This paper proposes an analytical framework for co-designing wireless networked control systems (WNCSs) demonstrated in an industrial scenario. The framework allows us to quantitatively characterize the impact of wireless channel model accuracy when designing a controller to stabilize a WNCS. We consider a scenario consisting of two co-located wireless networks: the first connects the plant automation network backbone to field devices via WirelessHART, ISA-100.11a, or IEEE 802.15.4e, and the second uses IEEE 802.11 equipment to supply real-time multimedia data to the supervisory devices. First, we derive a parametric 802.11 interference characterization for an arbitrary number of active interfering devices and perform extensive parametric analysis. We then derive the message and packet error probability expressions necessary to develop an appropriate finite-state Markov channel model. Finally, we ran sizeable Monte Carlo simulations to evaluate the impact of our channel model on the control performance of a wireless closed-loop system and compared it with the performance obtained using a Bernoulli channel model.
[J04]
Optimal Output-Feedback Control Over Markov Wireless Communication Channels.
Anastasia Impicciatore, Yuriy Zacchia Lun, Pierdomenico Pepe, and Alessandro D’Innocenzo.
IEEE Transactions on Automatic Control, vol. 69, no. 3, Mar. 2024, pp. 1643–1658.
The communication links connecting components of wireless control systems may be affected by packet losses due to time-varying fading and interference. We consider a wireless control network (WCN) with double-sided packet-losses: on the sensor-controller link (sensing link) and controller-actuator link (actuation link). We model the sensing and actuation links as finite-state Markov channels (FSMCs). One time-step delay affects the actuation link mode observation, while the sensing link mode observation is not affected by any delay. In this paper, we solve, as our main contribution, the optimal output-feedback control problem in this FSMC setting (under a TCP-like communication scheme) using two different state estimation techniques: Luenberger observer and current estimator, comparing the two methodologies and deriving a separation principle for both the cases. We also derive detectability conditions guaranteeing the existence of an optimal observer, either Luenberger or current.
[J03]
Railway Cyber-Security in the Era of Interconnected Systems: A Survey.
Simone Soderi, Daniele Masti, and Yuriy Zacchia Lun .
IEEE Transactions on Intelligent Transportation Systems, vol. 24, no. 7, Mar. 2023, pp. 6764–6779.
Technological advances in the telecommunications industry have brought significant advantages in the management and performance of communication networks. The railway industry is among the ones that have benefited the most. These interconnected systems, however, have a wide area exposed to cyberattacks. This survey examines the cybersecurity aspects of railway systems by considering the standards, guidelines, frameworks, and technologies used in the industry to assess and mitigate cybersecurity risks, particularly regarding the relationship between safety and security. To do so, we dedicate specific attention to signaling, which fundamental reliance on computer and communication technologies allows us to explore better the multifaceted nature of the security of modern hyperconnected railway systems. With this in mind, we then move on to analyzing the approaches and tools that practitioners can use to facilitate the cyber security process. In detail, we present a view on cyber ranges as an enabling technology to model and emulate computer networks and attack-defense scenarios, study vulnerabilities’ impact, and finally devise countermeasures. We also discuss several possible use cases strongly connected to the railway industry reality.
[J02]
Robust stability of polytopic time-inhomogeneous Markov jump linear systems.
Yuriy Zacchia Lun, Alessandro D’Innocenzo, and Maria Domenica Di Benedetto.
The transition probabilities of jumps between operational modes of discrete-time Markov(ian) jump linear systems (dtMJLSs) are generally considered to be time-invariant, certain, and often completely known in the majority of dedicated studies. Still, in most real cases the transition probability matrix (TPM) cannot be computed exactly and is time-varying. In this article, we take into account the uncertainty and time-variance of the jump parameters by considering the underlying Markov chain as polytopic and time-inhomogeneous, i.e., its TPM is varying over time with variations that are arbitrary within a polytopic set of stochastic matrices. We show that the conditions used for time-homogeneous dtMJLSs are not enough to ensure the stability of the time-inhomogeneous system, and that perturbations on values of the TPM can make a stable system unstable. We present necessary and sufficient conditions for mean square stability (MSS) of polytopic time-inhomogeneous dtMJLSs, prove that deciding MSS on such systems is NP-hard and that MSS is equivalent to exponential MSS and to stochastic stability. We also derive necessary and sufficient conditions for robust MSS of dtMJLSs affected by polytopic uncertainties on transition probabilities and bounded disturbances.
