Edge Selection in Bilinear Dynamical Networks

In large-scale networks, agents (e.g., sensors and actuators) and links (e.g., couplings and communication links) can fail or be (cyber-)attacked. In this paper, we focus on continuous-time bilinear networks, where additive disturbances model attack/uncertainty on agents/states (a.k.a. node disturbances) and multiplicative disturbances model attack/uncertainty on couplings between agents/states (a.k.a. link disturbances). We then investigate a network robustness notion in terms of the underlying digraph of the network, and structure of exogenous uncertainties/attacks. Specifically, we define the robustness measure using the H2-norm of the network and calculate it in terms of the reachability Gramian of the bilinear system. The main result shows that under certain conditions, the measure is supermodular over the set of all possible attacked links. The supermodular property facilitates the efficient solution finding of the optimization problem. We conclude the paper with a few examples illustrating how different structures can make the system more or less vulnerable to malicious attacks on links and present our concluding remarks.Comment: 6 pages, 2 figure

Determination of Design of Optimal Actuator Location Based on Control Energy

The thesis deals with the selection of the sets of inputs and outputs using the energy properties of the controllability and observability of a system and aims to define input and output structures which require minimization of the energy for control and state reconstruction. Such a study explores the energy dimension of the properties of controllability and observability, develops computations for the controllability and observability Gramians for stable and unstable systems and examines measures of the degree of controllability and observability properties using SVD (Singular Value Decomposition) of Gramians to compute the maximal and minimal energy requirements. These characterize the relative degree of controllability and observability under conditions where the available energy is constrained. The notion of energy surfaces in the state space is introduced and this enables the characterization of restricted notions of controllability and observability when the available energy is bounded. The maximal and minimal energy requirements for different input vectors is demonstrated and this provides the basis for the development of strategies and methodologies for selection of systems of inputs and outputs to minimize the energy required for control, respectively state reconstruction. These results enable the development of input, output structure selection methodology using a novel optimization method. This thesis contributes in the further development of the area of systems, or global instrumentation, developed so far based on the assignment of structural characteristics by incorporating the role of energy requirements. The research provides energy based tools for the selection of input and outputs schemes with a main criterion the minimization of the energy required for control and observation and thus provide an alternative approach based on quantitative system properties in characterizing control and state observation as functions of given sets of inputs and output sets. The methodologies developed may be used as design tools where apart from energy requirements other design criteria may be also incorporated for the selection of inputs and outputs. The methodology that is used is based on linear systems theory and tools from numerical linear algebra. The solution to the problems considered here is an integral part of the effort to develop an integrated approach to control and global process instrumentation

Optimal Approximate Minimization of One-Letter Weighted Finite Automata

In this paper, we study the approximate minimization problem of weighted finite automata (WFAs): to compute the best possible approximation of a WFA given a bound on the number of states. By reformulating the problem in terms of Hankel matrices, we leverage classical results on the approximation of Hankel operators, namely the celebrated Adamyan-Arov-Krein (AAK) theory. We solve the optimal spectral-norm approximate minimization problem for irredundant WFAs with real weights, defined over a one-letter alphabet. We present a theoretical analysis based on AAK theory, and bounds on the quality of the approximation in the spectral norm and $\ell^2$ norm. Moreover, we provide a closed-form solution, and an algorithm, to compute the optimal approximation of a given size in polynomial time.Comment: 32 pages. arXiv admin note: substantial text overlap with arXiv:2102.0686