Graph-theoretic characterisations of zeros for the input–output dynamics of complex network processes

Proceedings of the ACM/IEEE Sixth International Conference on Cyber-Physical Systems

Sahabandu

Dhal

et al. 2015

Self Cite

We explore the manipulation of networked cyber-physical devices via external actuation or feedback control at a single location, in the context of a canonical multi-agent system model known as the double integrator network. One main focus is to understand whether or not, and how easily, a stakeholder can manipulate network's full dynamics by designing the actuation signal for one agent (in an open-loop sense). Additionally, we investigate the ability of the stakeholder to manipulate the multi-agent system, and achieve control objectives, via local feedback control. For both problems, we find that manipulation of the dynamics is crucially dependent on the network's graph and associated spectrum.

Section: Local Closed-loop Controlmentioning

confidence: 99%

Local open- and closed-loop manipulation of multi-agent networks

Proceedings of the ACM/IEEE Sixth International Conference on Cyber-Physical Systems

Sahabandu

Dhal

et al. 2015

Self Cite

“…This matrix transforms the state vector inz = [z ′ 0 (1) ], ie, separate the states corresponding to the output and a derivative of the output, ie, infinite zero structure, from the remaining states. Although, Z does not transform the system into the SCB, this transformation is enough to find the zero state matrix (see the works of Chen et al 48 and Torres and Roy 49 ) sincez 0 in this new coordinates is not directly driven by the input nor directly affect the output, as shown in the following:z…”

Section: Local Closed-loop Controlmentioning

confidence: 99%

Local open‐ and closed‐loop manipulation of multiagent networks

Sahabandu

Intl J Robust & Nonlinear

Dhal³

et al. 2018

Self Cite

The manipulation of networked cyberphysical devices via local external actuation or feedback control is explored, in the context of a canonical multiagent dynamical system that is engaged in a consensus or synchronization task. One main focus is to understand whether or not, and how easily, a stakeholder can manipulate the full network's dynamics by hijacking only one agent's actuation signal. Explicit spectral characterizations are given of the energy (effort) required to manipulate the dynamics. These characterizations are used to (1) gain structural insights into ease of manipulation, (2) show that manipulation along the consensus manifold is easy, and (3) address network design to enable or prevent manipulation. Additionally, it is shown that the multiagent system can be manipulated effectively along the consensus manifold using local feedback controls, which do not require model knowledge or wide-area measurements.SAHABANDU ET AL. topology among the network's components. Thus, local actions in a CPN incur patterned wide-area impacts, regardless of the specifics of the local action or the network dynamics. In this work, we seek to understand whether and how local actuations can be designed to manipulate the network's wide-area behavior and to evaluate extreme impacts (whether beneficial or harmful). To do this, we consider a linear double-integrator network (DIN) model, which serves as a common abstraction for a number of CPN processes defined on a graph (eg, vehicle traffic on a highway, formation-controlled aerial vehicle teams, linearized swing dynamics of the electric power grid, and certain sensor-network algorithms). [6][7][8] This article explores the manipulation of the DIN via external actuation or feedback control at a single agent. First, we study whether or not the actuation signal for an agent can be designed to move the network's state to an arbitrary value and also the actuation effort (energy) required for manipulation. Characterizations are obtained in terms of the network's coupling parameters and the location of the manipulated agent. As a comparison, manipulation via a local feedback control is also considered, wherein only local measurements are used to decide the additional actuation of the agent. This is done by analyzing the transfer function of the dynamics from the perspective of the control channel, which then indicates whether or not the system can be manipulated to achieve certain control objectives (eg, fast tracking or disturbance rejection) in a feedback setting.The research described here contributes to an important research thrust on the security of cyberphysical systems (CPSs), which is a key property required for their effective operation (eg, the work of Banerjee et al 9 ). CPS security encompasses security of information, ie, the protection of sensitive or private information that is held by the CPS. In complement, CPS security also encompasses functional security, ie, protection of CPS functions from attacks and failures. The need for functional security for CPS is pa...

“…Many of these studies consider decentralized control of multiple autonomous but communicating agents (e.g., vehicles), which yields a closed-loop dynamics that is a network synchronization process. In complement, several recent studies have considered topology design to shape the performance of synchronization processes [21,2,3,27].…”

Section: Introductionmentioning

confidence: 99%

“…The authors focus particularly on symmetric unweighted network topologies, and give bounds on finite-zero locations and conditions for the presence of right-half-plane zeros. Meanwhile, our previous work pursues a structural decomposition of an input-output dynamics imposed on a synchronization process [3], and uses this decomposition to achieve simple graphical characterizations of the zeros. Motivated by vulnerability-analysis goals, control theorists have also studied robustification of synchronization processes via feedback [26], characterized disturbance propagation [13], and highlighted linkages between graph connectivity and network robustness (via the presence of non-trivial zero dynamics) [5,18,17].…”

Section: Introductionmentioning

confidence: 99%

“…In [3], we used the special coordinate basis (SCB) for linear systems [24] to obtain some preliminary structural results on the zeros of the SISO network model ( 1and (2)), which are foundational to the graph-theoretic results developed here. The SCB is a convenient tool for the graph-theoretic analysis of zeros, because it provides an explicit matrix-algebraic characterization of a system's zero structure.…”

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

Graph-theoretic analysis of network input–output processes: Zero structure and its implications on remote feedback control

Roy

2015

Automatica

Self Cite

The control of dynamical processes in networks is considered, in the case where measurement and actuation capabilities are sparse and possibly remote. Specifically, we study control of a canonical network dynamics, when only one network component's state can be measured and only one (in general different) component can be actuated. To do so, we characterize the finite-and infinite-zeros of the resulting SISO system in terms of the graph topology. Using these results, we establish graph-theoretic conditions under which there are zeros in the closed right-half plane. These conditions depend on the length, strength, and number of the paths from the component where the input is applied to the component where the measurements are made. Then, we present the implications of these conditions on the controller design task focusing in stabilizations/destabilization of network processes under static negative feedback.