[J01]
State of the art of cyber-physical systems security: An automatic control perspective.
Yuriy Zacchia Lun, Alessandro D’Innocenzo, Francesco Smarra, Ivano Malavolta, and Maria Domenica Di Benedetto.
Journal of Systems and Software, vol. 149, Mar. 2019, pp. 174–216.
Cyber-physical systems are integrations of computation, networking, and physical processes. Due to the tight cyber-physical coupling and to the potentially disrupting consequences of failures, security here is one of the primary concerns. Our systematic mapping study sheds light on how security is actually addressed when dealing with cyber-physical systems from an automatic control perspective. The provided map of 138 selected studies is defined empirically and is based on, for instance, application fields, various system components, related algorithms and models, attacks characteristics and defense strategies. It presents a powerful comparison framework for existing and future research on this hot topic, important for both industry and academia.
Conference Articles
[C15]
Wireless networked control over lossy uplinks abstracted by finite-state Markov channels.
Yuriy Zacchia Lun, Claudia Rinaldi, Fortunato Santucci, and Alessandro D’Innocenzo.
In proc. of the 22nd IFAC World Congress: IFAC-PapersOnLine (56) 2, Jul. 2023, pp. 3041–3047.
Networked control systems using wireless links to convey information among sensors, controllers, and actuators greatly benefit from having an accurate estimate of the communication channel condition. To this end, the finite-state Markov channel abstraction allows for reliable channel state estimation. This paper develops a Markov jump linear system representation for wireless networked control with intermittent channel state observation, message losses, and generalized hold-input dropout compensation. Furthermore, it exploits the emerging structural properties of the system to solve the finite-horizon linear quadratic regulation problem efficiently.
[C14]
Secure state estimation over Markov wireless communication channels.
Anastasia Impicciatore, Anastasios Tsiamis, Yuriy Zacchia Lun, Alessandro D’Innocenzo, and George J. Pappas.
In proc. of the 61st IEEE Conference on Decision and Control (CDC), Dec. 2022, pp. 2935–2940.
This note studies state estimation in wireless networked control systems with secrecy against eavesdropping. Specifically, a sensor transmits a system state information to the estimator over a legitimate user link, and an eavesdropper overhears these data over its link independent of the user link. Each connection may be affected by packet losses and is modeled by a finite-state Markov channel (FSMC), an abstraction widely used to design wireless communication systems. This paper presents a novel concept of optimal mean square expected secrecy over FSMCs and delineates the design of a secrecy parameter requiring the user mean square estimation error (MSE) to be bounded and eavesdropper MSE unbounded. We illustrate the developed results on an example of an inverted pendulum on a cart whose parameters are estimated remotely over a wireless link exposed to an eavesdropper.
[C13]
Learning Markov models of fading channels in wireless control networks: a regression trees based approach.
Luis Felipe Florenzan Reyes, Francesco Smarra, Yuriy Zacchia Lun, and Alessandro D’Innocenzo.
In proc. of the 29th Mediterranean Conference on Control and Automation (MED), Jun. 2021, pp. 232–237.
Finite-state Markov models are widely used for modeling wireless channels affected by a variety of non-idealities, ranging from shadowing to interference. In an industrial environment, the derivation of a Markov model based on the wireless communication physics can be prohibitive as it requires a complete knowledge of both the communication dynamics parameters and of the disturbances/interferers. In this work, a novel methodology is proposed to learn a Markov model of a fading channel via historical data of the signal-to-interference-plus-noise-ratio (SINR). Such methodology can be used to derive a Markov jump model of a wireless control network, and thus to design a stochastic optimal controller that takes into account the interdependence between the plant and the wireless channel dynamics. The proposed method is validated by comparing its prediction accuracy and control performance with those of a stationary finite-state Markov chain derived assuming perfect knowledge of the physical channel model and parameters of a WirelessHART point-to-point communication based on the IEEE-802.15.4 standard.
