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This article is concerned with the resilient fault diagnosis (FD) problem for a class of complex networks subject to possible loss of the actuator effectiveness and random variation of the filter gain. An unknown diagonal matrix is employed to characterize the multiplicative loss of actuator effectiveness for each node. The proposed filter utilizes the information from only the local node and the neighboring nodes. Since there is no need to have a center node receiving global information from every node, the developed FD algorithm is truly distributed. In the presence of gain variations, a time-varying filter is constructed to jointly estimate the system state and the loss of actuator effectiveness at each node. An upper bound of the filtering error covariance is calculated and then minimized via appropriately determining the filter gains. The filter is designed by solving two sets of recursive matrix equations, thereby meriting the suitability of online applications. Sufficient conditions are established to guarantee the exponential boundedness in mean square of the filtering error, and the monotonicity of the estimation error covariance with respect to the coupling strength is also investigated. An illustrative example is provided to show the usefulness of our FD strategy. [ABSTRACT FROM AUTHOR]

In this article, a new event-triggered Hi/H∞ optimization fault detection (FD) scheme is proposed for linear discrete time systems. A linear discrete time system with varying sampling periods is first presented to describe the dynamics of an event-triggered system. Based on this, an observer-based fault detection filter (FDF) is constructed as an event-triggered residual generator so that the generated residual signal is completely decoupled from the event-triggered transmission error. The design of event-triggered FDF is formulated as a multiobjective optimization problem denoted by Hi/H∞ and an optimal solution can be obtained by recursive calculation of Riccati equations. In addition, an event-triggered residual evaluation strategy is also presented. Comparing with the existing event-triggered FD schemes, the major contribution of this article is to decouple the residual signals from the event-triggered transmission errors completely and, consequently, the FD performance can be improved significantly. Moreover, an optimal tradeoff between the robustness of residual to unknown input and the sensitivity of residual to fault is achieved in the sense of Hi/H∞ optimization, while the design of FDF and event generator can be carried out independently. To demonstrate the effectiveness of the proposed method, a vehicle lateral dynamic system is used as a simulation example. [ABSTRACT FROM AUTHOR]

In this note, a new scheme of fault detection (FD) is proposed for linear discrete time-varying (LDTV) systems subject to l2-norm bounded unknown inputs. The basic idea is to find an optimal estimation of the l2-norm of the unknown inputs including the unknown initial state variables. This leads to a natural design of the FD system with the l2-norm boundedness of the unknown inputs as a threshold and the l2-norm of the unknown input estimate as the evaluation function. To avoid heavy computational burden, projection technique in Krein space is applied which allows a recursive computation of the evaluation function. It is shown that the achieved FD system satisfies both the worst case and best case sensitivity/robustness ratio criteria and further applications to observer-based FD lead to an alternative design of H\infty/H\infty and/or H-/H\infty fault detection filter. [ABSTRACT FROM PUBLISHER]

In this article, the diagnosability problem is investigated for open-loop and closed-loop stochastic systems under sensor and actuator faults. A novel quantitative fault diagnosability analysis method is developed to characterize the detectability and isolability for a given system without any predetermined fault diagnosis algorithm. By exploiting the Bhattacharyya distance, some novel indices are proposed to evaluate the difficulty degree of fault detectability and isolability. Necessary and sufficient conditions are established for the diagnosability of both open- and closed-loop stochastic systems undergoing sensor and actuator faults. In addition, the relationship between the fault detectability of open-loop systems and that of closed-loop ones is discussed. [ABSTRACT FROM AUTHOR]

This article is concerned with the moving horizon estimation (MHE) problem for networked linear systems (NLSs) with unknown inputs under dynamic quantization effects. For the NLSs with unknown input signals, the conventional MHE strategy is incapable of guaranteeing the satisfactory performance as the estimation error is dependent on the external disturbances. In this work, a novel MHE strategy is developed to cope with the underlying NLS with unknown inputs by dedicatedly introducing certain temporary estimates of unknown inputs, where the desired estimator parameters are designed to decouple the estimation error dynamics from the unknown inputs. A two-step design strategy (namely, decoupling step and convergence step) is proposed to obtain the estimator parameters. In the decoupling step, the decoupling parameter of the moving horizon estimator is designed based on certain assumptions on system parameters and quantization parameters. In the convergence step, by employing a special observability decomposition scheme, the convergence parameters of the moving horizon estimator are achieved such that the estimation error dynamics is ultimately bounded. Moreover, the developed MHE strategy is extended to the scenario with direct feedthrough of unknown inputs. Two simulation examples are given to demonstrate the correctness and effectiveness of the proposed MHE strategies. [ABSTRACT FROM AUTHOR]

