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Publications

Wireless networked control has attracted a lot of attention from both academia and industry in the past two decades, and has become a hot topic in recent years, mainly driven by mission-critical Industrial Internet of Things (IIoT) applications requiring closed-loop control, such as intelligent transportation, Tele-surgery, industry automation, power systems automation, and power electronics control. Specifically, a wireless networked control system (WNCS) is a spatially distributed control system consisting of networked sensors, actuators and a controller. The wireless sensors measure and report the physical process states of interest, the remote controller collects the sensors’ measurements and generates control signals, and the wireless actuators receive the control signals and control the processes. Due to its spatially distributed nature, reliable, dynamic and secure wireless communications among sensor, controller and actuator play an important role for WNCSs. Since communications and control are tightly coupled with each other, communications-control co-design is required in WNCSs to achieve optimal control performance, which introduces new design challenges for control-performance-centric communications, compared to the conventional rate-centric ones.

This collection of Best Readings focuses on performance analysis and communications-control co-design of WNCSs. The reading list includes three book titles, three tutorials, and four special issues that are all dedicated to the theory and practice of WNCSs, providing a holistic picture of the state of the art. The subsequent sections of the Best Reading focus on specific topics, including the foundations, wireless control over fading channels and multi-hop networks, resource allocation and medium-access control in WNCSs, wireless control with energy, computation and security constraints, and applying wireless standards in WNCSs.

Issued: April 2021

Contributors

Wanchun Liu, The University of Sydney, Australia
Daniel E. Quevedo, Queensland University of Technology, Australia
Yonghui Li, The University of Sydney, Australia
Vincent N.K. Lau, Hong Kong University of Science and Technology, Hong Kong

Pangun Park, Chungnam National University, Korea
Ling Shi, Hong Kong University of Science and Technology, Hong Kong
Petar Popovski, Aalborg University, Denmark

Editorial Staff

Matthew C. Valenti
Editor-in-Chief, ComSoc Best Readings
West Virginia University
Morgantown, WV, USA

Xianbin Wang
Associate Editor-in-Chief, ComSoc Best Readings
Western University
London, ON, Canada

Books

S. Yüksel and T. Basar, Stochastic Networked Control Systems: Stabilization and Optimization under Information Constraints, Springer Science & Business Media, 2013.
This book explains the fundamental theories on the stability and optimization of WNCS under imperfect wireless communications channels. The authors employ information-theoretic, control-theoretic and optimization tools to develop the results. This book aims to provide researchers a comprehensive, mathematically rigorous, but still accessible treatment of the interaction between communications and control of WNCSs.

A. S. Matveev and A. V. Savkin, Estimation and Control over Communication Networks, Springer Science & Business Media, 2009.
This book presents a systematic theory of estimation and control over communication networks. In particular, various problems of Kalman filtering, stabilization, and optimal control over communication channels are considered and solved. The results establish fundamental links among mathematical control theory, Shannon information theory, and entropy theory of dynamical systems.

D. Shi, L. Shi, and T. Chen, Event-based State Estimation: A Stochastic Perspective, Springer, 2016.
This book explores event-based remote estimation problems over wireless channels. It shows how several stochastic approaches are developed to maintain estimation performance when sensors perform their updates at slower rates only when needed. It is an indispensable reference for researchers and students who wish to expand their knowledge and work in the area of event-triggered systems. Engineers and practitioners in industrial process control will also benefit from the event-triggering technique that reduces communication costs and improves energy efficiency in wireless automation applications.

Overviews and Tutorials

P. Park, S. Coleri Ergen, C. Fischione, C. Lu, and K. H. Johansson, “Wireless Network Design for Control Systems: A Survey,” IEEE Communications Surveys & Tutorials, vol. 20, no. 2, pp. 978-1013, Second Quarter 2018.
This paper comprehensively surveys the recent progress of WNCSs, including wireless network design and optimization for WNCSs. Motivating examples, challenges and opportunities associated with implementing WNCSs are discussed.

