Class Of Nonlinear Networked Systems Research Articles

Observer-Based Security Fuzzy Control for Nonlinear Networked Systems Under Weighted Try-Once-Discard Protocol

This paper is concerned with the observer-based security fuzzy control problem for a class of nonlinear networked systems with imperfectly matched membership functions (MFs) under weighted try-once-discard (WTOD) protocol. The nonlinear networked system is constructed based on interval type-2 (IT2) Takagi-Sugeno (T-S) model, which can properly handle parameter uncertainties via lower and upper MFs. To mitigate the communication load, WTOD protocol is exploited to schedule the transmission order of the signals, in which those signals may be subjected to randomly occurring deception attacks. The observer is constructed under unmeasurable premise variables, and then the controller with imperfect matching MFs is designed according to the estimated states. Moreover, the observer-based controller is derived with Lyapunov stability theory such that the stochastic stability of the augmented closed-loop system with predefined disturbance attenuation performance can be guaranteed. Subsequently, sufficient conditions are provided for the desired observer and controller gain matrices based on linear matrix inequalities (LMIs) technique. Numerical simulation example demonstrates the validity of the proposed observer-based security fuzzy control design scheme.

Neural-Network-Based Secure State Estimation Under Energy-Constrained Denial-of-Service Attacks: An Encoding-Decoding Scheme

This paper is concerned with the secure state estimation issue for a class of networked nonlinear systems under energy-constrained denial-of-service (EC-DoS) cyber-attacks and encoding-decoding scheme (EDS). The information transmissions between sensors and the estimator are executed via a bandwidth-limited communication network, on which the EDS is deployed to convert transmitted signals into finite-length codewords for the purpose of improving transmission efficiency. The EC-DoS attacks, whose intention is to jeopardize the network-based signal transmissions by overloading the communication resource, are assumed to occur in an intermittent way with bounded occurrence frequency/durations owing to the inherent energy constraints on the attackers. Considering the worst case of such EC-DoS attacks, a neural-network (NN)-based state estimator is constructed to generate the desired state estimates for the underlying networked nonlinear system. By employing the Lyapunov stability theory, the estimation error dynamics of the system state and the neural-network weight are jointly analyzed within a unified framework. Subsequently, sufficient conditions are obtained for the existence of the desired NN-based state estimator, and then both the desired estimator gain matrix and the NN tuning parameters are characterized. Finally, the validity of our estimation approach is confirmed by an example.

Observer-based quantised control of networked systems with round-robin protocol and transmission delay

This paper addresses the ultimate boundedness control problem for a class of networked nonlinear systems with the round-robin (RR) protocol and uniform quantisation. The communication between sensor nodes and the controller is implemented via a constrained communication channel. The quantised output of the system is transmitted to the remote controller through a communication channel subject to a transmission delay. For the purpose of alleviating possible data collision, the well-known RR communication protocol is deployed to schedule the data transmissions. On the other hand, the uniform quantisation effects of the network are characterised by a round function (i.e. the nearest integer function). The purpose of the addressed problem is to design an observer-based controller for the networked nonlinear systems such that, in the presence of RR protocol and uniform quantisation effects, the closed-loop system is ultimately bounded. The controller is designed based on mean square stability analysis and Lyapunov-like method. A set of sufficient conditions for the ultimate boundedness of the closed-loop system are established and, on the basis of which, the desired controller gains are obtained by solving a set of linear matrix inequalities. The effectiveness of the proposed method is verified by numerical examples.

Learning-Based Event-Triggered Tracking Control for Nonlinear Networked Control Systems With Unmatched Disturbance

This article concentrates on optimal tracking control for a class of nonlinear networked systems subjecting to limited network bandwidth and unmatched disturbance. Given the models of the control and reference systems, the considered optimal tracking control issue is initially formulated as a minimax optimization problem. Then, with the introduction of an event-triggered mechanism used for saving bandwidth, the formulated problem is transformed into solving an event-based Hamilton-Jacobi-Isaacs (HJI) equation by recurring to the Bellman optimality theory. Based on the HJI equation, we demonstrate that the stability of the concerned system in the sense of uniformly ultimately bounded (UUB) can be guaranteed with the envisioned optimal control and worst disturbance policies. Here, the disturbance policy can be varied periodically while the control policy can only be updated at event-triggering instants, which differs from the existed researches. