This article is concerned with designing resilient state feedback controllers for a class of networked control systems under denial-of-service (DoS) attacks. The sensor samples system states periodically. The DoS attacks usually prevent those sampled signals from being transmitted through a communication network. A logic processor embedded in the controller is introduced to not only receive sampled signals but also capture information on the duration time of each DoS attack. Note that the duration time of DoS attacks is usually both lower and upper bounded. Then the closed-loop system is modeled as an aperiodic sampled-data system closely related to both lower and upper bounds of duration time of DoS attacks. By introducing a novel looped functional, which caters for the $N$ -order canonical Bessel–Legendre inequalities, some $N$ -dependent stability criteria are presented for the resultant closed-loop system. It is worth pointing out that a number of identity formulas are uncovered, which enable us to apply the notable free-weighting matrix approach to derive less conservative stability criteria. A linear-matrix-inequality-based criterion is provided to design stabilizing state-feedback controllers against DoS attacks. A satellite control system is given to demonstrate the effectiveness of the proposed method.

Resilient Control Design Based on a Sampled-Data Model for a Class of Networked Control Systems Under Denial-of-Service Attacks

This paper investigated the problem of H∞output tracking for a type of discrete network-based control systems subjected to quantization and data dropout. The state of controlled system and the reference model state were quantized before being communicated. The quantization error was treated as sector-bounded uncertainty. The effect of the random packet loss was modelled as a Bernoulli process. Later, a sufficient condition was proposed for the existence of H∞tracking controllers in terms of linear matrix inequalities(LMIs). The proposed controller could guarantee the output of the closed-loop networked control system tracks that of a given reference model well in the H∞sense.Finally, a numerical example was prensented to show the effectiveness and usfulness of the proposed H∞output tracking design.

Network-Based H_∞ Output Tracking Control for a Type of Discrete Time Systems

Network-based fuzzy control for nonlinear Markov jump systems subject to quantization and dropout compensation

This paper investigates the dissipative filtering problem for a class of discrete-time switched fuzzy systems with missing measurements. The fuzzy plant under consideration incorporates characteristics of Takagi–Sugeno fuzzy systems and switched systems simultaneously. The occurrence of missing measurements is described by a stochastic variable that satisfies the Bernoulli binary distribution, which characterizes the effect of data loss in information transmission between the plant and the filter. Utilizing the Lyapunov function technique, sufficient conditions are developed to ensure that the resultant filtering error system is exponentially stable and strictly dissipative. Two simulation examples are presented to illustrate the validity of the proposed method.

Dissipative Filtering for Switched Fuzzy Systems With Missing Measurements

The problem of observer-based finite-time H∞ control for discrete-time Markov jump systems with time-varying transition probabilities and uncertainties is studied in this paper, in which time-varying transition probabilities are modelled as convex polyhedron, and the parameter uncertainty satisfies norm-bounded. First of all, a Luenberger observer is designed to measure the system state. Then, observer-based controller is constructed to ensure the stochastic finite-time boundedness of the resulting closed-loop system with an H∞ performance. Furthermore, sufficient conditions are derived in light of linear matrix inequalities. In the end, the flexibility and applicability of the developed methods are demonstrated by two illustrative examples.

Observer-based finite-time H∞ control for uncertain discrete-time nonhomogeneous Markov jump systems

In this note, we discuss the modeling and control of a class of Ito stochastic networked control systems (NCSs) with packet dropouts that are subject to time-varying sampling. The system under consideration is first modeled as a continuous-time system with input delay that is subject to double randomness via the input-delay approach. Then, by assuming the packet drop rate and recurring to the celebrated formula of total probability, an equivalent model which takes full advantage of probability distribution characteristics of both packet dropouts and sampling periods is established. In particular, the probability distribution values of the stochastic delay taking values in two given intervals can be explicitly obtained, which is of crucial importance to model and analyze the actual problem in NCSs. Based on that, robustly exponentially mean-square stability of the system with an $H_\infty$ performance is guaranteed, an $H_\infty$ controller design procedure is then proposed. Finally, a numerical simulation example is exploited to show the effectiveness and applicability of the results derived and some less conservative results are obtained.

Modeling and Control of Itô Stochastic Networked Control Systems With Random Packet Dropouts Subject to Time-Varying Sampling

Stabilizability of minimum-phase systems with colored multiplicative uncertainty

In practice, deception attacks, uncertainties, and randomly occurring nonlinearities (RONs) in multi‐agent systems (MASs) are ubiquitous. Consequently, this paper settles the problem of secure consensus tracking control for uncertain MASs with randomly occurring nonlinearities under sensor attacks by adopting adaptive impulsive control methods. Compared with the previous works, a class of state‐dependent sensor attack is firstly considered in the impulsive control. Meanwhile, a novel adaptive algorithm is introduced to deal with unknown system matrices, randomly occurring nonlinearities and uncertain parameters caused by sensor attacks. Sufficient conditions are derived to achieve leader‐following consensus for the MASs by adaptive impulsive control under sensor attacks. Lastly, two simulation examples illustrate the validity of theorems in this paper.

Adaptive impulsive security consensus control of uncertain multi‐agent systems with randomly occurring nonlinearities

This paper proposes a method to suppress the tension disturbance caused by the rotation of the unwinding flip stand of the gravure printing machine. Firstly, a nonlinear model with unknown parameters is established for the disturbance according to the mechanism. Then the unknown parameters in the model are estimated by the particle swam optimization (PSO). Finally, a feedforward control method is applied to attenuate the disturbance. The comparison experimental results show that the proposed method performs well in tension disturbance attenuation.

Tension Disturbance Rejection based on Particle Swarm Optimization for Unwinding Systems

This work studies the mean-square stability and stabilization problem for netwroked feedback systems. Data transmission delays in the network channels of the systems are considered. It is assumed that these delays are i.i.d. processes with given PMFs. A necessary and suﬃcient condition of mean-square (input-output) stability is studied for the networked feedback systems in both time-domain and frequency-domain. Furthermore, according to this condition, mean-square stabization via output feedback is studied for the networked feedback systems in terms of the state-space models.

Junhui Li

Papers

Modeling and Control of Itô Stochastic Networked Control Systems With Random Packet Dropouts Subject to Time-Varying Sampling

Stabilizability of minimum-phase systems with colored multiplicative uncertainty

Adaptive impulsive security consensus control of uncertain multi‐agent systems with randomly occurring nonlinearities

Tension Disturbance Rejection based on Particle Swarm Optimization for Unwinding Systems

Mean-square stability of linear systems over channels with random transmission delays