C. Lu, A. Saifullah, B. Li, M. Sha, H. Gonzalez, D. Gunatilaka, C. Wu, L. Nie, and Y. Chen, “Real-time Wireless Sensor-Actuator Networks for Industrial Cyber-Physical Systems,” Proceedings of the IEEE, vol. 104, no. 5, pp. 1013–1024, May 2016.
This paper provides a survey of WNCSs in industry applications. It focuses on 1) real-time scheduling algorithms and analyses for WNCSs; 2) implementation and experimentation of industrial WNCS protocols; 3) cyber-physical co-design of wireless control systems that integrate wireless and control designs; and 4) a wireless cyber-physical simulator for co-design and evaluation of wireless control systems.

J. P. Hespanha, P. Naghshtabrizi, and Y. Xu, “A Survey of Recent Results in Networked Control Systems,” Proceedings of the IEEE, vol. 95, no. 1, pp. 138-162, January 2007.
This paper presents comprehensive results on estimation, analysis, and controller synthesis for NCSs. The survey addresses different aspects of the limitations imposed by communication, including data rate, sampling, network delay, and packet dropouts on NCSs. In particular, it covers a collection of results to determine the closed-loop stability of NCSs in the presence of the communication effects.

Special Issues

Design and Analysis of Communication Interfaces for Industry 4.0IEEE Journal on Selected Areas in Communications, vol. 38, no. 5, May 2020.

Secure Control of Cyber-Physical SystemsIEEE Transactions on Control of Network Systems, vol. 4, no. 1, March 2017.

Communication Technologies for Robotics and Autonomous SystemsIEEE Communications Magazine, vol. 59, no. 1, January 2021.

Special Issue on Control and CommunicationsIEEE Journal on Selected Areas in Communications, vol. 26, no. 4, May 2008.

Topic: Foundation of Wireless Networked Control Through Packet-Dropout, Data-Rate-Limited, and Gaussian Channels

L. Schenato, B. Sinopoli, M. Franceschetti, K. Poola, and S. S. Sastry, “Foundations of Control and Estimation Over Lossy Networks,” Proceedings of the IEEE, vol. 95, no. 1, pp. 163–187, January 2007.
This classical paper provides a detailed tutorial of optimal estimation and control design of WNCS over independent and identically distributed packet-dropout channels with TCP and UDP communication protocols. The stability conditions under different protocols in terms of packet drop probabilities are analyzed. The framework of optimization and stability analysis is presented in detail. A pendubot-based experiment is included to verify the theory.

L. Shi, M. Epstein, and R. M. Murray, “Kalman Filtering Over a Packet-Dropping Network: A Probabilistic Perspective,” IEEE Transactions on Automatic Control, vol. 55, no. 3, pp. 594-604, March 2010.
This paper is a well-cited paper, and it provides a complete characterization of the distribution of the estimation error covariance of the remote estimator for estimation over any packet-dropping networks.

G. N. Nair, F. Fagnani, S. Zampieri, and R. J. Evans, “Feedback Control Under Data Rate Constraints: An Overview,” Proceedings of the IEEE, vol. 95, no. 1, pp. 108-137, January 2007.
This classical paper presents a detailed tutorial of signal quantization and source coding design of WNCSs over error-free but data-rate-limited channels. A detailed analytical framework is provided for the stability conditions of WNCSs in terms of the available data rate.

J. H. Braslavsky, R. H. Middleton, and J. S. Freudenberg, “Feedback Stabilization Over Signal-to-Noise Ratio Constrained Channels,” IEEE Transactions on Automatic Control, vol. 52, no. 8, pp. 1391-1403, August 2007.
This pioneering paper introduces and investigates WNCSs over an analog additive white Gaussian noise channel. The stability condition in terms of the signal-to-noise is obtained.

S. Cai and V. K. N. Lau, “MSE Tail Analysis for Remote State Estimation of Linear Systems Over Multiantenna Random Access Channels,” IEEE Transactions on Automatic Control, vol. 65, no. 5, pp. 2046-2061, May 2020.
This is the first paper to consider a new performance metric, namely the MSE tail distribution, for remote state estimation over general wireless fading channels. The MSE tail distribution enables fine-grained analysis of the MSE sample path, which provides a stronger form of performance guarantee in remote state estimation systems compared with conventional average MSE metric. Closed-form sufficient conditions for “well-behaved” MSE Tail are derived under full rank and rank-deficient observation matrices.

