Outlier-Resistant Observer-Based Control for a Class of Networked Systems Under Encoding–Decoding Mechanism

National Natural Science Foundation of China; Natural Science Foundation of Heilongjiang Province of China; Key Laboratory of Advanced Perception and Intelligent Control of High-end Equipment of Ministry of Education in Anhui Polytechnic University of China; Alexander von Humboldt Foundation of Germany

Proportional-Integral Observer Design for Uncertain Time-Delay Systems Subject to Deception Attacks: An Outlier-Resistant Approach

National Natural Science Foundation of China (Grant Number: 61873148, 61873169, 61933007 and 62103281); Royal Society of the U.K.; Alexander von Humboldt Foundation of Germany

Ultimately Bounded Filtering Subject to Impulsive Measurement Outliers

This paper is concerned with the ultimately bounded filtering problem for linear time-delay systems subject to norm-bounded disturbances and impulsive measurement outliers (IMOs). The considered IMOs are modeled by a sequence of impulsive signals with certain known minimum norm (i.e. the minimum of the norms of all impulsive signals). In order to characterize the occasional occurrence of IMOs, a sequence of independently and identically distributed random variables is introduced to depict the interval lengths (i.e. the durations between two adjacent IMOs) of the outliers. In order to achieve satisfactory filtering performance, a novel parameter-dependent filtering approach is proposed to protect the filtering performance from IMOs by using a special outlier detection scheme, which is developed based on a particular input-output model. The ultimate boundedness (in mean square) of the filtering error is investigated by using the stochastic analysis technique and Lyapunov-functional-like method. The desired filter gain matrix is derived through solving a constrained optimization problem. A simulation example is provided to demonstrate the effectiveness of our propose

Outlier-Resistant Remote State Estimation for Recurrent Neural Networks with Mixed Time-Delays

10.13039/501100001809-National Natural Science Foundation of China (Grant Number: 61933007, 61873148 and 61873058); 10.13039/501100005046-Natural Science Foundation of Heilongjiang Province of China (Grant Number: ZD2019F001); Key Laboratory of Advanced Perception and Intelligent Control of High-End Equipment of Ministry of Education in Anhui Polytechnic University of China (Grant Number: GDSC202016); 10.13039/100005156-Alexander von Humboldt Foundation of Germany

Communication-protocol-based analysis and synthesis of networked systems: progress, prospects and challenges

In recent years, the communication-protocol-based synthesis and analysis issues have gained substantial research interest owing mainly to their significance in networked systems. In this work, we survey the control and filtering problems of networked systems under the effects induced by communication protocols. First, we introduce the engineering background of networked systems as well as the theoretical frameworks established to deal with the communication-protocol-based analysis and synthesis problems. Then, recent advances (especially the latest results) are reviewed on the stability analysis issue subject to protocol scheduling. Subsequently, the particular effort is devoted to presenting the latest progress on various communication-protocol-based control and filtering problems according to the characteristics of networked systems (e.g. time-varying nature, random behaviours, types of parameter uncertainties, and kinds of distributed structure). After that, we provide a systematic review of the communication-protocol-based fault diagnosis problems. Finally, some research challenges of communication-protocol-based control and filtering problems are outlined for future research

Multi-sensor multi-rate fusion estimation for networked systems: Advances and perspectives

National Natural Science Foundation of China under Grants 62103095, 61873058, 61873148 and 61933007; AHPU Youth Top-notch Talent Support Program of China under Grant 2018BJRC009; Natural Science Foundation of Anhui Province of China under Grant 2108085MA07; Royal Society of the UK; Alexander von Humboldt Foundation of Germany

Recursive Set-Membership State Estimation Over a FlexRay Network

10.13039/501100001809-National Natural Science Foundation of China (Grant Number: 61873148, 61873169, 61903253 and 61933007); Royal Society of the U.K.; Alexander von Humboldt Foundation of Germany

Recursive Bayesian Estimation for Discrete-Time Systems With State-Dependent Packet Dropouts: A Cross-Coupled Method

National Key Research and Development Program of China (Grant Number: 2022YFB4501700); National Science Foundation of China (Grant Number: 62222312, U21A2019 and 61933007); Hainan Province Science and Technology Special Fund of China (Grant Number: ZDYF2022SHFZ105); Fundamental Research Funds for the Central Universities

Cluster Synchronization Control for Discrete-Time Complex Dynamical Networks: When Data Transmission Meets Constrained Bit Rate

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Service Boosters: Library Operating Systems For The Datacenter

Cloud applications are taking an increasingly important place our technology and economic landscape. Consequently, they are subject to stringent performance requirements. High tail latency — percentiles at the tail of the response time distribution — is a threat to these requirements. As little as 0.01% slow requests in one microservice can significantly degrade performance for the entire application. The conventional wisdom is that application-awareness is crucial to design optimized performance management systems, but comes at the cost of maneuverability. Consequently, existing execution environments are often general-purpose and ignore important application features such as the architecture of request processing pipelines or the type of requests being served. These one-size-fits-all solutions are missing crucial information to identify and remove sources of high tail latency. This thesis aims to develop a lightweight execution environment exploiting application semantics to optimize tail performance for cloud services. This system, dubbed Service Boosters, is a library operating system exposing application structure and semantics to the underlying resource management stack. Using Service Boosters, programmers use a generic programming model to build, declare and an-notate their request processing pipeline, while performance engineers can program advanced management strategies. Using Service Boosters, I present three systems, FineLame, Perséphone, and DeDoS, that exploit application awareness to provide real time anomaly detection; tail-tolerant RPC scheduling; and resource harvesting. FineLame leverages awareness of the request processing pipeline to deploy monitoring and anomaly detection probes. Using these, FineLame can detect abnormal requests in-flight whenever they depart from the expected behavior and alerts other resource management modules. Pers ́ephone exploits an understanding of request types to dynamically allocate resources to each type and forbid pathological head-of-line blocking from heavy-tailed workloads, without the need for interrupts. Pers ́ephone is a low overhead solution well suited for microsecond scale workloads. Finally, DeDoS can identify overloaded components and dynamically scale them, harvesting only the resources needed to quench the overload. Service Boosters is a powerful framework to handle tail latency in the datacenter. Service Boosters clearly separates the roles of application development and performance engineering, proposing a general purpose application programming model while enabling the development of specialized resource management modules such as Perséphone and DeDoS