Non-fragile guaranteed cost control for networked nonlinear Markov jump systems under multiple cyber-attacks

This paper is concerned with the problem of non-fragile guaranteed cost control (GCC) for networked nonlinear Markov jump systems subject to multiple cyber-attacks, which are characterized by Takagi–Sugeno (T–S) fuzzy model with time-varying delay. Specifically, a variety of cyber-attacks, including deception attacks and Denial-of-Service (DoS) attacks, are considered, which occur in the forward and feedback communication links, respectively. To achieve stochastic stability under guaranteed cost function (GCF), the paper proposes a Lyapunov–Krasovskii (L–K) function approach. The approach derives sufficient conditions for stochastic stability, and obtains non-fragile controller gains and the uniform upper bound of the GCF using linear matrix inequalities (LMIs) technique. Finally, the effectiveness of the proposed algorithm is evaluated by simulation experiment.     

具有输入时滞的关联不确定大系统的分散鲁棒控制

研究了一类同时具有输入时滞以及不确定参数的关联大系统的稳定性问题.基于所谓的还原法,给出一种新的状态反馈控制器的设计方法,这种方法的不同之处在于利用了时延的大小以及反馈控制的历史信息.根据Lyapunov稳定性理论得到了系统在控制器作用下稳定的充分条件,所有条件都化成可解的标准线性矩阵不等式(LMIs)形式.最后给出了一个数值例子,说明结果的可行性,并和一般无记忆的控制器相比较,说明建立的控制器有着更好的性能.     

Backstepping-based decentralized adaptive neural H∞ tracking control for a class of large-scale nonlinear interconnected systems

The decentralized tracking control methods for large-scale nonlinear systems are investigated in this paper. A backstepping-based robust decentralized adaptive neural H_∞ tracking control method is addressed for a class of large-scale strict feedback nonlinear systems with uncertain disturbances. Under the condition that the nonlinear interconnection functions in subsystems are unknown and mismatched, the decentralized adaptive neural network H_∞ tracking controllers are designed based on backstepping technology. Neural networks are used to approximate the packaged multinomial including the unknown interconnections and nonlinear functions in the subsystems as well as the derivatives of the virtual controls. The effect of external disturbances and approximation errors is attenuated by H_∞ tracking performance. Whether the external disturbances occur or not, the output tracking errors of the close-loop system are guaranteed to be bounded. A practical example is provided to show the effectiveness of the proposed control approach.     

Robust resilient controllers synthesis for uncertain fractional-order large-scale interconnected system

The problem of the decentralized stabilization for fractional order large-scale interconnected uncertain system with norm-bounded parametric uncertainties and controller gain perturbations is studied. It is solved under two circumstances: one is under the additive controller gain perturbations; the other is under the multiplicative ones. Sufficient conditions on the decentralized stabilization of fractional order large-scale interconnected system with a commensurate order 0<α<1$0<\alpha <1$ are established by applying a complex Lyapunov inequality method. The state feedback non-fragile controller designs for fractional order large-scale interconnected uncertain system under the two classes of gain perturbations are obtained in terms of solutions to LMIs. Numerical examples are used to illustrate the effectiveness of the proposed method.     

Delay-dependent guaranteed cost control for uncertain 2-D discrete systems with state delay in the FM second model

This paper is concerned with the problem of delay-dependent guaranteed cost control for uncertain two-dimensional (2-D) state delay systems described by the Fornasini and Marchesini (FM) second state-space model. Given a scalar α∈(0,1), a sufficient condition for the existence of delay-dependent guaranteed cost controllers is given in terms of a linear matrix inequality (LMI) based on a summation inequality for 2-D discrete systems. A convex optimization problem is proposed to design a state feedback controller stabilizing the 2-D state delay system as well as achieving the least guaranteed cost for the resulting closed-loop system. Finally, the simulation example of thermal processes is given to illustrate the effectiveness of the proposed result.     

Event-triggered decentralized output-feedback control for interconnected nonlinear systems with input quantization

In this paper, the event-triggered decentralized control problem for interconnected nonlinear systems with input quantization is investigated. A state observer is constructed to estimate the unmeasurable states, and the state-dependent interconnections are accommodated by presenting some smooth functions. Then by employing backstepping technique and neural networks (NNs) approximation capability, a novel decentralized output feedback control strategy and an event-triggered mechanism are designed simultaneously. It is proved through Lyapunov theory that the closed-loop system is stable and the tracking property of all subsystems is guaranteed. Finally, the effectiveness of the proposed scheme is illustrated by an example.     

New results on robust finite-time stability of singular large-scale complex systems with interconnected delays

In this paper, we provide an efficient approach based on combination of singular value decomposition (SVD) and Lyapunov function methods to finite-time stability of linear singular large-scale complex systems with interconnected delays. By representing the singular large-scale system as a differential-algebraic system and using Lyapunov function technique, we provide new delay-dependent conditions for the system to be regular, impulse-free and robustly finite-time stable. The conditions are presented in the form of a feasibility problem involving linear matrix inequalities (LMIs). Finally, a numerical example is presented to show the validity of the proposed results.     