N. W. Bauer, S. J. L. M. B. van Loon, N. van de Wouw, and W. P. M. H. M. Heemels, “Exploring the Boundaries of Robust Stability Under Uncertain Communication: An NCS Toolbox Applied to a Wireless Control Setup,” IEEE Control Systems Magazine, vol. 34, no. 4, pp. 65-86, August 2014.
The paper presents the analysis, design, and experimental validation of WNCSs. In particular, the NCS toolbox is provided for robust and stochastic stability analysis and controller design over wireless networks.

Topic: Latency, Data Rate, and Reliability Tradeoff in Wireless Networked Control

W. Liu, G. Nair, Y. Li, D. Nesic, B. Vucetic, and H. V. Poor, “On the Latency, Rate and Reliability Tradeoff in Wireless Networked Control Systems for IIoT,” IEEE Internet of Things Journal, vol. 8, no. 2, pp. 723-733, January 2021.
The paper considers a WNCS where a controller sends commands to an actuator through a digital additive white Gaussian noise channel. A detailed model of the wireless communication system is adopted, which jointly considers the inter-related communication parameters, including latency, data rate, and reliability. The fundamental necessary and sufficient stability conditions of the WNCS in terms of the communications parameters are derived.

K. Gatsis, H. Hassani, and G. J. Pappas, “Latency-Reliability Tradeoffs for State Estimation,” IEEE Transactions on Automatic Control, vol. 66, no. 3, pp. 1009-1023, March 2021.
The paper focuses on a remote state estimation system where a sensor sends measurements of a plant to a controller through a digital additive white Gaussian noise channel. The tradeoffs between transmission latency and reliability on the estimation performance are investigated. A cross-layer design methodology is proposed, i.e., select the code length depending on the plant dynamics to optimize estimation performance.

K. Huang, W. Liu, Y. Li, A. Savkin, and B. Vucetic, “Wireless Feedback Control With Variable Packet Length for Industrial IoT,” IEEE Wireless Communications Letters, vol. 9, no. 9, pp. 1586-1590, September 2020.
The paper proposes a novel WNCS where a controller sent commands to an actuator through a packet drop channel and can decide the transmission packet length in each time slot. A longer packet means a longer delay but better reliability. A decision-making problem is formulated and solved for finding the optimal variable-length packet-transmission policy for minimizing the long-term control performance of the WNCSs.

K. Huang, W. Liu, M. Shirvanimoghaddam, Y. Li, and B. Vucetic, “Real-Time Remote Estimation With Hybrid ARQ in Wireless Networked Control,” IEEE Transactions on Wireless Communications, vol. 19, no. 5, pp. 3490-3504, May 2020.
The paper considers a remote estimation system via a packet drop channel, where the sensor-to-controller transmission adopts a hybrid automatic repeat request (HARQ)-based retransmission scheme. There is a fundamental tradeoff between the reliability and latency of the sensor’s measurement transmission, as a retransmission leads to a longer latency but better reliability. A novel problem for optimizing the sensor’s online transmission policy: to retransmit or not, was proposed and solved, so as to minimize the long-term remote estimation mean squared error.

M. Pezzutto, F. Tramarin, S. Dey, and L. Schenato, “Adaptive Transmission Rate for LQG Control over Wi-Fi: A Cross-Layer Approach,” Automatica, Volume 119, pp. 1-12, 2020.
This work focuses on a WNCS where the link between the sensor and the controller relied on a Wi-Fi network. The tradeoff between the transmission bit rate and the reliability on the control performance is investigated.

Topic: Wireless Networked Control over Fading Channels

D. E. Quevedo, J. Østergaard, and A. Ahlén, “Power Control and Coding Formulation for State Estimation With Wireless Sensors,” IEEE Transactions on Control Systems Technology, vol. 22, no. 2, pp. 413-427, March 2014.
The paper considers power control and coding method of a multi-sensor remote estimation system over wireless correlated channels. Numerical results show that the proposed method can lead to energy savings of around 50%.

P. Minero, L. Coviello, and M. Franceschetti, “Stabilization Over Markov Feedback Channels: The General Case,” IEEE Transactions on Automatic Control, vol. 58, no. 2, pp. 349-362, February 2013.
The paper investigates the mean-square stabilization of a discrete-time linear dynamical system over an error-free time-varying digital feedback channel, where the data rate was modeled as a Markov chain. A necessary-and-sufficient stability condition and a necessary stability condition are derived for the scalar and vector cases, respectively.

