Planning and scheduling for agents operating in heterogeneous, multi-agent environments is governed by the nature of the environment and the interactions between agents. Significant efficiency and capability gains can be attained by employing planning and scheduling mechanisms that are tailored to particular agent roles. This paper presents such a framework for a global sensor web that operates as a two-level hierarchy, where the mission level coordinates complex tasks globally and the resource level coordinates the operation of subtasks on individual sensor networks. We describe important challenges in coordinating among agents employing two different planning and scheduling methods and develop a coordination solution for this framework. Experimental results validate the benefits of employing guided, context-sensitive coordination of planning and scheduling in such sensor web systems.

This paper recalls a non-linear constructive method, based on controlling cascades of conic-systems as it applies to the control of quad-rotor aircraft. Such a method relied on the physical model of the system to construct high performance, modest sampling period (Ts = .02 s) and low complexity digital-controllers. The control of fixed-wing aircraft, however is not nearly a straight forward task in extending results related to the control of quad-rotor aircraft. Although fixed-wing aircraft and quad-rotor aircraft ultimately share the same kinematic equations of motion, fixed-wing aircraft are intimately dependent on their relationship to the wind reference frame. This additional coupling leads to additional equations of motion including those related to the angle-of attack, slide-slip-angle, and bank angle. As a result a more advanced non-linear control method known as back-stepping is required to compensate for non-passive non-linearity's. These back-stepping controllers are recursive in nature and can even address actuator magnitude and rate limitations and even include adaptability to unknown lift and drag coefficients. This paper presents a non-adaptive back-stepping controller which is aimed to verify a fixed-wing aircraft model not subject to actuator limitations (in order to simplify discussion). The back-stepping controller proposed is less complex then previously proposed controllers, exhibits similar response characteristics while being robust to both steady head wind shear and discrete-time wind gust disturbances.

Several localization algorithms exist for wireless sensor networks that use angle of arrival measurements to estimate node position. However, there are limited options for actually obtaining the angle of arrival using resource-constrained devices. In this paper, we describe a radio interferometric technique for determining bearings from an anchor node to any number of target nodes at unknown positions. The underlying idea is to group three of the four nodes that participate in a typical radio interferometric measurement together to form an antenna array. Two of the nodes transmit pure sinusoids at close frequencies that interfere to generate a low-frequency beat signal. The phase difference of the measured signal between the third array node and the target node constrains the position of the latter to a hyperbola. The bearing of the node can be estimated by the asymptote of the hyperbola. The bearing estimation is carried out by the node itself, hence the method is distributed, scalable and fast. Furthermore, this technique does not require modification of the mote hardware because it relies only on the radio. Experimental results demonstrate that our approach can estimate node bearings with an accuracy of approximately 3 degrees in 0.5 sec.