On designing decentralized impulsive controllers for synchronization of complex dynamical networks with nonidentical nodes and coupling delays

This paper investigates the problem of designing decentralized impulsive controllers for synchronization of a class of complex dynamical networks (CDNs) about some prescribed goal function. The CDNs are allowed to possess nonidentical nodes and coupling delays. Two cases of time-varying coupling delays are considered: the case where the coupling delays are uniformly bounded, and the case where the derivatives of the coupling delays are not greater than 1. The synchronization analysis for the first case is performed by applying a time-varying Lyapunov function based method combined with Razumikhin-type technique, while the synchronization analysis for the second case is conducted based on a time-varying Lyapunov functional based method. For each case, by utilizing a convex combination technique, the resulting synchronization criterion is formulated as the feasibility problem of a set of linear matrix inequalities (LMIs). Then, sufficient conditions on the existence of a decentralized impulsive controller are presented by employing these newly obtained synchronization criteria. The local impulse gain matrices can be designed by solving a set of LMIs. Finally, two representative examples are given to illustrate the correctness of the theoretical results.     

Affine matched parameterization approach to sampled-data stabilization criteria for T-S fuzzy systems with variable sampling

This paper presents new parameterized sampled-data stabilization criteria using affine transformed membership functions for T-S fuzzy systems. To deal with the sampled control input having aperiodic sampling intervals, the proposed method adopts new looped functionals, and employs a modified free weighting matrix inequality. A relaxed condition for the controller design is derived by formulating the constraint conditions of the membership functions in the proposed controller with affinely matched weighting parameter vectors. Based on a newly devised lemma for handling affinely matched vectors, the stabilization and guaranteed cost performance criteria are given in terms of linear matrix inequalities (LMIs). The superiority of the presented method is demonstrated via significantly improved results in numerical examples.     

Fast-DRD: Fast decentralized reinforcement distillation for deadline-aware edge computing

Edge computing has recently gained momentum as it provides computing services for mobile devices through high-speed networks. In edge computing system optimization, deep reinforcement learning(DRL) enhances the quality of services(QoS) and shorts the age of information(AoI). However, loosely coupled edge servers saturate a noisy data space for DRL exploration, and learning a reasonable solution is enormously costly. Most existing works assume that the edge is an exact observation system and harvests well-labeled data for the pretraining of DRL neural networks. However, this assumption stands in opposition to the motivation of driving DRL to explore unknown information and increases the scheduling and computing costs in large-scale dynamic systems. This article leverages DRL with a distillation module to drive learning efficiency for edge computing with partial observation. We formulate the deadline-aware offloading problem as a decentralized partially observable Markov decision process (Dec-POMDP) with distillation, called fast decentralized reinforcement distillation(Fast-DRD). Each edge server decides makes offloading decisions in accordance with its own observations and learning strategies in a decentralized manner. By defining trajectory observation history(TOH) distillation and trust distillation to avoid overfitting, Fast-DRD learns a suitable offloading model in a noisy partially observed edge system and reduces the cost for communication among servers. Finally, experimental simulations are presented to evaluate and compare the effectiveness and complexity of Fast-DRD.     

Decentralized sampled-data fuzzy controller design for a VTOL UAV

This study focuses on a sampled-data fuzzy decentralized tracking control problem for a quadrotor unmanned aerial vehicle (UAV) under the variable sampling rate condition. To this end, the overall dynamics of the quadrotor is expressed as a decentralized Takagi–Sugeno (T–S) fuzzy model interconnected with each other. Although the proposed decentralized control technique divides the overall UAV control system into attitude and position subsystems, the stability of the entire control system is guaranteed. Besides, in this paper, the model uncertainty, interconnection, and reference trajectory are considered as disturbances acting on the tracking error. To attenuate these disturbances, a novel sampled-data tracking control design technique is derived based on a linear reference model to be tracked and the time-dependent Lyapunov–Krasovskii functional (LKF). By doing so, both the stability of the tracking error dynamics and the minimization of tracking performance are guaranteed. Also, the proposed tracking control design method is derived as a linear matrix inequality (LMI)-based optimal problem. Finally, a simulation example is provided to demonstrate the effectiveness and feasibility of the proposed design methodology.     

Robust stabilization of polytopic discrete-time systems with time-varying state delay: A convex approach

Convex conditions, expressed as linear matrix inequalities (LMIs), for stability analysis and robust design of uncertain discrete-time systems with time-varying delay are presented in this paper. Delay-dependent and delay-independent convex conditions are given. This paper is particularly devoted to the synthesis case where convex conditions are proposed to consider maximum allowed delay interval. It is also presented some relaxed LMIs that yield less conservative conditions at the expense of increasing the computational burden. Extensions to cope with decentralized control and output feedback control are discussed. Numerical examples, including real world motivated models, are presented to illustrate the effectiveness of the proposed approach.     