D. E. Quevedo, A. Ahlen, and K. H. Johansson, “State Estimation Over Sensor Networks with Correlated Wireless Fading Channels,” IEEE Transactions on Automatic Control, vol. 58, no. 3, pp. 581-593, March 2013.
The paper focuses on a multi-hop remote estimation network over packet dropout channels, where the packet error probability of each channel was modeled as a time-varying multi-state Markov chain. Sufficient stability conditions for exponential stability are derived.

K. You, M. Fu, and L. Xie, “Mean Square Stability for Kalman Filtering with Markovian packet losses,” Automatica, vol. 47, no. 12, pp. 2647-2657, 2011.
The paper investigates a remote estimation problem over a packet dropout channel, where the transmission success/failure is modeled as an on-off Markov chain. Some necessary and sufficient conditions for mean-square stability are derived.

Topic: Wireless Networked Control Through Multi-hop Networks

R. Alur, A. D’Innocenzo, K. H. Johansson, G. J. Pappas, and G. Weiss, “Compositional Modeling and Analysis of Multi-Hop Control Networks,” IEEE Transactions on Automatic Control, vol. 56, no. 10, pp. 2345-2357, October 2011.
The paper proposes a WNCS, where multiples plants are controlled by multiple controllers via a multi-hop wireless network. A graph-theory-based method to model the wireless control loops and an analytical framework are established for analyzing robustness of the error-prone multi-hop WNCS.

Z. Ren, P. Cheng, L. Shi, and Y. Dai, “State Estimation Over Delayed Mutihop Network,” IEEE Transactions on Automatic Control, vol. 63, no. 10, pp. 3545-3550, October 2018.
The paper investigates a sensor-controller remote state estimation system via a multi-hop relay network. The transmission delay in each hop is modeled as a Markov chain. The lower and upper bounds of the remote estimation covariance are obtained, based on which some necessary and sufficient stability conditions of the remote estimation system in terms of the statistics of the delay are derived.

A. S. Leong and D. E. Quevedo, “Kalman Filtering with Relays Over Wireless Fading Channels,” IEEE Transactions on Automatic Control, vol. 61, no. 6, pp. 1643-1648, June 2016.
The paper investigates a multi-sensor-single-controller remote estimation system via a multi-relay network. Each relay can either forward one of the sensors’ measurements to the controller, or perform a simple linear network coding operation on some of the sensor measurements. Optimal and suboptimal methods are obtained for finding the best relay configuration and transmission power control for optimizing the remote estimation performance.

Topic: Resource Allocation and Medium-Access Control in WNCSs

K. Gatsis, M. Pajic, A. Ribeiro, and G. J. Pappas, “Opportunistic Control Over Shared Wireless Channels,” IEEE Transactions on Automatic Control, vol. 60, no. 12, pp. 3140-3155, December 2015.
The pioneering paper focuses on a WNCS with multiple control loops over a shared wireless medium. A scheduler observes the random channel conditions that each control system experienced over the shared medium and opportunistically selects systems to transmit at a set of non-overlapping frequencies. The transmit power of each system also adapts to channel conditions, which determines the probability of successfully receiving and closing the loop. An offline algorithm to find the optimal transmission scheduling and power control protocol for achieving the best overall control performance is developed, as well as an online algorithm.

K. Gatsis, A. Ribeiro, and G. J. Pappas, “Random Access Design for Wireless Control Systems,” Automatica, Volume 91, pp. 1-9, 2018.
The paper investigates a WNCS with multiple control loops over a shared wireless medium, without the presence of a scheduler. Random access policies are developed where the total transmit power of the sensors is minimized while desired control performance is guaranteed for each involved control loop. It is proved that the optimal channel access policies can be decoupled, and the optimal policies are of a threshold nature with respect to channel conditions.

S. Wu, X. Ren, S. Dey, and L. Shi, “Optimal Scheduling of Multiple Sensors Over Shared Channels with Packet Transmission Constraint,” Automatica, Volume 96, pp. 22-31, 2018.
The paper considers a multi-sensor-single-controller remote state estimation system over a shared wireless medium. An optimal transmission scheduling policy for minimizing the overall average estimation error is obtained as a solution of a Markov decision process problem, allocating a subset of the sensors to the available frequency channels. Some structural results about the optimal policy are derived.

