Distributed Verification of Structural Controllability for Linear Time-Invariant Systems

Motivated by the development and deployment of large-scale dynamical systems, often composed of geographically distributed smaller subsystems, we address the problem of verifying their controllability in a distributed manner. In this work we study controllability in the structural system theoretic sense, structural controllability. In other words, instead of focusing on a specific numerical system realization, we provide guarantees for equivalence classes of linear time-invariant systems on the basis of their structural sparsity patterns, i.e., location of zero/nonzero entries in the plant matrices. To this end, we first propose several necessary and/or sufficient conditions to ensure structural controllability of the overall system, on the basis of the structural patterns of the subsystems and their interconnections. The proposed verification criteria are shown to be efficiently implementable (i.e., with polynomial time complexity in the number of the state variables and inputs) in two important subclasses of interconnected dynamical systems: similar (i.e., every subsystem has the same structure), and serial (i.e., every subsystem outputs to at most one other subsystem). Secondly, we provide a distributed algorithm to verify structural controllability for interconnected dynamical systems. The proposed distributed algorithm is efficient and implementable at the subsystem level; the algorithm is iterative, based on communication among (physically) interconnected subsystems, and requires only local model and interconnection knowledge at each subsystem

Structural Controllability of a Networked Dynamic System with LFT Parameterized Subsystems

This paper studies structural controllability for a networked dynamic system (NDS), in which each subsystem may have different dynamics, and unknown parameters may exist both in subsystem dynamics and in subsystem interconnections. In addition, subsystem parameters are parameterized by a linear fractional transformation (LFT). It is proven that controllability keeps to be a generic property for this kind of NDSs. Some necessary and sufficient conditions are then established respectively for them to be structurally controllable, to have a fixed uncontrollable mode, and to have a parameter dependent uncontrollable mode, under the condition that each subsystem interconnection link can take a weight independently. These conditions are scalable, and in their verifications, all arithmetic calculations are performed separately on each subsystem. In addition, these conditions also reveal influences on NDS controllability from subsystem input-output relations, subsystem uncontrollable modes and subsystem interconnection topology. Based on these observations, the problem of selecting the minimal number of subsystem interconnection links is studied under the requirement of constructing a structurally controllable NDS. A heuristic method is derived with some provable approximation bounds and a low computational complexity.Comment: Accepted by IEEE Transactions on Automatic Control as full paper, scheduled to appear in Volume 64 (2019), Issue 12 (December

On the Controllability and Observability of Networked Dynamic Systems

Some necessary and sufficient conditions are obtained for the controllability and observability of a networked system with linear time invariant (LTI) dynamics. The topology of this system is fixed but arbitrary, and every subsystem is permitted to have different dynamic input-output relations. These conditions essentially depend only on transmission zeros of every subsystem and the connection matrix among subsystems, which makes them attractive in the analysis and synthesis of a large scale networked system. As an application, these conditions are utilized to characterize systems whose steady state estimation accuracy with the distributed predictor developed in (Zhou, 2013) is equal to that of the lumped Kalman filter. Some necessary and sufficient conditions on system matrices are derived for this equivalence. It has been made clear that to guarantee this equivalence, the steady state update gain matrix of the Kalman filter must be block diagonal.Comment: 30 pages, 1 figur

Verification and Design of Resilient Closed-Loop Structured System

This paper addresses the resilience of large-scale closed-loop structured systems in the sense of arbitrary pole placement when subject to failure of feedback links. Given a structured system with input, output, and feedback matrices, we first aim to verify whether the closed-loop structured system is resilient to simultaneous failure of any subset of feedback links of a specified cardinality. Subsequently, we address the associated design problem in which given a structured system with input and output matrices, we need to design a sparsest feedback matrix that ensures the resilience of the resulting closed-loop structured system to simultaneous failure of any subset of feedback links of a specified cardinality. We first prove that the verification problem is NP-complete even for irreducible systems and the design problem is NP-hard even for so-called structurally cyclic systems. We also show that the design problem is inapproximable to factor (1-o(1))log n, where n denotes the system dimension. Then we propose algorithms to solve both the problems: a pseudo-polynomial algorithm to address the verification problem of irreducible systems and a polynomial-time O(log n)-optimal approximation algorithm to solve the design problem for a special feedback structure, so-called back-edge feedback structure.Comment: 14 Page

Controllability and data-driven identification of bipartite consensus on nonlinear signed networks

Nonlinear networked systems are of interest in several areas of research, such as multi-agent systems and social networks. In this paper, we examine the controllability of several classes of nonlinear networked dynamics on which the underlying graph admits negative weights. Such signed networks exhibit bipartite clustering when the underlying graph is structurally balanced. We show that structural balance is the key ingredient inducing uncontrollability when combined with a leader-node symmetry and a certain type of dynamical symmetry. We then examine the problem of extracting the bipartite structure of such graphs from data using Extended Dynamic Mode Decomposition to approximate the corresponding Koopman operator.Comment: To be presented at the 56th IEEE Conference on Decision and Control in Melbourne, Australi

Analysis and Design of Actuation-Sensing-Communication Interconnection Structures towards Secured/Resilient Closed-loop Systems

