Liwei An

Northeastern University (Shenyang, China) | NEU · College of Information Science and Engineering

This article pays attention to the obstacle avoidance trajectory tracking control problem for uncertain Euler–Lagrange (EL) systems subject to velocity constraints and input saturation. The existing obstacle avoidance results do not consider velocity constraints under input saturation, which means that an EL system may not be able to obtain suffici...

This paper studies the problem of event-triggered (ET) backstepping control with state/output triggering for nonlinear strict-feedback systems. To address the issue of nondifferentiability of virtual controls caused by the ET mechanism, a set of homogeneous feedback filters are constructed to generate smooth state/output estimates with necessary di...

This paper studies the problem of collision/obstacle avoidance in the distributed cooperative output regulation of nonlinear multi-agent systems (MASs). First, a nonlinear distributed command governor equipped by two dynamical barrier functions is constructed to generate safe command signals. Then, a filtering-based distributed command tracking con...

Reference governors are add-on control schemes which enforce state constraints on pre-stabilized systems by modifying, whenever necessary, the reference. This paper studies the design schemes of reference governors for collisions-free leader-following coordination (CF-LFC) of nonlinear multi-agent systems under unreliable communications. The “unrel...

This paper studies the problem of obstacle avoidance in the distributed optimal coordination (DOC) for a class of uncertain multi-robot systems. Due to the existence of the obstacle regions, the considered optimization problem is intrinsically non-convex, which will result in the generation of some unexpected equilibriums (local minima). The existi...

In a sensor network, some sensors usually provide the same or equivalent measurement information, which is not taken into account by the existing secure state estimation methods against sparse sensor attacks such that the computational efficiency of these methods needs to be further improved. In this paper, by considering the observation equivalenc...

Opacity, a confidentiality property that characterizes whether a “secret” of a system can be inferred by an outside intruder, is an increasing concern in cyber–physical systems (CPSs). The existing distributed estimation algorithms allow each node to broadcast its explicit state information to its neighbors, which results in the disclosure of CPS’s...

This article investigates the data-based distributed sensor scheduling for a wireless sensor network (WSN), where multiple sensor nodes monitor different linear systems correspondingly. The WSN admits a network topology to formulate a fully distributed sensor scheduling policy, and transmits measured information over a shared wireless channel. Due...

This article studies the problem of distributed optimal coordination (DOC) for heterogeneous linear multiagent systems. Compared with the existing results where the structure constraints on local gradients or system matrices are required, the considered DOC framework is sufficiently general in the sense that no extra assumption is required except...

This article studies a class of distributed attack strategies against state estimation of wireless sensor networks. The attack objective is to corrupt the least numbers of sensors so that the state estimate error approaches a target bias while avoiding being detected and high attacking is lost. First, with precise knowledge of the measurement model...

This paper proposes two distributed state estimation protocols for static linear cyber–physical systems under Byzantine links/nodes caused by adversarial attacks. First, a basic version of secure distributed algorithm is proposed where the influence of the Byzantine links/nodes is countered by adopting a local min-switching decision (LMSD) rather t...

Multiagent distributed optimal coordination (DOC) involves the motion conflicts of a large numbers of physical systems, which lead to significant safety challenges in terms of collision avoidance. This article studies the problem of secure DOC for multiple uncertain Euler–Lagrangian (EL) systems. The objective is to steer each EL agent to achieve...

In a sensor network, some sensors usually provide the same or equivalent measurement information, which is not taken into account by the existing secure state estimation methods against sparse sensor attacks such that the computational efficiency of these methods needs to be further improved. In this paper, by considering the observation equivalenc...

This paper studies the problem of distributed optimal coordination (DOC) for a class of nonlinear large-scale cyber-physical systems (CPSs) in the presence of cyber attacks. A secure DOC architecture with attack diagnosis is proposed that guarantees the attack-free subsystems to achieve the output consensus which minimizes the sum of their objectiv...

This article investigates the problem of secure state estimation for continuous-time linear systems in the presence of sparse sensor attacks. Compared with the existing results, the attacked sensor set can be changed by adversaries against secure estimation. To address the more erratic attacks, a novel supervisory state observer is proposed, which...