A. S. Leong, A. Ramaswamy, D. E. Quevedo, H. Karl, and L. Shi, “Deep Reinforcement Learning for Wireless Sensor Scheduling in Cyber-Physical Systems,” Automatica, Volume 113, pp. 1-8, 2020.

The paper investigates a many-sensor-single-controller remote state estimation system over a shared wireless medium. The optimal scheduling policy is first formulated as a Markov decision process (MDP), and then solved using a Deep Q-Network, a recent deep reinforcement learning algorithm that is at once scalable and model-free.

S. Cai and V. K. N. Lau, “Modulation-Free M2M Communications for Mission-Critical Applications,” IEEE Transactions on Signal and Information Processing over Networks, vol. 4, no. 2, pp. 248-263, June 2018.
The paper studies a WNCS with multiple distributed wireless sensors sending measurement data of an unstable dynamic plant to a remote controller. A novel coding-free transmission scheme is proposed, which utilizes collision to enhance the system performance. A sufficient stability condition of the WNCS in terms of communication resources is derived.

W. Liu, P. Popovski, Y. Li, and B. Vucetic, “Wireless Networked Control Systems With Coding-Free Data Transmission for Industrial IoT,” IEEE Internet of Things Journal, vol. 7, no. 3, pp. 1788-1801, March 2020.
The paper considers a WNCS, where a controller remotely controls multiple unstable dynamic plants. A novel coding-free control method is proposed to achieve ultra-low latency communications in single-controller-multi-plant WNCS for both slow- and fast-fading channels. A power allocation problem to optimize the overall control performance is formulated and solved, subject to the plant stabilization conditions and the controller’s power limit.

A. S. Leong, S. Dey, and D. E. Quevedo, “Transmission Scheduling for Remote State Estimation and Control with an Energy Harvesting Sensor,” Automatica, Volume 91, pp. 54-60, 2018.
The paper proposes a remote state estimation problem where a sensor, equipped with energy harvesting capabilities, observes a dynamical process and transmits local state estimates over a packet dropping channel to a remote estimator. An optimal transmission policy is obtained for achieving the minimum estimation error, subject to constraints on the sensor’s battery energy governed by an energy harvesting process.

Topic: Wireless Control with Communications and Energy Constraints: Event-Triggered Control

J. Wu, Q. Jia, K. H. Johansson, and L. Shi, “Event-Based Sensor Data Scheduling: Trade-Off Between Communication Rate and Estimation Quality,” IEEE Transactions on Automatic Control, vol. 58, no. 4, pp. 1041-1046, April 2013.
The paper investigates sensor data scheduling for remote state estimation. Due to constrained communication energy and bandwidth, a sensor needs to decide whether it should send the current measurement to a remote estimator or not. An event-based sensor data scheduler is proposed, and the corresponding minimum squared error estimator is derived. By selecting an appropriate event-triggering threshold, it is illustrated how to achieve a desired balance between the sensor-to-estimator communication rate and the estimation quality.

D. Han, Y. Mo, J. Wu, S. Weerakkody, B. Sinopoli, and L. Shi, “Stochastic Event-Triggered Sensor Schedule for Remote State Estimation,” IEEE Transactions on Automatic Control, vol. 60, no. 10, pp. 2661-2675, October 2015.
This paper is an important reference in event-based state estimation which proposed a stochastic event-triggered under which the Gaussianity of the innovation process is preserved turning a difficult nonlinear filtering problem into a linear one.

A. S. Leong, S. Dey, and D. E. Quevedo, “Sensor Scheduling in Variance Based Event Triggered Estimation with Packet Drops,” IEEE Transactions on Automatic Control, vol. 62, no. 4, pp. 1880-1895, April 2017.
The paper investigates a multi-sensor-single-controller remote state estimation problem, where sensors transmit local state estimates over a shared packet dropping channel to the controller. At every discrete time instant, the remote estimator decides whether each sensor should transmit or not, with each sensor transmission incurring a fixed energy cost. An optimization problem is formulated and solved that minimizes a convex combination of the expected estimation error covariance at the remote estimator and expected energy usage across the sensors.