This paper is concerned with the moving horizon estimation problem for a class of discrete time-delay systems under the Round-Robin (RR) protocol. The communication between the sensor nodes and the remote state estimator is implemented via a shared network, where only one sensor node is permitted to transmit data at each time instant for the purpose of preventing data collisions. The RR protocol is utilized to orchestrate the transmission order of sensor nodes, under which the selected node obtaining access to the network could be modeled by a periodic function. A lifting technology is introduced to reformulate the system model into a linear system without delays. The aim of the addressed problem is to develop a moving horizon estimator such that the estimation error is ultimately bounded. A sufficient condition is established to ensure the ultimate boundedness in terms of a matrix inequality. Within the established theoretical framework, two optimization problems are proposed to calculate the corresponding estimator parameters according to two different performance requirements (e.g., the smallest ultimate bound and the fastest decay rate). Finally, simulation examples are given to illustrate the effectiveness of the estimator design scheme. [ABSTRACT FROM AUTHOR]

In this paper, we consider the distributed filtering problem for continuous-time stochastic systems over sensor networks subject to Markovian switching topologies. Due to limited communication energy and bandwidth, an event-based communication scheme is proposed with the aim to decrease the transmission frequency. An individual triggering condition is put forward to regulate the communication rates for each component of the system state in order to better reflect the engineering requirements. The aim of this paper is to design a distributed filter over sensor networks with Markovian switching topologies such that the dynamics of the estimation error is exponentially mean-square bounded. It is shown that, with the proposed event-based distributed filtering algorithm, the exponential mean-square boundedness of the estimation errors is guaranteed if the sensor network is distributively detectable and the combined communication topology is strongly connected. A numerical example is presented to illustrate the usefulness of the developed algorithm. [ABSTRACT FROM AUTHOR]

This paper is concerned with the recursive filtering problem for a class of networked linear time-varying systems subject to the scheduling of the random access protocol (RAP). The communication between the sensor nodes and the remote filter is implemented via a shared network. For the purpose of preventing the data from collisions, only one sensor node is allowed to get access to the network at each time instant. The transmission order of sensor nodes is orchestrated by the RAP scheduling, under which the selected nodes obtaining access to the network could be characterized by a sequence of independent and identically-distributed variables. The aim of the addressed filtering problem is to design a recursive filter such that the filtering error covariance could be minimized by properly designing the filter gain at each time instant. The desired filter gain is calculated recursively by solving two Riccati-like difference equations. Furthermore, the boundedness issue of the corresponding filtering error covariance is investigated. Sufficient conditions are obtained to ensure the lower and upper bounds of the filtering error covariance. Two illustrative examples are given to demonstrate the correctness and effectiveness ofour developed recursive filtering approach. [ABSTRACT FROM AUTHOR]

The stability and stabilization problems for a class of switched discrete-time nonlinear systems are studied in this paper. Each nonlinear subsystem of the presented switched system is modeled as a piecewise affine (PWA) one by splitting the state space into polyhedron regions. With the aid of a simple searching strategy for active state transition pairs at a switching instant, i.e., the so-called $\mathbb {S}$ -arbitrary switching approach, the stability criteria are derived via the relaxed piecewise quadratic Lyapunov function technique. Then, using the descriptor system approach, a family of PWA stabilizing controllers are designed to guarantee exponential stability of the resulting closed-loop control system, and the corresponding PWA controller gains could be calculated using numerical software. The validity and potential of the developed techniques are verified through a numerical example. [ABSTRACT FROM AUTHOR]

This paper is concerned with the ultimate boundedness control problem for a class of networked nonlinear systems subject to the try-once-discard (TOD) protocol scheduling and uniform quantization effects. To prevent the transmission data from collisions, the communication between sensor nodes and the controller is implemented via a constrained communication channel, where only one sensor node is permitted to transmit data at each time instant. The TOD protocol is utilized to regulate the signal transmission over the communication network under which the scheduling behavior is described by a special switching function. On the other hand, the uniform quantization effects of the network are characterized by a round function (i.e., the nearest integer function). The purpose of the addressed problem is to design an observer-based controller for the networked nonlinear systems such that, in the presence of TOD protocol and uniform quantization effects, the closed-loop system is ultimately bounded and the controlled output is locally minimized. Sufficient conditions are established to guarantee the ultimate boundedness of the dynamics of the closed-loop system in mean square by applying the stochastic analysis approach. Furthermore, the desired controller gains are derived by solving a convex optimization problem. Finally, a numerical example is given to illustrate the effectiveness of the proposed controller design scheme. [ABSTRACT FROM PUBLISHER]

This technical note focuses on a class of switched nonlinear systems with unstable modes and switching uncertainties. Both prescribed switching instants and switching sequence of the nominal switching signal would change. Two novel indexes named time changing ratios and mode changing ratios are proposed, based on which several conditions that fully utilize the trade-off among stable and unstable modes are established to achieve the robust stability of the switched system. An example of multi-agent systems illustrates the efficiency of the new results. [ABSTRACT FROM PUBLISHER]