Publications

This paper proposes an event-triggered quantized-data feedback control scheme for linear systems. An event-triggered communication scheme is introduced to select which sampled-data should be quantized and transmitted to the controller. The threshold is constructed by considering the difference between the current sampled data and the latest quantized data. A finite-level dynamical quantizer is developed based on the communication scheme and quantized data. An output feedback controller is designed to ensure that the state of the closed-loop is uniform ultimate bounded. A numerical example illustrates the effectiveness of the proposed approach.

Due to the limited understanding of Industrial Control Systems (ICSs), device identification has become increasingly vital for threat detection and security defense in ICS environments. However, the narrow range of device types and models in the existing datasets has significantly hindered the effectiveness and scalability of current device identification methods. To address this gap, we introduce a novel data collection framework specifically designed for ICS devices and present the resulting dataset, ICSLibrary, which we have made publicly available. To the best of the authors' knowledge, ICSLibrary is the first dataset dedicated to device identification in ICS security. It encompasses the most extensive range of device types, models and instances from 27 industrial vendors, collected across two countries over a 21-month period. Furthermore, we use ICSLibrary as a benchmark to evaluate several typical device fingerprinting methods, revealing a notable 16% drop in accuracy in the device model identification task, which highlights the unique challenges posed by ICSLibrary.

This paper is concerned with distributed attack detection for a discrete time-varying system monitored by a sensor network. An adversary simultaneously launches distinct data deception attacks on both the system dynamics and sensor intercommunication links so as to intentionally falsify the system state and the exchanged sensor measurement outputs. First, delicate distributed estimators are constructed, aiming to provide resilient local estimates for unavailable system state and appropriate residuals for attack detection. Second, an auxiliary Krein space state–space model as well as innovation analysis and a projection technique is skillfully employed to cast the finite horizon distributed estimator design problem into a minimization problem of a certain indefinite quadratic form. A necessary and sufficient condition on the existence of the minimum is derived. Third, a computational efficient recursive algorithm is developed to design desired distributed estimators such that the local estimates and residuals can be both determined at each time step. Furthermore, a two-stage distributed detection mechanism is proposed for each estimator to alert the attack occurrence. Specifically, it is shown that by properly choosing a weighting matrix parameter, each estimator can respectively detect the deception attacks launched on the system layer and sensor intercommunication links. Finally, the effectiveness of the proposed approach is demonstrated through numerical verification.

This paper addresses the sampled-data multi-objective active suspension control problem for an in-wheel motor driven electric vehicle subject to stochastic sampling periods and asynchronous premise variables. The focus is placed on the scenario that the dynamical state of the half-vehicle active suspension system is transmitted over an in-vehicle controller area network that only permits the transmission of sampled data packets. For this purpose, a stochastic sampling mechanism is developed such that the sampling periods can randomly switch among different values with certain mathematical probabilities. Then, an asynchronous fuzzy sampled-data controller, featuring distinct premise variables from the active suspension system, is constructed to eliminate the stringent requirement that the sampled-data controller has to share the same grades of membership. Furthermore, novel criteria for both stability analysis and controller design are derived in order to guarantee that the resultant closed-loop active suspension system is stochastically stable with simultaneous H2 and H∞ performance requirements. Finally, the effectiveness of the proposed stochastic sampled-data multi-objective control method is verified via several numerical cases studies in both time domain and frequency domain under various road disturbance profiles.

Offshore platforms often endure a variety of continuous marine loads, each capable of inducing vibrations that pose risks, such as structural damage, personnel discomfort, fatigue, and safety hazards. Therefore, active vibration control emerges as a cornerstone in ocean platform engineering. This study focuses on addressing the problem of wave-induced vibration suppression using fuzzy sampled-data control techniques. Initially, a Takagi–Sugeno fuzzy dynamic model of offshore structures is developed by taking into account time-varying perturbations in natural frequency and damping ratio of the dominant vibration mode and unmodeled dynamics induced by other modes of structure. Then, using the looped functional method, several sufficient conditions are obtained to ensure the asymptotic stability of the closed-loop system. Based on these conditions, an algorithm is devised to compute suitable control gains in terms of linear matrix inequalities. Finally, extensive simulations demonstrate the efficacy of the proposed sampled-data fuzzy controller. Not only does it exhibit robustness against parametric perturbations in offshore structures, but it also yields significant reductions in wave-induced responses, thus fortifying the platform’s safety and resilience.

This chapter is concerned with distributed secondary frequency and voltage control for islanded microgridsMicrogrids. First, the distributed secondary controlSecondary control problem is formulated by taking both communication delaysCommunication delays and...