This paper proposes a combined energy-based and physics of failure model for degradation analysis and prognosis of electrolytic capacitors in DC-DC power converters. Electrolytic capacitors and MOSFET’s have higher failure rates than other components in DC-DC converter systems. Currently our work focuses on analyzing and modeling electrolytic capacitors degradation and its effects on the output of DC-DC converter systems. The output degradation is typically measured by the increase in ripple current and the drop in output voltage at the load. Typically the ripple current effects dominate, and they can have adverse effects on downstream components. For example, in avionics systems where the power supply drives a GPS unit, ripple currents can cause glitches in the GPS position and velocity output, and this may cause errors in the Inertial Navigation (INAV) system causing the aircraft to fly off course. A model based approach to studying degradation phenomena enables us to combine the energy based modeling of the DC-DC converter with physics of failures models of capacitor degradation, and predict using stochastic simulation methods how system performance deteriorates with time. This more systematic analysis may provide a more general and accurate method for computing the remaining useful life (RUL) of the component and the converter system. We have employed a topological energy based modeling scheme based on the bond graph (BG) modeling language for building parametric models of multi-domain physical systems. The BG approach captures relationship between component parameters, system behavior and performance. Component degradation models are constructed using empirical physics of failure models that have been presented in the literature, and validating these models using data collected from accelerated degradation studies. The physics of failure models provide mathematical formulations that are directly linked to component parameters. Literature reports a number of operating conditions that may cause capacitor degradation. These include High Voltage conditions, Transients, Reverse Bias, Strong Vibrations and high ripple current. In our work, we have studied the effects of capacitor degradation on DC-DC converter performance by developing a combination of converter system model and a physics of failure model of electrolytic capacitor degradation when subjected to thermal and electrical stresses. Thermal stress occurs when the capacitors operate in high temperature environments, while electrical stress conditions occur due to high operating voltages and even ripple currents above the rated values. In our work we are developing models to capture the failure phenomenon in these components. Our current work adopts a physics of failure model (Arrhenius Law) for equivalent series resistance (ESR) increase in electrolytic capacitors subjected to electrical and thermal stresses. Under stress conditions the ESR gradually increases and capacitance of the capacitor gradually decreases with time thus resulting in the capacitors ability to filter out AC components in the output voltage. As a result, the output ripples current and ripple voltages of the converter increases over time. The output DC voltage also decreases over time, but the ripple current effects on the load are more significant. High ripple currents may lead to frequent resets or even damage in the systems that are downstream from the power supply. We present a combined model- and data-driven approach for estimating and validating the parameters of our physics of failure models for capacitor degradation. We use Monte Carlo simulation methods to develop prognostic methods that predict remaining useful life based on degradation in the power supply output. For model simulation study the derived degradation model of the capacitors are reintroduced into the DC-DC converter system model to study changes in the system performance using Monte Carlo methods. The simulation results observed under different stress conditions are recorded and compared with the hardware experiments. We have designed different hardware setups for capturing the data of actual degradation phenomenon under thermal and electrical stress. In the first setup capacitors are subjected to only thermal stress. Under this condition output ripple voltage and increase in ESR is monitored over the period of time. In the second setup experiment the capacitors are subjected to electrical stress by continuous charging/discharging cycle. The ESR parameter is monitored regularly over this period of time. The data from these experiments is used to verify results from the models developed and also for refining the model parameters for more accuracy. The paper concludes with comments and future work to be done.

Current methods of estimating air quality involve assigning a single value called the Air Quality Index (AQI) to a large land area for a 24-hour period based on a very few, sparsely-located sensors. This produces a low-resolution image of the air quality in that region. We have devised a new mobile air quality monitoring network with the ability to provide high-resolution realtime pollution data at any location within the coverage area. We have prototyped sensors and proven the feasibility of the approach, and are currently testing a small-scale implementation using irregularly-sampled spatiotemporal measurements from mobile car-mounted sensors coupled with existing static data. This data feeds a web-based application, enabling users to view air quality in specific regions as well as estimate exposure over speci ed time periods and plan routes based on minimal exposure to a given pollutant.

Network security is a major issue affecting SCADA systems designed and deployed in the last decade. Simulation of network attacks on a SCADA system presents certain challenges, since even a simple SCADA system is composed of models in several domains and simulation environments. Here we demon- strate the use of C2WindTunnel to simulate a plant and its controller, and the Ethernet network that connects them, in different simulation environments. We also simulate DDOS-like attacks on a few of the routers to observe and analyze the effects of a network attack on such a system.