K. Huang, W. Liu, Y. Li, B. Vucetic, and A. Savkin, “Optimal Downlink–Uplink Scheduling of Wireless Networked Control for Industrial IoT,” IEEE Internet of Things Journal, vol. 7, no. 3, pp. 1756-1772, March 2020.
The pioneering paper considers a WNCS with a half-duplex controller, which introduces a novel decision-making problem: when to receive the sensor’s measurement and when to send a control command to the actuator. The necessary and sufficient condition of the existence of a stationary and deterministic optimal policy is derived in closed form. The transmission-scheduling policy for optimizing the long-term average control performance is obtained.

V. K. N. Lau, S. Cai, and M. Yu, “Decentralized State-Driven Multiple Access and Information Fusion of Mission-Critical IoT Sensors for 5G Wireless Networks,” IEEE Journal on Selected Areas in Communications, vol. 38, no. 5, pp. 869-884, May 2020.
This paper studies decentralized dynamic scheduling of mission-critical IoT sensors over general fading channels based on Lypaunov optimization where the active sensor(s) is adaptive to both the instantaneous local state estimation covariance and the instantaneous local channel fading at the sensor. Closed-form sufficient conditions for the estimation stability under the dynamic scheduling are also derived.

Topic: Wireless Control with Delay Constraints: Model-Predictive Control

V. Gupta, B. Sinopoli, S. Adlakha, A. Goldsmith, and R. Murray, “Receding Horizon Networked Control,” in Proc., Allerton Conference on Communications, Control, and Computing, Monticello, Illinois, September 2006.
The pioneering paper proposes a novel model predictive control method to compensate for the transmission delay between a controller and an actuator. The controller sends a sequence of control commands to the actuator in each packet. These commands are stored in a buffer and applied sequentially until the next control packet arrives. The stability condition of the WNCS with the model predictive method is derived.

B. Demirel, V. Gupta, D. E. Quevedo, and M. Johansson, “On the Trade-Off Between Communication and Control Cost in Event-Triggered Dead-Beat Control,” IEEE Transactions on Automatic Control, vol. 62, no. 6, pp. 2973-2980, June 2017.
The paper considers a WNCS where the communication between the controller and the actuator is triggered by a threshold-based rule over a packet drop channel. The WNCS adopts a dead-beat-control-based predictive control method. The control performance of the WNCS is analyzed for any given event-threshold, quantifying the trade-off between the communication cost and the control performance of event-triggered control systems.

P. Mishra, D. Chatterjee, and D. E. Quevedo, “Stochastic Predictive Control Under Intermittent Observations and Unreliable Actions,” Automatica, vol. 118, pp. 1-14, August 2020.
The paper investigates a WNCS, where a smart sensor equipped with a Kalman filter is employed for the estimation of the states from incomplete and corrupt measurements, and an estimator at the controller side optimally feeds the intermittently received sensor data to the controller. The remote controller iteratively solves constrained stochastic optimal control problems and transmits the control commands according to a carefully designed transmission protocol through an unreliable channel.

E. G. W. Peters, D. E. Quevedo, and J. Østergaard, “Shaped Gaussian Dictionaries for Quantized Networked Control Systems with Correlated Dropouts,” IEEE Transactions on Signal Processing, vol. 64, no. 1, pp. 203-213, January 2016.
The paper focuses on a WNCS where a controller sends quantized control signals to an actuator over an error-prone digital channel. The controller adopts packetized predictive control to reduce the impact of packet losses. An efficient fixed-rate vector quantizer is proposed.

Topic: Wireless Control with Computation Constraints: Anytime Control

V. Gupta and F. Luo, “On a Control Algorithm for Time-Varying Processor Availability,” IEEE Transactions on Automatic Control, vol. 58, no. 3, pp. 743-748, March 2013.
The paper proposes an anytime control algorithm for a multi-input linear system for the scenario that the computation availability for control command is unknown a priori. The main idea is to first calculate the most important component of the control vector and then calculate the less important ones as more computation resource time becomes available.

D. E. Quevedo, V. Gupta, W. Ma, and S. Yüksel, “Stochastic Stability of Event-Triggered Anytime Control,” IEEE Transactions on Automatic Control, vol. 59, no. 12, pp. 3373-3379, December 2014.
The paper studies a WNCS where the controller has time-varying computation resource, and sensor-controller transmission has packet dropouts. To make efficient use of communication and processing resources, the sensor transmits only when the plant state lies outside a bounded target set. Sufficient conditions on system parameters for stochastic stability of the WNCS is derived.

