On Resilient Control of Nonlinear Systems under Denial-of-Service

We analyze and design a control strategy for nonlinear systems under Denial-of-Service attacks. Based on an ISS-Lyapunov function analysis, we provide a characterization of the maximal percentage of time during which feedback information can be lost without resulting in the instability of the system. Motivated by the presence of a digital channel we consider event-based controllers for which a minimal inter-sampling time is explicitly characterized.Comment: 7 pages, 1 figur

Resilient Control under Denial-of-Service

We investigate resilient control strategies for linear systems under Denial-of-Service (DoS) attacks. By DoS attacks we mean interruptions of communication on measurement (sensor-to-controller) and/or control (controller-to-actuator) channels carried out by an intelligent adversary. We characterize the duration of these interruptions under which stability of the closed-loop system is preserved. The resilient nature of the control descends from its ability to adapt the sampling rate to the occurrence of the DoS.Comment: 10 pages, abridged version submitte

Self-triggered Coordination over a Shared Network under Denial-of-Service

The issue of security has become ever more prevalent in the analysis and design of cyber-physical systems. In this paper, we analyze a consensus network in the presence of Denial-of-Service (DoS) attacks, namely attacks that prevent communication among the network agents. By introducing a notion of Persistency-of-Communication (PoC), we provide a characterization of DoS frequency and duration such that consensus is not destroyed. An example is given to substantiate the analysis

Towards Stabilization of Distributed Systems under Denial-of-Service

In this paper, we consider networked distributed systems in the presence of Denial-of-Service (DoS) attacks, namely attacks that prevent transmissions over the communication network. First, we consider a simple and typical scenario where communication sequence is purely Round-robin and we explicitly calculate a bound of attack frequency and duration, under which the interconnected large-scale system is asymptotically stable. Second, trading-off system resilience and communication load, we design a hybrid transmission strategy consisting of Zeno-free distributed event-triggered control and Round-robin. We show that with lower communication loads, the hybrid communication strategy enables the systems to have the same resilience as in pure Round-robin

Bias estimation in sensor networks

This paper investigates the problem of estimating biases affecting relative state measurements in a sensor network. Each sensor measures the relative states of its neighbors and this measurement is corrupted by a constant bias. We analyse under what conditions on the network topology and the maximum number of biased sensors the biases can be correctly estimated. We show that for non-bipartite graphs the biases can always be determined even when all the sensors are corrupted, while for bipartite graphs more than half of the sensors should be unbiased to ensure the correctness of the bias estimation. If the biases are heterogeneous, then the number of unbiased sensors can be reduced to two. Based on these conditions, we propose some algorithms to estimate the biases.Comment: 12 pages, 8 figure

On Persistency of Excitation and Formulas for Data-Driven Control

In a paper by Willems and coworkers it was shown that persistently exciting data could be used to represent the input-output trajectory of a linear system. Inspired by this fundamental result, we derive a parametrization of linear feedback systems that paves the way to solve important control problems using data-dependent Linear Matrix Inequalities only. The result is remarkable in that no explicit system's matrices identification is required. The examples of control problems we solve include the state feedback stabilization and the linear quadratic regulation problems. We also extend the stabilization problem to the case of output feedback control design