25,487 research outputs found
Safe Control for Nonlinear Systems under Faults and Attacks via Control Barrier Functions
Safety is one of the most important properties of control systems. Sensor
faults and attacks and actuator failures may cause errors in the sensor
measurements and system dynamics, which leads to erroneous control inputs and
hence safety violations. In this paper, we improve the robustness against
sensor faults and actuator failures by proposing a class of Fault-Tolerant
Control Barrier Functions (FT-CBFs) for nonlinear systems. Our approach
maintains a set of state estimators according to fault patterns and
incorporates CBF-based linear constraints for each state estimator. We then
propose a framework for joint safety and stability by integrating FT-CBFs with
Control Lyapunov Functions. With a similar philosophy of utilizing redundancy,
we proposed High order CBF-based approach to ensure safety when actuator
failures occur. We propose a sum-of-squares (SOS) based approach to verify the
feasibility of FT-CBFs for both sensor faults and actuator failures. We
evaluate our approach via two case studies, namely, a wheeled mobile robot
(WMR) system in the presence of a sensor attack and a Boeing 747 lateral
control system under actuator failures.Comment: 15 pages, 5 figures, submitted to IEEE Transactions on Automatic
Contro
Fault-tolerant relay deployment based on length-constrained connectivity and rerouting centrality in wireless sensor networks
Wireless Sensor Networks (WSNs) are prone to failures. To be robust to failures, the network topology should provide alternative routes to the sinks so when failures occur the routing protocol can still offer reliable delivery. We define l-CRC, a new centrality index which measures a node’s importance to connectivity and efficient delivery in the network. We then use this centrality index to concentrate on the most important nodes, providing alternative paths around the nodes with high centrality. Varying l-CRC allows us to trade off cost for robustness. We introduce GRASP-ABP, a local search algorithm for initial robust topology design. We evaluate the algorithm empirically in terms of the number of additional nodes it suggests and its runtime. We then evaluate the robustness of the designs against node failures in simulation, and we demonstrate that the centrality-based GRASP-ABP’s designs are able to offer reliable delivery, comparable to competitor algorithms, but with fewer additional relays and faster runtime
On the strengths of connectivity and robustness in general random intersection graphs
Random intersection graphs have received much attention for nearly two
decades, and currently have a wide range of applications ranging from key
predistribution in wireless sensor networks to modeling social networks. In
this paper, we investigate the strengths of connectivity and robustness in a
general random intersection graph model. Specifically, we establish sharp
asymptotic zero-one laws for -connectivity and -robustness, as well as
the asymptotically exact probability of -connectivity, for any positive
integer . The -connectivity property quantifies how resilient is the
connectivity of a graph against node or edge failures. On the other hand,
-robustness measures the effectiveness of local diffusion strategies (that
do not use global graph topology information) in spreading information over the
graph in the presence of misbehaving nodes. In addition to presenting the
results under the general random intersection graph model, we consider two
special cases of the general model, a binomial random intersection graph and a
uniform random intersection graph, which both have numerous applications as
well. For these two specialized graphs, our results on asymptotically exact
probabilities of -connectivity and asymptotic zero-one laws for
-robustness are also novel in the literature.Comment: This paper about random graphs appears in IEEE Conference on Decision
and Control (CDC) 2014, the premier conference in control theor
Investigation of Air Transportation Technology at Princeton University, 1989-1990
The Air Transportation Technology Program at Princeton University proceeded along six avenues during the past year: microburst hazards to aircraft; machine-intelligent, fault tolerant flight control; computer aided heuristics for piloted flight; stochastic robustness for flight control systems; neural networks for flight control; and computer aided control system design. These topics are briefly discussed, and an annotated bibliography of publications that appeared between January 1989 and June 1990 is given
Precise Packet Loss Pattern Generation by Intentional Interference
Abstract—Intermediate-quality links often cause vulnerable
connectivity in wireless sensor networks, but packet losses caused by such volatile links are not easy to trace. In order to equip link layer protocol designers with a reliable test and debugging tool, we develop a reactive interferer to generate packet loss patterns precisely. By using intentional interference to emulate parameterized lossy links with very low intrusiveness, our tool facilitates both robustness evaluation of protocols and flaw detection in protocol implementation
The failure tolerance of mechatronic software systems to random and targeted attacks
This paper describes a complex networks approach to study the failure
tolerance of mechatronic software systems under various types of hardware
and/or software failures. We produce synthetic system architectures based on
evidence of modular and hierarchical modular product architectures and known
motifs for the interconnection of physical components to software. The system
architectures are then subject to various forms of attack. The attacks simulate
failure of critical hardware or software. Four types of attack are
investigated: degree centrality, betweenness centrality, closeness centrality
and random attack. Failure tolerance of the system is measured by a 'robustness
coefficient', a topological 'size' metric of the connectedness of the attacked
network. We find that the betweenness centrality attack results in the most
significant reduction in the robustness coefficient, confirming betweenness
centrality, rather than the number of connections (i.e. degree), as the most
conservative metric of component importance. A counter-intuitive finding is
that "designed" system architectures, including a bus, ring, and star
architecture, are not significantly more failure-tolerant than interconnections
with no prescribed architecture, that is, a random architecture. Our research
provides a data-driven approach to engineer the architecture of mechatronic
software systems for failure tolerance.Comment: Proceedings of the 2013 ASME International Design Engineering
Technical Conferences & Computers and Information in Engineering Conference
IDETC/CIE 2013 August 4-7, 2013, Portland, Oregon, USA (In Print
Robust detection, isolation and accommodation for sensor failures
The objective is to extend the recent advances in robust control system design of multivariable systems to sensor failure detection, isolation, and accommodation (DIA), and estimator design. This effort provides analysis tools to quantify the trade-off between performance robustness and DIA sensitivity, which are to be used to achieve higher levels of performance robustness for given levels of DIA sensitivity. An innovations-based DIA scheme is used. Estimators, which depend upon a model of the process and process inputs and outputs, are used to generate these innovations. Thresholds used to determine failure detection are computed based on bounds on modeling errors, noise properties, and the class of failures. The applicability of the newly developed tools are demonstrated on a multivariable aircraft turbojet engine example. A new concept call the threshold selector was developed. It represents a significant and innovative tool for the analysis and synthesis of DiA algorithms. The estimators were made robust by introduction of an internal model and by frequency shaping. The internal mode provides asymptotically unbiased filter estimates.The incorporation of frequency shaping of the Linear Quadratic Gaussian cost functional modifies the estimator design to make it suitable for sensor failure DIA. The results are compared with previous studies which used thresholds that were selcted empirically. Comparison of these two techniques on a nonlinear dynamic engine simulation shows improved performance of the new method compared to previous technique
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