W.-J. Ma, V. Gupta, and D. E. Quevedo, “Collaborative Processing in Distributed Control for Resource Constrained Systems,” IET Control Theory & Applications, vol. 11, no. 11, pp. 1796–1806, November 2017.
The paper considers a distributed multi-controller-multi-plant WNCS, where each controller had limited and time-varying computation resources. A novel controller collaborative algorithm is proposed to ensure the stochastic stability of the entire system.

Topic: Communications-Control Codesign in WNCSs

P. Park, J. Araújo, and K. H. Johansson, “Wireless Networked Control System Co-Design,” in Proc., IEEE International Conference on Networking, Sensing and Control (ICNSC), Delft, Netherlands, April 2011.
The paper proposes a framework for the joint design of wireless network and controllers. The co-design approach is based on a constrained optimization problem, for which the objective function is the energy consumption of the network and the constraints are the packet loss probability and delay.

D. Antunes and W. P. M. H. Heemels, “Rollout Event-Triggered Control: Beyond Periodic Control Performance,” IEEE Transactions on Automatic Control, vol. 59, no. 12, pp. 3296-3311, December 2014.
The paper investigates sensor and controller transmission scheduling over a shared wireless network. Rollout strategies are proposed to jointly design the transmission scheduling and the control policy.

M. Eisen, M. M. Rashid, K. Gatsis, D. Cavalcanti, N. Himayat, and A. Ribeiro, “Control Aware Radio Resource Allocation in Low Latency Wireless Control Systems,” IEEE Internet of Things Journal, vol. 6, no. 5, pp. 7878-7890, October 2019.
The paper proposes a novel control-aware communication design of a multi-control-loop WNCS over shared wireless resources. The method incorporates both control and channel state information in scheduling transmissions across time slots, frequency bands, and data rates using the next-generation Wi-Fi scheduling architecture. Control loops that are closer to instability or further from a desired range in a given control cycle are given higher packet delivery rate targets to meet.

Topic: Wireless Security in WNCSs

M. S. Chong, H. Sandberg, and A. M. H. Teixeira, “A Tutorial Introduction to Security and Privacy for Cyber-Physical Systems,” in Proc., European Control Conference (ECC), Naples, Italy, June 2019.
This paper provides a high-level introduction to control-theoretic approaches for the security and privacy of cyber-physical systems (CPS). It takes a risk-based approach to the problem and develops a model framework for the design of secure and resilient CPS.

Y. Li, L. Shi, P. Cheng, J. Chen, and D. E. Quevedo, “Jamming Attacks on Remote State Estimation in Cyber-Physical Systems: A Game-Theoretic Approach,” IEEE Transactions on Automatic Control, vol. 60, no. 10, pp. 2831-2836, October 2015.
The paper focuses on a remote estimation system, where the sensor to controller transmission can be jammed by a malicious attacker. With energy constraints for both the sensor and the attacker, the interactive decision-making process of when to send and when to attack is investigated as a game-theoretic problem.

Y. Li, D. E. Quevedo, S. Dey, and L. Shi, “A Game-Theoretic Approach to Fake-Acknowledgment Attack on Cyber-Physical Systems,” IEEE Transactions on Signal and Information Processing over Networks, vol. 3, no. 1, pp. 1-11, March 2017.
The paper considers a remote estimation system, where a sensor adopts an acknowledgement (ACK)-based online power schedule to improve the remote state estimation performance under limited resources. A malicious attacker can modify the ACKs from the remote estimator and convey fake information to the sensor. To investigate the optimal strategies for both the sensor (to trust an ACK or not) and the attacker (to attack or not), a game-theoretic framework is built and the equilibrium for both sides is investigated.

H. Zhang, P. Cheng, L. Shi, and J. Chen, “Optimal DoS Attack Scheduling in Wireless Networked Control System,” IEEE Transactions on Control Systems Technology, vol. 24, no. 3, pp. 843-852, May 2016.
The paper studies a WNCS system under the presence of a malicious attacker. The optimal attacking policy under an energy constraint is investigated to achieve the highest cost function of the WNCS.