Computer memory occupation is an important issue in secure estimation of cyber-physical systems. The existing secure state observers, which estimate system state from sparsely corrupted measurements, often need to run combinatorial sub-estimators such that they demand tremendous memory occupation. To this end, this paper proposes two adaptive obser...

This paper considers the transmission power scheduling in the control of a linear plant when the plant state is transmitted from a sensor to the controller over a wireless fading channel. The power allocated to these transmissions determines the probability of successful packet reception. This paper focuses on investigating how much power should be...

Cyber–physical systems (CPSs) usually employ distributed sensor networks to gather, process and exchange information as a team. In contrast to the previous centralized secure state estimation (SSE) for CPSs, this paper proposes a distributed SSE algorithm via consensus-based distributed non�convex optimization protocols. The algorithm is implemente...

Attack optimization is an important issue in securing cyber‐physical systems. This paper investigates how an attacker should schedule its denial‐of‐service attacks to degrade the robust performance of a closed‐loop system. The measurements of system states are transmitted to a remote controller over a multichannel network. With limited resources, t...

Opacity, a confidentiality property, is an increasing concern in cyber-physical systems (CPSs) that are vulnerable to an intruder which intends to reveal a “secret” of a system. This paper presents a new framework for opacity and considers the problem of enforcing opacity in CPSs modeled as linear time-invariant systems. The confidential informatio...

State estimation from the sparsely corrupted measurements, a combinatorial problem, has been addressed by brute force search or convex relaxations in the literature. However, the computational efficiency and estimation correctness of these methods cannot be simultaneously guaranteed. This paper studies how to relieve the computational complexity on...

This paper investigates the problem of secure control for cyber-physical systems (CPSs) under sensor and actuator attacks. The attacks are assumed to be sparse but arbitrary. The strong detectability under the sparse attacks is characterized by computing the rank of the called structural matrix pencil. An adaptive hybrid control strategy is propose...

In this paper, an adaptive output feedback compensation control scheme is proposed for a class of non�linear systems with unknown sensor failures. For estimating the unmeasured states, a novel switching�type adaptive observer is constructed, in which the observer gains are tuned in a switching manner. To compensate for the failure effects on transi...

This paper is concerned with the problem of adaptive stabilization for a class of switched linear‐parametric nonlinear systems under arbitrary switching. The traditional adaptive backstepping control is successfully extended to switched systems from nonswitched ones where the asymptotic regulation of system state is not destroyed due to rapid or ab...

Cyber-physical systems (CPSs) are naturally highly interconnected and complexly nonlinear. This paper investigates the problem of decentralized adaptive output feedback control for CPSs subject to intermittent denial-of-service (DoS) attacks. The considered CPSs are modeled as a class of nonlinear uncertain strict-feedback interconnected systems. W...

This paper investigates the problem of adaptive fault-tolerant control for a class of nonlinear parametric strict-feedback systems with multiple unknown control directions. Multiple sensor faults are first considered such that all real state variables are unavailable. Then, a constructive design method for the problem is set up by exploiting a para...

This paper investigates the problem of secure state estimation for cyber-physical systems (CPSs) modeled by continuous or discrete-time linear systems when some sensors are corrupted by an attacker. A novel state observer is proposed with adaptive switching mechanism. Attack tolerance principle is established based on adaptively truncating the inje...

This paper studies the robust stabilization problem for a class of uncertain nonlinear systems with unstable zero dynamics. The considered zero dynamic is not assumed to be input-to-state practically stable and contains nonlinear uncertainties and mismatched external disturbances. A new robust adaptive fuzzy control method is developed by combining...

Data-driven cyber attacks are more practical than the existing model-based ones. This technical note, from the attacker's standpoint, investigates how an adversary should design a sensor-actuator coordinated attack policy to degrade system performance while undetected, without exact knowledge of system matrices. To guarantee the attack undetected,...

In this paper, an improved adaptive resilient control scheme is proposed for mitigating adversarial attacks in cyber-physical systems (CPSs). By introducing a two-step backstepping approach, an adaptive bound estimation mechanism and a Nussbam function with faster growth rate, the effects of unknown sensor and actuator attacks are successfully miti...