[C12]
Optimal output-feedback control and separation principle for Markov jump linear systems modeling wireless networked control scenarios.
Anastasia Impicciatore, Yuriy Zacchia Lun, Pierdomennico Pepe, and Alessandro D’Innocenzo.
In proc. of the 2021 American Control Conference (ACC), May 2021, pp. 2700–2706.
The communication channels used to convey information between the components of wireless networked control systems (WNCSs) are subject to packet losses due to time-varying fading and interference. We consider a wireless networked control scenario, where the packet loss occurs in both the sensor-controller link (sensing link), and the controller-actuator link (actuation link). Moreover, we consider one time-step delay mode observations of the actuation link. While the problems of state feedback optimal control and stabilizability conditions for systems with one time-step delay mode observations of the actuation link have been already solved, we study the optimal output feedback control problem, and we derive a separation principle for the aforementioned wireless networked control scenario. Particularly, we show that the optimal control problem (with one time step delay in the mode observation of actuation link state) and the optimal filtering problem can be solved independently under a TCP-like communication scheme.
[C11]
On the impact of accurate radio link modeling on the performance of WirelessHART control networks.
Yuriy Zacchia Lun, Claudia Rinaldi, Amal Alrish, Alessandro D’Innocenzo, and Fortunato Santucci.
In proc. of the 39th IEEE Conference on Computer Communications (INFOCOM), Jul. 2020, pp. 2430–2439.
The challenges in analysis and co-design of wireless networked control systems are well highlighted by considering wireless industrial control protocols. In this perspective, this paper addresses the modeling and design challenge by focusing on WirelessHART, which is a networking protocol stack widely adopted for wireless industrial automation. Specifically, we first develop and validate a Markov channel model that abstracts the WirelessHART radio link subject to channel impairments and interference. The link quality metrics introduced in the theoretical framework are validated in order to enable the accurate representation of the average and extreme behavior of the radio link. By adopting these metrics, it is straightforward to handle a consistent finite-state abstraction. On the basis of such a model, we then derive a stationary Markov jump linear system model that captures the dynamics of a control loop closed over the radio link. Subsequently, we show that our modeling framework is able to discover and manage the challenging subtleties arising from bursty behavior. A relevant theoretical outcome consists in designing a controller that guarantees stability and improves control performance of the closed-loop system, where other approaches based on a simplified channel model fail.
[C10]
Stabilizability of Markov jump linear systems modeling wireless networked control scenarios.
Yuriy Zacchia Lun, and Alessandro D’Innocenzo.
In proc. of the 58th IEEE Conference on Decision and Control (CDC), Dec. 2019, pp. 5766–5772.
The communication channels used to convey information between the components of wireless networked control systems (WNCSs) are subject to packet losses due to time-varying fading and interference. The WNCSs with missing packets can be modeled as Markov jump linear systems with one time-step delayed mode observations. While the problem of the optimal linear quadratic regulation for such systems has been already solved, we derive the necessary and sufficient conditions for stabilizability. We also show, with an example considering a communication channel model based on WirelessHART (a on-the-market wireless communication standard specifically designed for process automation), that such conditions are essential to the analysis of WNCSs where packet losses are modeled with Bernoulli random variables representing the expected value of the real random process governing the channel.
[C09]
Linear quadratic regulation of polytopic time-inhomogeneous Markov jump linear systems.
Yuriy Zacchia Lun, Alessandro Abate, and Alessandro D’Innocenzo.
In proc. of the 17th European Control Conference (ECC), Jun. 2019, pp. 4094–4099.