具有状态和输入时滞的不确定离散切换系统的保代价控制

针对二次型代价指标,研究了一类状态和控制输入都存在时滞的参数不确定线性离散切换系统的保代价控制问题.利用分段Lyapunov函数,在基于状态的切换规则下,给出了此类系统保代价控制律,所得到的控制律不仅能使系统闭环鲁棒渐近稳定,而且使系统的闭环代价指标在对象参数摄动的范围内不超过确定的上界.最后通过一个实例的仿真验证了设计方法的有效性.     

A sampled-data control problem of neural-network-based systems using an improved free-matrix-based inequality

In this work, a sampled-data control problem for neural-network-based systems with an optimal guaranteed cost is investigated. By constructing suitable time-dependent functionals and utilizing an improved free-matrix-based integral inequality, a sampled-data stability criterion for neural-network-based systems is derived. Based on a first result, a sampled-data controller design method for neural-network-based systems that meets the maximum sampling period and minimum guaranteed cost performance is proposed. The superiority and validity of the results will be verified by comparing with the existing results in a numerical example.     

Non-fragile guaranteed cost control for uncertain stochastic nonlinear time-delay systems

This paper deals with the problem of non-fragile guaranteed cost control for a class of uncertain stochastic nonlinear time-delay systems. The parametric uncertainties are assumed to be time-varying and norm bounded. The time-delay factors are unknown and time-varying with known bounds. The aim of this paper is to design a memoryless non-fragile state feedback control law such that the closed-loop system is stochastically asymptotically stable in the mean square for all admissible parameter uncertainties and the closed-loop cost function value is not more than a specified upper bound. A new sufficient condition for the existence of such controllers is presented based on the linear matrix inequality (LMI) approach. Then, a convex optimization problem is formulated to select the optimal guaranteed cost controller which minimizes the upper bound of the closed-loop cost function. Numerical example is given to illustrate the effectiveness of the developed techniques.     

Resilient sliding mode control for a class of cyber-physical systems with multiple transmission channels under denial-of-service attacks

This paper investigates the resilient sliding mode control problem for cyber-physical systems (CPSs) with multiple transmission channels under denial-of-service (DoS) attacks. A set of finite-time observers is designed, and a switched integral-type sliding surface is introduced. Thus, the impact of unreliable state estimating channels is reduced, and the disturbance rejection performance is also improved. The number of linear matrix inequalities (LMIs) decreases compared with some existing results in designing the observer-based controller, and the input-to-state stability (ISS) is guaranteed. Moreover, the input saturation and event-triggering scheme are considered in the controller and handled by an auxiliary system. The network congestion in the control channel is thus relieved, and the Zeno behavior is excluded simultaneously. Finally, an example of an unmanned stratospheric airship is given to demonstrate effectiveness of the proposed resilient control approach.     

Observer-based decentralized control of large-scale stochastic high-order feedforward systems with multi time delays

This paper investigates the problem of observer-based decentralized control for a class of large-scale stochastic high-order feedforward systems with multi time delays. By using the homogeneous domination idea and constructing the implementable observer, the decentralized output-feedback controller design scheme is firstly proposed. Then, with the aid of stochastic time delay system stability theory, the globally asymptotically stable in probability of the closed-loop system is verified by selecting an appropriate Lyapunov–Krasoviskii functional. Finally, an example is provided to demonstrate the efficiency of the proposed design method.     

Design of a H∞ model reference tracking control for interconnected nonlinear systems by decentralized dynamic output-feedback

This study investigates the problem of robust tracking control for interconnected nonlinear systems affected by uncertainties and external disturbances. The designed H_∞ dynamic output-feedback model reference tracking controller is parameterized in terms of linear matrix inequalities (LMIs), which is formulated within a convex optimization problem readily implementable. The resolution of such a problem, guarantying not only the quadratic stability but also a prescribed performance level of the resulting closed-loop system, enables to calculate concurrently the robust decentralized control and observation gain matrices. The established LMI conditions are computed in a single-step resolution to obtain all the controller/observer parameters and therefore to overcome the problem of iterative algorithm based on a multi-stage resolution leading in most cases to conservative and suboptimal solutions. Numerical simulations on diverse applications ranging from a numerical academic example to coupled inverted double pendulums and a 3-strongly interconnected machine power system are provided to corroborate the merit of the proposed control scheme.     

Observer-based output feedback control for networked systems with dual-channel event-triggered sampling and quantization

This paper investigates the problem of observer-based output feedback control for linear networked systems with dual-channel event-triggered mechanisms and quantization. Both continuous-time and discrete-time event detection cases are discussed. In the continuous-time case, the stability of observer error dynamics and closed-loop system are analyzed respectively, and it is proved that Zeno behavior would not occur. In order to approach engineering practice, in the discrete-time case, two types of network attacks including denial-of-service (DoS) and fault data injection (FDI) attacks are considered, whose nature property is characterized by Bernoulli variables. By combining these factors and transmission delay, a novel augmented system model is proposed, and some sufficient conditions are derived based on Lyapunov functional approach and linear matrix inequalities (LMIs). Compared with the existing results, this framework is more comprehensive and practical, and the global uniform ultimate boundedness of closed-loop systems can be guaranteed. Finally, simulation examples are given to demonstrate the effectiveness of the proposed method.