Probabilistic‐constrained filtering for a class of nonlinear systems with improved static event‐triggered communication

Summary The present work deals with the problem of static output feedback control for discrete‐time switched systems (SSs) with quantization effects. Different from the existing results on SSs, a more general model with respect to a new switching rule (SR) is explored by utilizing a nonhomogeneous sojourn probability approach. Both control input and measured output are quantized by the mode‐dependent static logarithmic quantizers, respectively. To decrease the conservatism and eliminate the coupling parameters, a descriptor technology is employed in the static output feedback control scheme. In the framework of the time‐dependent SR, sufficient conditions are proposed to guarantee the mean square stability of resulting systems. Finally, an example is expressed to demonstrate the applicability and validity of the developed theoretical results.

“…With the aid of statistical technique, the information of statistic information φ f is easy to be achieved, that is,

φ_{f} = \lim_{k \to \infty} \frac{k_{f}}{k}

, where k f is the times of ϑ k = f in the interval [1, k ]. Therefore, compared with TP method, the study of DTSSs with SP approach is a fascinating topic …”

Section: Problem Formulationmentioning

confidence: 99%

Static output feedback control of switched systems with quantization: A nonhomogeneous sojourn probability approach

Cheng

Park

Zhao

et al. 2019

“…For example, in some literature, a typical ETS is given as

t_{k + 1} = \min false{t \in double-struckR false| false(false‖ x false(t_{k} false) - x false(t false) false‖ false) \geq σ false(false‖ x false(t false) false‖ false) false}

, where x ( t ) is the current state, x ( t k ) is the last released packet, t k is the most recent released instant, t k +1 is the next released instant, and σ is a constant threshold parameter. In the past two decades, different types of triggering conditions have been explored, which can be roughly classified into several categories, such as the absolute ETS, mixed ETS, hybrid ETS, static ETS, dynamic ETS, periodic/discrete ETS, adaptive ETS, and distributed ETS . It is worth noting that, in order to avoid ZENO phenomenon, Heemels et al and Yeu et al made a trade‐off between the time‐triggered control and event‐triggered control and proposed a periodic/discrete event‐triggered control for linear systems.…”

Section: Introductionmentioning

confidence: 99%

Resilient control of networked control systems under deception attacks: A memory‐event‐triggered communication scheme

Kunyu

Tian

Liu

et al. 2019

Self Cite

179

104

Summary This paper considers resilient event‐triggered control problem for a class of networked systems subject to randomly occurring deception attacks. First, a new memory event‐triggered scheme (METS) is proposed to reduce the utilization of communication resources while maintaining desired system performance. Different from some existing event‐triggered schemes, some recently released packets are firstly utilized in the proposed METS, which provides a better flexibility to improve the system dynamics. Second, considering the security problem of the networked control systems, a randomly occurring deception attack model is employed where the bounded malicious signals are injected by the adversary. Considering both the effects of METS and deception attack, new type of networked control system model is constructed and the corresponding memory state‐feedback controller is designed. Then, sufficient conditions for the asymptotical stability of the systems are derived by using a Lyapunov functional technique. Finally, the obtained results are verified through a pendulum system, which demonstrates the effectiveness of the proposed methods.

“…For instance, in order to provide a reasonable defensive strategy in theory, from the viewpoint of the adversary, various attack policies were investigated in other works, and then, the effect of the attacks on the system control (or remote state estimation) performance was analyzed. On the other hand, attack detection and estimation strategies were developed in the works of Yang et al and Tian et al from the defender's perspective. Besides, some effective secure control policies for CPSs are developed against adversarial attacks .…”

Section: Introductionmentioning

confidence: 99%

“…Secondly, with the aid of the existing reported attack policies, [11][12][13][14]33 attack estimation methods 16,39 and typical failure types, 4 the corresponding system dynamics under the attacks can be obtained. Based on them, the system under attacks possibly changing the system dynamics and no attacks is modeled as a family of subsystems, similar to those in the switched system.…”

Section: Introductionmentioning

confidence: 99%

On modeling and secure control of cyber‐physical systems with attacks/faults changing system dynamics: An average dwell‐time approach

Huang

Dong

2019

Summary The problem of secure control in cyber‐physical systems is considered in this work. A new modeling framework is first introduced, ie, cyber‐physical systems with attacks/faults changing system dynamics is modeled as a switched system, where the switching among subsystems is triggered by a rule generated by attackers but unknown for defenders. Based on an average dwell‐time approach incorporated by the attack frequency and duration properties, a convergence condition of the Lyapunov function on active intervals of subsystems (ie, the attack and healthy modes), under the developed switched controller, is given. Next, the unknown rule, however, leads to the asynchronous switching problem between the candidate controllers and system modes. As a result, degradation of the system performance (eg, a large chatter occurred in the system state trajectories) in the asynchronous intervals is caused. To address the difficulty, a novel switching law based on a prescribed performance is proposed, and it is shown that the asynchronous intervals are shortened by reducing adjustable parameters in the switching law. An illustrative example verifies the effectiveness of the proposed method.