Visible to the public Biblio

Found 1720 results

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Boggs, Wesley, Heaslip, Kevin, Louisell, Chuck.  2013.  Analysis of sign damage and failure: Utah case study. Transportation Research Record: Journal of the Transportation Research Board. :83–89.
Botha, Hermanus V., Boddhu, Sanjay K., McCurdy, Helena B., Gallagher, John C., Matson, Eric T., Kim, Yongho.  2015.  A Research Platform for Flapping Wing Micro Air Vehicle Control Study. Robot Intelligence Technology and Applications 3: Results from the 3rd International Conference on Robot Intelligence Technology and Applications. :135–150.

The split-cycle constant-period frequency modulation for flapping wing micro air vehicle control in two degrees of freedom has been proposed and its theoretical viability has been demonstrated in previous work. Further consecutive work on developing the split-cycle based physical control system has been targeted towards providing on-the-fly configurability of all the theoretically possible split-cycle wing control parameters with high fidelity on a physical Flapping Wing Micro Air Vehicle (FWMAV). Extending the physical vehicle and wing-level control modules developed previously, this paper provides the details of the FWMAV platform, that has been designed and assembled to aid other researchers interested in the design, development and analysis of high level flapping flight controllers. Additionally, besides the physical vehicle and the configurable control module, the platform provides numerous external communication access capabilities to conduct and validate various sensor fusion study for flapping flight control.

Brown, Fraser, Nötzli, Andres, Engler, Dawson.  2016.  How to Build Static Checking Systems Using Orders of Magnitude Less Code. Proceedings of the Twenty-First International Conference on Architectural Support for Programming Languages and Operating Systems. :143–157.
Brugarolas, R., Valero-Sarmiento, J. M., Bozkurt, A., Essick, G..  2016.  Auto-Adjusting Mandibular Repositioning Device for In-Home Use. 38th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, Orlando, FL
Brugarolas, R., Roberts, D., Sherman, B., Bozkurt, A..  2013.  Machine Learning Based Posture Estimation for a Wireless Canine Machine Interface. on Biomedical Wireless Technologies, Networks, and Sensing Systems (BioWireleSS),.
Burkay Orten, Prakash Ishwar, William Clement Karl, Venkatesh Saligrama.  2011.  Sensing structure in learning-based binary classification of high-dimensional data. 49th Annual Allerton Conference on Communication, Control, and Computing, Allerton 2011, Allerton Park {&} Retreat Center, Monticello, IL, USA, 28-30 September, 2011. :1521–1528.
Burkay Orten, Prakash Ishwar, W. Clem Karl, Venkatesh Saligrama, Homer H. Pien.  2011.  Sensing-aware classification with high-dimensional data. Proceedings of the {IEEE} International Conference on Acoustics, Speech, and Signal Processing, {ICASSP} 2011, May 22-27, 2011, Prague Congress Center, Prague, Czech Republic. :3700–3703.
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C. Guo, Z. Fu, S. Ren, Y. Jiang, L. Sha.  2017.  Towards Verifiable Safe and Correct Medical Best Practice Guideline Systems. 2017 IEEE 41st Annual Computer Software and Applications Conference (COMPSAC). 01:760-765.
C. Guo, S. Ren, Y. Jiang, P. L. Wu, L. Sha, R. B. Berlin.  2016.  Transforming Medical Best Practice Guidelines to Executable and Verifiable Statechart Models. 2016 ACM/IEEE 7th International Conference on Cyber-Physical Systems (ICCPS). :1-10.
C. Nowzari, J. Cortes.  2016.  Team-triggered coordination for real-time control of networked cyberphysical systems. 61:34-47.

This paper studies the real-time implementation of distributed controllers on networked cyberphysical systems. We build on the strengths of event- and self-triggered control to synthesize a unified approach, termed team-triggered, where agents make promises to one another about their future states and are responsible for warning each other if they later decide to break them. The information provided by these promises allows individual agents to autonomously schedule information requests in the future and sets the basis for maintaining desired levels of performance at lower implementation cost. We establish provably correct guarantees for the distributed strategies that result from the proposed approach and examine their robustness against delays, packet drops, and communication noise. The results are illustrated in simulations of a multi-agent formation control problem.

C. Nowzari, J. Cortes.  2014.  Zeno-free, distributed event-triggered communication and control for multi-agent average consensus. :2148-2153.

This paper studies a distributed event-triggered communication and control strategy that solves the multi-agent average consensus problem. The proposed strategy does not rely on the continuous or periodic availability of information to an agent about the state of its neighbors, but instead prescribes isolated event times where both communication and controller updates occur. In addition, all parameters required for its implementation can be locally determined by the agents. We show that the resulting network executions are guaranteed to converge to the average of the initial agents' states, establish that events cannot be triggered an infinite number of times in any finite time period (i.e., absence of Zeno behavior), and characterize the exponential rate of convergence. We also provide sufficient conditions for convergence in scenarios with time-varying communication topologies. Simulations illustrate our results.

C. Nowzari, J. Cortes.  2015.  Self-triggered and team-triggered control of networked cyber-physical systems. Event-Based Control and Signal Processing. :203-220.

This chapter describes triggered control approaches for the coordination of networked cyber-physical systems. Given the coverage of the other chapters of this book, our focus is on self-triggered control and a novel approach we term team-triggered control.

C. Nowzari, J. Cortes.  2016.  Distributed event-triggered coordination for average consensus on weight-balanced digraphs. 68:237-244.

This paper proposes a novel distributed event-triggered algorithmic solution to the multi-agent average consensus problem for networks whose communication topology is described by weight-balanced, strongly connected digraphs. The proposed event-triggered communication and control strategy does not rely on individual agents having continuous or periodic access to information about the state of their neighbors. In addition, it does not require the agents to have a priori knowledge of any global parameter to execute the algorithm. We show that, under the proposed law, events cannot be triggered an infinite number of times in any finite period (i.e., no Zeno behavior), and that the resulting network executions provably converge to the average of the initial agents' states exponentially fast. We also provide weaker conditions on connectivity under which convergence is guaranteed when the communication topology is switching. Finally, we also propose and analyze a periodic implementation of our algorithm where the relevant triggering functions do not need to be evaluated continuously. Simulations illustrate our results and provide comparisons with other existing algorithms.