ddect SMS-based control commands ftvm infected Android devices. Specifically, we rely on the important radio activities recorded in Android log files. These radio activities are currently overlooked by researchers. We show the effectiveness of our rnethod by using the examples frorn published literature. Our method requires much less user knowledge but is more generic than traditional approaches.

Observer-based control for time-varying delay neural networks with nonlinear observation

This paper studies the problem of designing observer-based controllers for a class of delayed neural networks with nonlinear observation. The system under consideration is subject to nonlinear observation and an interval time-varying delay. The nonlinear observation output is any nonlinear Lipschitzian function and the time-varying delay is not required to be differentiable nor its lower bound be zero. By constructing a set of appropriate Lyapunov-Krasovskii functionals and utilizing the Newton-Leibniz formula, some delay-dependent stabilizability conditions which are expressed in terms of Linear Matrix Inequalities (LMIs) are derived. The derived conditions allow simultaneous computation of two bounds that characterize the exponential stability rate of the closed-loop system. The unknown observer gain and the state feedback observer-based controller are directly obtained upon the feasibility of the derived LMIs stabilizability conditions. A simulation example is presented to verify the effectiveness of the proposed result.