Bruce H. Krogh

Energy-efficient surveillance system using wireless sensor networks

The focus of surveillance missions is to acquire and verify information about enemy capabilities and positions of hostile targets. Such missions often involve a high element of risk for human personnel and require a high degree of stealthiness. Hence, the ability to deploy unmanned surveillance missions, by using wireless sensor networks, is of great practical importance for the military. Because of the energy constraints of sensor devices, such systems necessitate an energy-aware design to ensure the longevity of surveillance missions. Solutions proposed recently for this type of system show promising results through simulations. However, the simplified assumptions they make about the system in the simulator often do not hold well in practice and energy consumption is narrowly accounted for within a single protocol. In this paper, we describe the design and implementation of a running system for energy-efficient surveillance. The system allows a group of cooperating sensor devices to detect and track the positions of moving vehicles in an energy-efficient and stealthy manner. We can trade off energy-awareness and surveillance performance by adaptively adjusting the sensitivity of the system. We evaluate the performance on a network of 70 MICA2 motes equipped with dual-axis magnetometers. Our results show that our surveillance strategy is adaptable and achieves a significant extension of network lifetime. Finally, we share lessons learned in building such a complete running system.

Deadlock avoidance in flexible manufacturing systems with concurrently competing process flows

The concurrent flow of multiple jobs through a FMS can lead to deadlock conditions due to competition for limited resources in the system. The authors develop a Petri net (PN) model of concurrent job flow and dynamic resource allocation in an FMS and define deadlock in terms of transition enabling in the PN model. The problem of deadlock avoidance is addressed by introducing the notion of a restriction policy, which is a feedback policy for excluding some enabled transitions from the current resource allocation alternatives. The authors then present their deadlock avoidance algorithm (DAA) and prove that restricted deadlock can never occur for any resource allocation policy implemented under the DAA restriction policy. The DAA can be implemented easily in real time and is much less restrictive for FMS applications than existing algorithms for deadlock avoidance in computer systems. Application of the DAA is illustrated for three FMS examples: allocation of finite buffer space in a multicell machining facility, collision avoidance in a multirobot assembly cell, and coordination of multiple AGVs on a shop floor. >

VigilNet: An integrated sensor network system for energy-efficient surveillance

This article describes one of the major efforts in the sensor network community to build an integrated sensor network system for surveillance missions. The focus of this effort is to acquire and verify information about enemy capabilities and positions of hostile targets. Such missions often involve a high element of risk for human personnel and require a high degree of stealthiness. Hence, the ability to deploy unmanned surveillance missions, by using wireless sensor networks, is of great practical importance for the military. Because of the energy constraints of sensor devices, such systems necessitate an energy-aware design to ensure the longevity of surveillance missions. Solutions proposed recently for this type of system show promising results through simulations. However, the simplified assumptions they make about the system in the simulator often do not hold well in practice, and energy consumption is narrowly accounted for within a single protocol. In this article, we describe the design and implementation of a complete running system, called VigilNet, for energy-efficient surveillance. The VigilNet allows a group of cooperating sensor devices to detect and track the positions of moving vehicles in an energy-efficient and stealthy manner. We evaluate VigilNet middleware components and integrated system extensively on a network of 70 MICA2 motes. Our results show that our surveillance strategy is adaptable and achieves a significant extension of network lifetime. Finally, we share lessons learned in building such an integrated sensor system.

A Survey of Petri Net Methods for Controlled Discrete EventSystems

This paper surveys recent research on the application of Petri net models to the analysis and synthesis of controllers for discrete event systems. Petri nets have been used extensively in applications such as automated manufacturing, and there exists a large body of tools for qualitative and quantitative analysis of Petri nets. The goal of Petri net research in discrete event systems is to exploit the structural properties of Petri net models in computationally efficient algorithms for computing controls. We present an overview of the various models and problems formulated in the literature focusing on two particular models, the controlled Petri nets and the labeled nets. We describe two basic approaches for controller synthesis, based on state feedback and event feedback. We also discuss two efficient techniques for the on-line computation of the control law, namely the linear integer programming approach which takes advantage of the linear structure of the Petri net state transition equation, and path-based algorithms which take advantage of the graphical structure of Petri net models. Extensions to timed models are briefly described. The paper concludes with a discussion of directions for future research.