This paper investigates the adaptive fuzzy decentralized control problem for a class of uncertain nonlinear large-scale systems. Different from the conventional backstepping-based adaptive output feedback control technique, the output measurements are imperfect and considered to suffer random packet dropouts (RPDs), random sensor delays (RSDs) and...

This paper investigates the H∞ static output feedback (SOF) control problem for switched linear system under arbitrary switching, where the actuator failure models are considered to depend on switching signal. An active reliable control scheme is developed by combination of linear matrix inequality (LMI) method and adaptive mechanism. First, by exp...

This paper deals with the problem of adaptive tracking control for a class of switched uncertain nonlinear systems under arbitrary switching. First, combing fuzzy approximation and dynamic surface control (DSC), a switched adaptive statefeedback control scheme is proposed based on directly tuning the estimation of the switching ideal weight vectors...

This paper investigates the exact tracking control problem for a class of uncertain nonlinear switched systems with arbitrary switchings. Two mode-dependent adaptive backstepping state feedback control schemes are presented, where unknown switching parameters are directly estimated via switched adaptive laws. To avoid the loss of adaptive informati...

This paper investigates the adaptive H∞ static output feedback (SOF) control problem for continuous-time linear systems with stochastic sensor failures. A multi-Markovian variable is introduced to denote the failure scaling factors for each sensor. Different from the existing results, the failure parameters are stochastically jumping and their boun...

This paper focuses on the problem of fault detection (FD) for a class of nonlinear systems described by the T-S fuzzy singular model with multiple time delays and actuator faults. Two finite-frequency performance indices are introduced to measure fault sensitivity and disturbance robustness. To reduce the conservatism of the existing results, a fin...

This studies the fuzzy-approximation-based adaptive memory fault-tolerant control problem for a class of non-linear time-delay systems with non-affine non-linear delayed faults. The main advantages of the developed scheme are as follows: first, based on the partial information of time-varying delays, the unknown delay terms are approximated by comb...

In this paper, delay-independent fault detection and accommodation (FDA) control is developed for a class of uncertain nonlinear time-delay systems with multiple time-delay faults and external disturbances. Compared with the existing results, the system states are unmeasurable and the bounds of model uncertainties and the disturbances only exist bu...

This paper investigates the simultaneous fault detection and control (SFDC) problems for a class of discrete-time networked systems with multiple stochastic delays and data missing. Both faults and disturbances are assumed to be in low frequency domain. The communication delays are uniformly modeled by multiple random variables obeying the Bernoull...

In this study, the problem of filtering-based adaptive fuzzy control is investigated for non-linear strict-feedback systems with unmeasured states. An input-driven filter is designed for estimating the unmeasured states. By exploiting the bound of system output, an upper bound of filtering error is obtained and it is further optimised by solving a...

In this paper, the problem of adaptive fuzzy tracking control is investigated for a class of switched nonlinear systems. A new switched adaptive output feedback control method is presented where the changes of plant can be considered explicitly. Mode-dependent fuzzy logic systems are employed to approximate the switching nonlinear functions in syst...

In this paper, delay-dependent adaptive dynamic surface control (DSC) is developed for a class of uncertain nonlinear time-delay systems. The considered system is in strict-feedback form with unknown dead zone. Compared with the existing results, a novel adaptive fuzzy memory state feedback controller is constructed, which relaxes the restrictions...

This paper investigates the fault detection (FD) problem for networked control systems (NCS). The random delays from the sensor to the controller (S-C) and from the controller to the actuator (C-A) are modeled as a Markov chain. Whilst considering the data dropout phenomenon happens unavoidably and the measurement drops intermittently, C-A data dro...

In this study, we propose two backstepping-based adaptive fuzzy fault-tolerant control (FTC) methods for a class of nonlinear strict-feedback systems with actuator failures. First, a traditional FTC (TFTC) method is considered. Our analysis shows that TFTC has poor tracking performance due to the existence of approximation errors and external distu...

This paper is devoted to investigating the stability and stabilisation problems for discrete-time piecewise homogeneous Markov jump linear system with imperfect transition probabilities. A sufficient condition is derived to ensure the considered system to be stochastically stable. Moreover, the corresponding sufficient condition on the existence of...