This paper focuses on stabilization of second-order oscillatory systems using both feedback control and intentionally introduced time delay. The argument principle is employed as a key technique to divide the parameter space of time delay and controller gain into several regions. Every admissible value in these regions moves the poles of the closed-loop system towards the left of the complex plane such that stability improvement is achieved. The concept of potent asymptotic stability is first introduced, referring to the property that all the poles of the closed-loop system are stable and lie on the left of open-loop system poles in the complex plane. Analytical characterizations on parameter pairs of time delay and controller gain that result in potent asymptotic stability are established. All the poles and corresponding root locus with respect to gain are examined. Numerical examples and simulations are given to illustrate the usefulness and merits of the theoretical results.

This paper is concerned with the problem of delay-dependent robust H/sub /spl infin// control for uncertain time-delay fuzzy systems with norm-bounded uncertainty. The time-delay is assumed to be a time-varying continuous function belonging to a given interval, which means that the lower and upper bounds for the delay are available. No restriction on the derivative of the time-varying delay is needed, which allows the time-delay to be a fast time-varying function. The state-space Takagi-Sugeno (T-S) uncertain fuzzy model with interval time-varying delay is adopted. Delay-dependent conditions for the existence of robust H/sub /spl infin// controller are presented in the form of linear matrix inequalities (LMIs). A numerical example is given to demonstrate the effectiveness of the proposed method.

This paper deals with the problem of distributed optimization of a multiagent system with network connectivity preservation. In order to realize cooperative interactions, a connected network is the prerequisite for high-quality information exchange among agents. However, sensing or communication capability is range-limited, so it is impractical to simply make an assumption that network connectivity is preserved by default. To address this concern, a class of generalized potentials including discontinuities caused by unexpected obstacles or noises are designed. For a class of quadratic cost functions, based on the potentials, a new distributed protocol is proposed to formally guarantee the network connectivity over time and to realize the state agreement in finite time while the sum of local functions known to individual agents is optimized. Since the right-hand side of the proposed protocol is discontinuous, some nonsmooth analysis tools are applied to analyze system performance. In some practical scenarios, where initial states are unavailable, a distributed protocol is further developed to realize the consensus in a prescribed finite time while solving the distributed optimization problem and maintaining network connectivity. Illustrative examples are provided to demonstrate the effectiveness of the proposed protocols.

This paper investigates the stability of linear uncertain systems with time‐varying delay. Stability criteria are derived based on a generalized discretized Lyapunov functional approach. The kernel of the functional, which is a function of two variables, is chosen as piecewise linear. The stability conditions are written in the form of linear matrix inequalities. Numerical examples indicate significant improvements over the existing results.

No abstract is provided for this article.

This chapter addresses the observer-based FDFFault Detection Filter (FDF) design for a continuous-time NCS by taking packet dropouts and network-induced delays into account. An observer-based FDFFault Detection Filter (FDF) and a reference residual model are introduced to construct a model for the continuous-time NCS. To reduce the time for fault detection, a new data reconstructionData reconstruction scheme is proposed and the corresponding closed-loop model is established. Based on the established models, FDF design criteria are derived to asymptotically stabilize the residual system.

This brief is concerned with delay-dependent stability for neural networks with two additive time-varying delay components. By constructing a new Lyapunov functional and using a convex polyhedron method to estimate the derivative of the Lyapunov functional, some new delay-dependent stability criteria are derived. These stability criteria are less conservative than some existing ones. An example is given to demonstrate the less conservatism of the stability results.

Industrial cyber-physical systems closely integrate physical processes with cyberspace, enabling real-time exchange of various information about system dyn

In this paper, we present a novel H ∞ control scheme for a networked control system (NCS) with multiple data packet dropouts. Multiple data packet dropouts occur randomly in both control channel and measurement channel. The NCS with both measurement and control packet dropouts is modeled as a stochastic parameter system which contains two independent Bernoulli distributed white sequences. An H ∞ dynamic output controller is designed to exponentially stabilize the networked system in the sense of mean square, and also to achieve the prescribed H ∞ disturbance attenuation level. An iterative algorithm is developed to compute the optimal H ∞ disturbance attenuation and the controller parameters by solving the semi-definite programming problem via an interior-point approach. Two illustrative examples are provided to show the applicability of the proposed method.

This paper is concerned with observer-based H <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">∞</sub> control for a networked control system (NCS) under simultaneous consideration of time-varying network-induced delays and packet dropouts. By taking the sensor-to-controller and controller-to-actuator network-induced delays and packet dropouts into full consideration and proposing a linear estimation-based delay compensation method, a new model for an observer-based NCS is established. Then the stabilization criteria for the considered NCS are derived. When transferring nonlinear matrix inequalities into linear matrix inequalities (LMIs), new bounding inequalities are proposed. A numerical example is given to illustrate the merits and effectiveness of the obtained results.