Synthesis of feedback control logic for a class of controlled Petri nets

An efficient solution is developed for a class of forbidden state problems for discrete event systems (DESs). DESs are considered which can be modeled as cyclic controlled marked graphs (CMGs), a special class of controlled Petri nets (CPNs). The distributed representation of the DES state in terms of the CMG marking permits an efficient specification of the forbidden states in terms of individual place markings. More important, it is shown that the graphical representations of the state transition logic in a CMG can be used to synthesize state feedback logic which is maximally permissive while guaranteeing the forbidden states will not occur. The practical application of the theoretical results is illustrated for an example of automated guided vehicle (AGV) coordination in a flexible manufacturing facility. >

Computational techniques for hybrid system verification

This paper concerns computational methods for verifying properties of polyhedral invariant hybrid automata (PIHA), which are hybrid automata with discrete transitions governed by polyhedral guards. To verify properties of the state trajectories for PIHA, the planar switching surfaces are partitioned to define a finite set of discrete states in an approximate quotient transition system (AQTS). State transitions in the AQTS are determined by the reachable states, or flow pipes, emitting from the switching surfaces according to the continuous dynamics. This paper presents a method for computing polyhedral approximations to flow pipes. It is shown that the flow-pipe approximation error can be made arbitrarily small for general nonlinear dynamics and that the computations can be made more efficient for affine systems. The paper also describes CheckMate, a MATLAB-based tool for modeling, simulating and verifying properties of hybrid systems based on the computational methods previously described.

Lightweight detection and classification for wireless sensor networks in realistic environments

A wide variety of sensors have been incorporated into a spectrum of wireless sensor network (WSN) platforms, providing flexible sensing capability over a large number of low-power and inexpensive nodes. Traditional signal processing algorithms, however, often prove too complex for energy-and-cost-effective WSN nodes. This study explores how to design efficient sensing and classification algorithms that achieve reliable sensing performance on energy-and-cost effective hardware without special powerful nodes in a continuously changing physical environment. We present the detection and classification system in a cutting-edge surveillance sensor network, which classifies vehicles, persons, and persons carrying ferrous objects, and tracks these targets with a maximum error in velocity of 15%. Considering the demanding requirements and strict resource constraints, we design a hierarchical classification architecture that naturally distributes sensing and computation tasks at different levels of the system. Such a distribution allows multiple sensors to collaborate on a sensor node, and the detection and classification results to be continuously refined at different levels of the WSN. This design enables reliable detection and classification without involving high-complexity computation, reduces network traffic, and emphasizes resilience and adaptation to the realistic environment. We evaluate the system with performance data collected from outdoor experiments and field assessments. Based on the experience acquired and lessons learned when developing this system, we abstract common issues and introduce several guidelines which can direct future development of detection and classification solutions based on WSNs.

Distributed model predictive control

We explore a distributed model predictive control (DMPC) scheme. The controllers apply model predictive control (MPC) policies to their local subsystems. They exchange their predictions by communication and incorporate the information from other controllers into their local MPC problem so as to coordinate with each other. For the full local state feedback and one-step delayed prediction exchange case, stability is ensured for controllable systems satisfying a matching condition by imposing stability constraints on the next state in the prediction. An example of multi-area load-frequency control is used as an example application for this DMPC scheme to show the performance of the scheme.

Wind Integration in Power Systems: Operational Challenges and Possible Solutions

This paper surveys major technical challenges for power system operations in support of large-scale wind energy integration. The fundamental difficulties of integrating wind power arise from its high inter-temporal variation and limited predictability. The impact of wind power integration is manifested in, but not limited to, scheduling, frequency regulations, and system stabilization requirements. Possible alternatives are suggested for a more reliable and cost-effective power system operation. New computationally efficient methods for improving system performances by using prediction and operational interdependencies over different time horizons remain critical open research problems.

Integrated path planning and dynamic steering control for autonomous vehicles

A method is presented for combining two previously proposed algorithms for path-planning and dynamic steering control into a computationally feasible scheme for real-time feedback control of autonomous vehicles in uncertain environments. In the proposed approach to vehicle guidance and control, Path Relaxation is used to compute critical points along a globally desirable path using a priori information and sensor data. Generalized potential fields are then used for local feedback control to drive the vehicle along a collision-free path using the critical points as subgoals. Simulation results are presented to demonstrate the control scheme.