This paper considers the analysis and design of resilient/robust decentralized control systems. Specifically, we aim to assess how the pairing of sensors and actuators lead to architectures that are resilient to attacks/hacks for industrial control systems and other complex cyber-physical systems. We consider inherent structural properties such as internal fixed modes of a dynamical system depending on actuation, sensing, and interconnection/communication structure for linear discrete time-invariant dynamical systems. We introduce the notion of resilient fixed-modes free system that ensures the non-existence of fixed modes when the actuation-sensing-communication structure is compromised due to attacks by a malicious agent on actuators, sensors, or communication components and natural failures. Also, we provide a graph-theoretical characterization for the resilient structurally fixed modes that enables to capture the non-existence of resilient fixed modes for almost all possible systems' realizations. Additionally, we address the minimum actuation-sensing-communication co-design ensuring the non-existence of resiliently structurally fixed modes, which we show to be NP-hard. Notwithstanding, we identify conditions that are often satisfied in engineering settings and under which the co-design problem is solvable in polynomial-time complexity. Furthermore, we leverage the structural insights and properties to provide a convex optimization method to design the gain for a parametrized system and satisfying the sparsity of a given information pattern. Thus, exploring the interplay between structural and non-structural systems to ensure their resilience. Finally, the efficacy of the proposed approach is demonstrated on a power grid example

Affine Dependence of Network Controllability/Observability on Its Subsystem Parameters and Connections

This paper investigates observability/controllability of a networked dynamic system (NDS) in which system matrices of its subsystems are expressed through linear fractional transformations (LFT). Some relations have been obtained between this NDS and descriptor systems about their observability/controllability. A necessary and sufficient condition is established with the associated matrices depending affinely on subsystem parameters/connections. An attractive property of this condition is that all the required calculations are performed independently on each individual subsystem. Except well-posedness, not any other conditions are asked for subsystem parameters/connections. This is in sharp contrast to recent results on structural observability/controllability which is proven to be NP hard. Some characteristics are established for a subsystem which are helpful in constructing an observable/controllable NDS. It has been made clear that subsystems with an input matrix of full column rank are helpful in constructing an observable NDS, while subsystems with an output matrix of full row rank are helpful in constructing a controllable NDS. These results are extended to an NDS with descriptor form subsystems. As a byproduct, the full normal rank condition of previous works on network observability/controllability has been completely removed. On the other hand, satisfaction of this condition is shown to be appreciative in building an observable/controllability NDS.Comment: 15 pages, 1 figure. Results without proof of Section III in this paper have been presented in the 58th IEEE Conference on Decision and Control, Nice, France, 2019. This work has been submitted to the IEEE for possible publication. Copyright may be transferred without notice, after which this version may no longer be accessibl

Optimal Network Topology Design in Composite Systems with Constrained Neighbors for Structural Controllability

Composite systems are large complex systems con- sisting of interconnected agents (subsystems). Agents in a com- posite system interact with each other towards performing an in- tended goal. Controllability is essential to achieve desired system performance in linear time-invariant composite systems. Agents in a composite system are often uncontrollable individually, further, only a few agents receive input. In such a case, the agents share/communicate their private state information with pre-specified neighboring agents so as to achieve controllability. Our objective in this paper is to identify an optimal network topology, optimal in the sense of minimum cardinality information transfer between agents to guarantee the controllability of the composite system when the possible neighbor set of each agent is pre-specified. We focus on graph-theoretic analysis referred to as structural controllability as numerical entries of system matrices in complex systems are mostly unknown. We first prove that given a set of agents and the possible set of neighbors, finding a minimum cardinality set of information (interconnections) that must be shared to accomplish structural controllability of the composite system is NP-hard. Subsequently, we present a polynomial-time algorithm that finds a 2-optimal solution to this NP-hard problem. Our algorithm combines a minimum weight bipartite matching algorithm and a minimum spanning tree algorithm and gives a subset of interconnections which when established guarantees structural controllability, such that the worst-case performance is 2-optimal. Finally, we show that our approach directly extends to weighted constrained optimal net- work topology design problem and constrained optimal network topology design problem in switched linear systems

A unified framework for modeling and implementation of hybrid systems with synchronous controllers

This paper presents a novel approach to including non-instantaneous discrete control transitions in the linear hybrid automaton approach to simulation and verification of hybrid control systems. In this paper we study the control of a continuously evolving analog plant using a controller programmed in a synchronous programming language. We provide extensions to the synchronous subset of the SystemJ programming language for modeling, implementation, and verification of such hybrid systems. We provide a sound rewrite semantics that approximate the evolution of the continuous variables in the discrete domain inspired from the classical supervisory control theory. The resultant discrete time model can be verified using classical model-checking tools. Finally, we show that systems designed using our approach have a higher fidelity than the ones designed using the hybrid automaton approach.Comment: 16 page

A Graphical Characterization of Structurally Controllable Linear Systems with Dependent Parameters

One version of the concept of structural controllability defined for single-input systems by Lin and subsequently generalized to multi-input systems by others, states that a parameterized matrix pair $(A, B)$ whose nonzero entries are distinct parameters, is structurally controllable if values can be assigned to the parameters which cause the resulting matrix pair to be controllable. In this paper the concept of structural controllability is broadened to allow for the possibility that a parameter may appear in more than one location in the pair $(A, B)$. Subject to a certain condition on the parameterization called the "binary assumption", an explicit graph-theoretic characterization of such matrix pairs is derived