In most real cases transition probabilities between operational modes of Markov jump linear systems cannot be computed exactly and are time-varying. We take into account this aspect by considering Markov jump linear systems where the underlying Markov chain is polytopic and time-inhomogeneous, i.e. its transition probability matrix is varying over time, with variations that are arbitrary within a polytopic set of stochastic matrices. We address and solve for this class of systems the infinite-horizon optimal control problem. In particular, we show that the optimal controller can be obtained from a set of coupled algebraic Riccati equations, and that for mean square stabilizable systems the optimal finite-horizon cost corresponding to the solution to a parsimonious set of coupled difference Riccati equations converges exponentially fast to the optimal infinite-horizon cost related to the set of coupled algebraic Riccati equations. All the presented concepts are illustrated on a numerical example showing the efficiency of the provided solution.
[C08]
Work in Progress: Systematic Derivation of Accurate Analytic Markov Channel Models for Industrial Control.
Amal Alrish, Yuriy Zacchia Lun, Alessandro D’Innocenzo, and Fortunato Santucci.
In proc. of the 15th IEEE International Workshop on Factory Communication Systems (WFCS), May 2019, pp. 1–4.
The motivation of this work is to systematically derive an accurate Markov channel model suitable to represent any industrial communication protocol. This model accounts for both channel and control dynamics. Our analytic model is derived by taking into account multiple interferers and physical phenomena characterizing a communication link. Our finite-state Markov channel model matches both average packet error probability and worst case bursty behavior of the accurate analytic model of the channel.
[C07]
Approximate abstractions of Markov chains with interval decision processes.
Yuriy Zacchia Lun, Jack Wheatley, Alessandro D’Innocenzo, and Alessandro Abate.
In proc. of the 6th IFAC Conference on Analysis and Design of Hybrid Systems (ADHS): IFAC-PapersOnLine (51) 16, Jul. 2018, pp. 91–96.
This work introduces a new abstraction technique for reducing the state space of large, discrete-time labelled Markov chains. The abstraction leverages the semantics of interval Markov decision processes and the existing notion of approximate probabilistic bisimulation. Whilst standard abstractions make use of abstract points that are taken from the state space of the concrete model and which serve as representatives for sets of concrete states, in this work the abstract structure is constructed considering abstract points that are not necessarily selected from the states of the concrete model, rather they are a function of these states. The resulting model presents a smaller one-step bisimulation error, when compared to a like-sized, standard Markov chain abstraction. We outline a method to perform probabilistic model checking, and show that the computational complexity of the new method is comparable to that of standard abstractions based on approximate probabilistic bisimulations.
[C06]
Optimal robust control and a separation principle for polytopic time-inhomogeneous Markov jump linear systems.
Yuriy Zacchia Lun, Alessandro D’Innocenzo, Alessandro Abate, and Maria Domenica Di Benedetto.
In proc. of the 56th IEEE Conference on Decision and Control (CDC), Dec. 2017, pp. 6525–6530.
Markov-jump linear systems (MJLSs) allow representing linear systems subject to abrupt parameter changes modeled as a Markov chain, and are useful in many application domains. In most real cases the transition probabilities between operational modes of such systems cannot be computed exactly and are time-varying. We take into account this aspect by considering MJLSs where the underlying Markov chain is polytopic and time-inhomogeneous, i.e. its transition probability matrix is varying over time with variations that are arbitrary within a polytopic set of stochastic matrices. We address and solve for this class of systems the finite horizon optimal control and filtering problems. In particular, we show that the optimal controller having only partial information on the continuous state can be obtained from two types of coupled Riccati difference equations (CRDEs), one associated to the control problem, and the other one associated to the filtering problem.
[C05]
Robust LQR for time-inhomogeneous Markov jump switched linear systems.
Yuriy Zacchia Lun, Alessandro D’Innocenzo, and Maria Domenica Di Benedetto.
In proc. of the 20th IFAC World Congress: IFAC-PapersOnLine (50) 1, Jul. 2017, pp. 2199–2204.
