Resilient estimation and control for distributed dynamic systems

  • Xiaoyu Guo

Student thesis: Phd


Increasing research attention has been placed towards distributed dynamic systems that integrate sensing, computation, communication and physical processes. A prominent feature of such systems is communication among subsystems via network mediums, and distributed estimation and control schemes can enable distributed dynamic systems to carry out complicated tasks in a cooperative manner. Utilization of networks and exposure to the physical environment means that distributed systems are more vulnerable to adversaries that include attacks, faults, and disturbances. In practical distributed systems, a wide range of adversaries exist in various forms (such as deception attack and denial-of-service attack) that affect various channels (such as the sensor channel, communication channel and actuator channel). This thesis focuses on the important topic of developing resilient estimation and control schemes for distributed dynamic systems to improve the safety and performance in the presence of adversaries. Firstly, the simultaneous presence of disturbances and attacks on distributed systems is tackled by a novel three-stage estimation approach which includes anti-disturbance estimation, optimal attack detection and detection-triggered attack-resilient estimation. This approach effectively decouples the influence of multiple disturbances and false data injection attacks existing on the same channel. In some cases, heterogeneous attacks on different channels can be simultaneously injected to have a joint effect on distributed systems. Utilizing a novel event-based update scheme, an adaptive term and a distributed disturbance observer, an event-based distributed estimation approach is introduced to deal with the joint effects of aperiodic denial-of-service attacks on the communication channel and unknown deception attacks on the sensor channel. While the previous works deal with disturbances and attacks through compensation and attenuation, some attacks, namely the sparse injection attacks on sensors are potentially unbounded and cannot be dealt with the observer-based compensation approach. In such cases, it is more desirable to isolate and remove the sensor channels that are under attack. In the third section, a switching sparse attack detector based on a monitoring function utilizes the sensing redundancy to identify and remove the attacked sensor channels, and a backstepping control scheme is designed for the practical implementation of the proposed algorithm on a robotic manipulator. In the final section, adversaries on the actuator channel are studied, where the challenging topic of unknown direction faults on multi-input-multi-output distributed systems is dealt with novel Nussbaum functions, and a distributed containment control scheme is proposed for a network of uncertain nonlinear agents. Moreover, an event-triggering mechanism is introduced to avoid continuous communication among agents. The main contribution of this thesis is presenting a framework for the resilient estimation and control of distributed network systems against a wide range of adversaries, including but not limited to injection attacks, denial of service attacks, actuator faults and disturbances. The approaches introduced in each chapter of this thesis have compelling features that can be either implemented on their own, or integrated with other existing control and estimation schemes to enhance the resilience of distributed systems.
Date of Award1 Aug 2023
Original languageEnglish
Awarding Institution
  • The University of Manchester
SupervisorZhirun Hu (Supervisor) & Zhengtao Ding (Supervisor)

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