This paper proposes a model based approach to study the degradation effects of power supply converters on the avionics systems. Avionics systems combine physical processes, computational hardware, and software systems, and present unique challenges to performing root cause analysis when faults occur, and also for establishing the effects of faults on overall system behavior and performance. However, systematic analysis of these conditions are very important for analysis of safety and also to avoid catastrophic failures in navigation systems. A combined energy-based and physics of failure model approach is adopted for degradation analysis and prognosis of degrading components in DC-DC power converters. We have developed automated methods for generating Simulink models from bond graph representations of physical models. The bond graph models are also used to derive models for diagnostic and prognostic analysis. Further, we have also developed models of the software and hardware components of the GPS and INAV subsystems as Simulink™ modules. The complete system for studying the behaviors of the avionics system (both nominal and faulty) is implemented as a set of integrated Simulink modules. In avionics systems, degradations and faults in this unit propagates to the GPS and INAV systems. These can cause a variety of faults in these systems, e.g., ripple currents at the power supply output can cause glitches in the GPS position and velocity output, and this, in turn, produces errors in the Inertial Navigation (INAV) system calculations. One of the faults we have been studying in detail is electrolytic capacitor degradation in the power supply, and its effects on the functioning of the GPS unit. We apply qualitative fault signature methods for detecting and isolating faults in all three components of the avionics system. Fault signature generation is based on establishing causal relations between system parameters and measurements, and estimating the effect of a parameter value change (representing a fault) on the measured values. In the literature a number of operating conditions that cause capacitor degradation, such as High Voltage conditions, Transients, Reverse Bias, Strong Vibrations and high ripple current have been reported. Some of these conditions are observed by the power supplies embedded in the avionics systems. In this work, we study some of these conditions which lead to capacitor degradation i.e. due to thermal and electrical stresses. A topological energy based modeling scheme developed on the bond graph (BG) modeling language for building parametric models of multi-domain physical systems has been implemented. A model based approach to studying degradation phenomena enables us to combine the energy based modeling of the DC-DC converter with physics of failures models of capacitor degradation, and to predict using stochastic simulation methods how system performance deteriorates with time. This more systematic analysis may provide a more general and accurate method for computing the remaining useful life (RUL) of the component and the converter system. We adopt a physics of failure model (Arrhenius Law) for equivalent series resistance (ESR) increase in electrolytic capacitors subjected to electrical and thermal stresses. High ripple currents due to degradation lead to frequent resets and even damage in the systems that are downstream from the power supply. The literature indicates that the fluctuation in power supply voltage and excessive ripple currents could lead to various failures in the GPS receiver module. In this work we have simulated the GPS reset events due to voltage fluctuations. We have also simulated the loss of receiver lock due to excessive ripple current. We have demonstrated using our simulation models the effects of power supply faults on the overall performance of the GPS solution. Our methodology also provides a framework for developing efficient fault signature methods for fault detection and fault isolation. In future, we will conduct more detailed analysis of degradation effects, and their propagation to the different components of the system. We will also develop methods to quantify the effects of degradation on overall system performance.

This paper presents the framework of a mobile air quality monitoring network, with an in-depth discussion of several new innovative techniques for web-based visualization. These techniques allow typical web users to access high-resolution pollution data gathered from a large number of vehicle-mounted mobile sensing devices coupled with highly-accurate static sensor data in an easy-to-use, intuitive interface. Additionally, this interface o ffers users a set of novel applications to promote health and pollution awareness, including a green trip planner, whereby users can plot routes between two locations based on a path of least exposure to specifi ed pollutants, and an exposure estimator, which allows users to calculate previous levels of exposure to harmful pollutants based only on a single timed GPS track.

This work-in-progress paper introduces a new hardware platform for wireless sensor networks, summarizes the new challenges it creates for software development and describes a toolchain being developed to meet those challenges. The hardware platform is based on a low-power FPGA as opposed to a traditional microcontroller. The FPGA confi guration includes a soft core microcontroller, but there are plenty of resources left to implement a subset of the operating system, middleware and application components directly on the FPGA. Instead of creating this partition early in the design phase, we advocate a flexible hardware/software boundary enabling "late binding" of components to the softcore or the hardware fabric. This increases the complexity of the design space mandating sophisticated tool support. The paper describes a toolchain that helps manage this complexity. The two main tools are a domain-speci c modeling environment and a symbolic design-space exploration tool.