https://bura.brunel.ac.uk/bitstream/2438/14221/1/FullText.pdf

A survey of deep neural network architectures and their applications

With the continuous increase in complexity and expense of industrial systems, there is less tolerance for performance degradation, productivity decrease, and safety hazards, which greatly necessitates to detect and identify any kinds of potential abnormalities and faults as early as possible and implement real-time fault-tolerant operation for minimizing performance degradation and avoiding dangerous situations. During the last four decades, fruitful results have been reported about fault diagnosis and fault-tolerant control methods and their applications in a variety of engineering systems. The three-part survey paper aims to give a comprehensive review of real-time fault diagnosis and fault-tolerant control, with particular attention on the results reported in the last decade. In this paper, fault diagnosis approaches and their applications are comprehensively reviewed from model- and signal-based perspectives, respectively.

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A Survey of Fault Diagnosis and Fault-Tolerant Techniques—Part I: Fault Diagnosis With Model-Based and Signal-Based Approaches

Fault detection, isolation, and reconfiguration (FDIR) is an important and challenging problem in many engineering applications and continues to be an active area of research in the control community. This paper presents a survey of the various model-based FDIR methods developed in the last decade. In the paper, the FDIR problem is divided into the fault detection and isolation (FDI) step, and the controller reconfiguration step. For FDI, we discuss various model-based techniques to generate residuals that are robust to noise, unknown disturbance, and model uncertainties, as well as various statistical techniques of testing the residuals for abrupt changes (or faults). We then discuss various techniques of implementing reconfigurable control strategy in response to faults.

A Survey of Fault Detection, Isolation, and Reconfiguration Methods

Brief paper: Smooth second-order sliding modes: Missile guidance application

In this paper, we mainly review the topics in consensus and coordination of multi-agent systems, which have received a tremendous surge of interest and progressed rapidly in the past few years. Focusing on different kinds of constraints on the controller and the self-dynamics of each individual agent, as well as the coordination schemes, we categorize the recent results into the following directions: consensus with constraints, event-based consensus, consensus over signed networks, and consensus of heterogeneous agents. We also review some applications of the very well developed consensus algorithms to the topics such as economic dispatch problem in smart grid and k -means clustering algorithms.

Recent Advances in Consensus of Multi-Agent Systems: A Brief Survey

Sliding-mode control is applied to design robust homing missile guidance law. The sufe cient and necessary condition for the sliding-mode motion of a linear time-varying system not to be affected by disturbances and the sufe cient condition for that motion not to be affected by parameter perturbations are given. An adaptive reaching law of sliding mode for a linear time-varying system is then presented and used to derive an adaptive sliding-mode guidance law. Theoretical analysis and simulation results show that the adaptive sliding-mode guidance law is robust against disturbances and parameter perturbations. Furthermore, the presented guidance law is simple to implement in practice.

Adaptive Sliding-Mode Guidance of a Homing Missile

https://bura.brunel.ac.uk/bitstream/2438/4054/1/Fulltext.pdf

Brief paper: Robust fault detection for networked systems with communication delay and data missing

In this note, an approach to the design of optimal fault detection systems for linear discrete-time periodic systems is proposed, which leads to an optimized compromise between robustness to unknown disturbances and sensitivity to faults. The needed computation mainly consists in solving a difference periodic Riccati system. The proposed approach is finally illustrated by a numerical example.

Fault detection of linear discrete-time periodic systems

In this technical note, the $H_{\infty}$ consensus control problem is investigated over a finite horizon for general discrete time-varying multi-agent systems subject to energy-bounded external disturbances. A decentralized estimation-based output feedback control protocol is put forward via the relative output measurements. A novel event-based mechanism is proposed for each intelligent agent to utilize the available information in order to decide when to broadcast messages and update control input. The aim of the problem addressed is to co-design the time-varying controller and estimator parameters such that the controlled multi-agent systems achieve consensus with a disturbance attenuation level $\gamma$ over a finite horizon $[0,T]$ . A constrained recursive Riccati difference equation approach is developed to derive the sufficient conditions under which the $H_{\infty}$ consensus performance is guaranteed in the framework of event-based scheme. Furthermore, the desired controller and estimator parameters can be iteratively computed by resorting to the Moore-Penrose pseudo inverse. Finally, the effectiveness of the developed event-based $H_{\infty}$ consensus control strategy is demonstrated in the numerical simulation.

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D.H. Zhou

Papers

Adaptive Sliding-Mode Guidance of a Homing Missile

Brief paper: Robust fault detection for networked systems with communication delay and data missing

Fault detection of linear discrete-time periodic systems

Event-Based $H_{\infty}$ Consensus Control of Multi-Agent Systems With Relative Output Feedback: The Finite-Horizon Case

Technical Communique: A frequency domain approach to fault detection in sampled-data systems