Markov jump switched linear systems (MJSLSs) are switched linear systems, where a switching signal is governed by a Markov decision process. We consider a polytopic time-inhomogeneous setting, where the transition probabilities (between the operational modes of the system) associated to each discrete action are varying over time, with variations that are arbitrary within a polytopic set. We present and solve for this class of systems the finite horizon optimal control problem.
[C04]
Robust stability of time-inhomogeneous Markov jump linear systems.
Yuriy Zacchia Lun, Alessandro D’Innocenzo, and Maria Domenica Di Benedetto.
In proc. of the 20th IFAC World Congress: IFAC-PapersOnLine (50) 1, Jul. 2017, pp. 3418–3423.
In this work we derive necessary and sufficient conditions for robust mean square stability of discrete-time time-inhomogeneous Markov jump linear systems (MJLSs) affected by polytopic uncertainties on transition probabilities and bounded disturbances.
[C03]
On stability of time-inhomogeneous Markov jump linear systems.
Yuriy Zacchia Lun, Alessandro D’Innocenzo, and Maria Domenica Di Benedetto.
In proc. of the 55th IEEE Conference on Decision and Control (CDC), Dec. 2016, pp. 5527–5532.
In this work we present necessary and sufficient conditions for mean square stability (MSS) of discrete-time time-inhomogeneous Markov jump linear systems (MJLS) affected by polytopic uncertainties on transition probabilities. We also prove that deciding MSS on such systems is NP-hard and that MSS is equivalent to exponential mean square stability (EMSS) and to stochastic stability (SS).
[C02]
WSN-Aided People Localization: A Ray Tracing Network Planning and Performance Analysis Tool.
Yuriy Zacchia Lun, Stefano Tennina, Marco Di Renzo, Fabio Graziosi, and Christos Verikoukist.
In proc. of the 11th ACM Conference on Embedded Networked Sensor Systems (SenSys), Nov. 2013.
Wireless Sensor Networks (WSNs) are fostering pervasive healthcare applications, where people are remotely monitored, without the full time assistance of professional care-givers. A key enabling element is the possibility to locate people in indoor environments, especially in emergency situations. Framed within the WSN4QoL project, this paper proposes the use of a ray tracing model for network planning, to support efficient people localization and performance analysis. Preliminary results show accurate radio coverage estimations, with a minimal calibration effort.
[C01]
WSN4QoL: Wireless Sensor Networks for quality of life.
Stefano Tennina, Elli Kartsakli, Aristeidis Lalos, Angelos Antonopoulos, P-V Mekikis, Marco Di Renzo, Yuriy Zacchia Lun, Fabio Graziosi, Luis Alonso, and Christos Verikoukis.
In proc. of the 15th IEEE International Conference on e-Health Networking, Applications and Services (HealthCom), Oct. 2013, pp. 277–279.
Life expectancy is projected to increase significantly in the coming years. This fact has pushed the need for designing new and more pervasive healthcare systems. In this field, distributed and networked embedded systems, such as Wireless Sensor Networks (WSNs), are the most suitable technology to achieve continuous monitoring of aged people for their own safety, without affecting their daily activities. This paper proposes recent advancements in this field by introducing WSN4QoL, a Marie Curie project which involves academic and industrial partners from three EU countries. The project aims to propose new WSN-based technologies to meet the specific requirements of pervasive healthcare applications. In particular, in this paper, a Network Coding (NC) mechanism and a distributed localization solution are presented. They have been implemented on WSN testbeds to achieve efficiency in the communications and to enable indoor people tracking. Preliminary results in a real environment show good system performance that meet our expectations.
Theses
[T01]
Stability and optimal control of polytopic time-inhomogeneous Markov jump linear systems.
Yuriy Zacchia Lun. Advisors: Maria Domenica Di Benedetto and Alessandro D’Innocenzo.
PhD dissertation. Gran Sasso Science Institute (GSSI), L’Aquila, Italy, Oct. 2017.