A. S. Leong, D. E. Quevedo, D. Dolz, and S. Dey, “Information Bounds for State Estimation in the Presence of an Eavesdropper,” IEEE Control Systems Letters, vol. 3, no. 3, pp. 547-552, July 2019.
This paper investigates transmission scheduling for remote state estimation in the presence of an eavesdropper. It is shown that with unstable systems, any transmission policy which keeps the expected estimation error covariance bounded must always reveal a non-zero expected amount of information to the eavesdropper.

A. Tsiamis, K. Gatsis, and G. J. Pappas, “State-Secrecy Codes for Networked Linear Systems,” IEEE Transactions on Automatic Control, vol. 65, no. 5, pp. 2001-2015, May 2020.
The paper considers a remote state estimation system in the presence of a passive eavesdropper. An authorized user estimates the state of an unstable linear plant, based on the packets received from a sensor, while the packets may also be intercepted by the eavesdropper. A novel coding scheme at the sensor is proposed, which encoded the state information, in order to impair the eavesdropper’s estimation performance while enabling the user to successfully decode the sent messages.

Z. Guo, D. Shi, K. H. Johansson, and L. Shi, “Optimal Linear Cyber-Attack on Remote State Estimation,” IEEE Transactions on Control of Network Systems, vol. 4, no. 1, pp. 4-13, March 2017.
This paper proposes a novel linear data integrity attack in remote state estimation. It studies the worst possible attack and its consequence on the system performance, suggesting how one can protect the system by building more intelligent bad data detectors.

Y. Li, D. E. Quevedo, S. Dey, and L. Shi, “SINR-Based DoS Attack on Remote State Estimation: A Game-Theoretic Approach,” IEEE Transactions on Control of Network Systems, vol. 4, no. 3, pp. 632-642, September 2017.
This paper investigates remote estimation under DoS attack and formulates the problem as a Markov power control game between the system designer and the adversary. It further offers a Nash Q-learning algorithm for reaching a Nash equilibrium.

Topic: Applying Wireless Standards in WNCSs

C. Peng, D. Yue, and M. Fei, “A Higher Energy-Efficient Sampling Scheme for Networked Control Systems over IEEE 802.15.4 Wireless Networks,” IEEE Transactions on Industrial Informatics, vol. 12, no. 5, pp. 1766-1774, October 2016.
This paper proposes a higher energy-efficient mixed sampling scheme for a WNCS over IEEE 802.15.4 wireless networks. The proposed scheme can improve the energy efficiency of the WNCS by reducing the number of transmitted packets and increasing the idle-listening period of wireless sensor nodes.

E. G. W. Peters, D. E. Quevedo, and M. Fu, “Controller and Scheduler Codesign for Feedback Control Over IEEE 802.15.4 Networks,” IEEE Transactions on Control Systems Technology, vol. 24, no. 6, pp. 2016-2030, November 2016.
The paper investigates the possibilities and limitations of feedback control in the IEEE 802.15.4 specification and states the problem of scheduling when the controller utilizes both the contention-based and guaranteed parts of the protocol. Some scheduler-controller co-design algorithms are proposed and compared that take both the contention-based and guaranteed parts of the protocol into account.

A. I. Maass and D. Nešić, “Stabilization of Non-Linear Networked Control Systems Closed over a Lossy WirelessHART Network,” IEEE Control Systems Letters, vol. 3, no. 4, pp. 996-1001, October 2019.
The paper studies the stabilization of a WNCS where the information between plant and controller is sent over a lossy wireless multi-hop network adopting a WirelessHART protocol. A sufficient stability condition in terms of the intensity of transmission is derived.

G. Tian, S. Camtepe, and Y. Tian, “A Deadline-Constrained 802.11 MAC Protocol With QoS Differentiation for Soft Real-Time Control,” IEEE Transactions on Industrial Informatics, vol. 12, no. 2, pp. 544-554, April 2016.
The paper proposes a deadline-constrained medium access control protocol with quality of service (QoS) differentiation for IEEE 802.11 soft real-time WNCSs. The protocol handles periodic traffic by developing two specific mechanisms, a contention-sensitive backoff mechanism and an intra-traffic-class QoS differentiation mechanism.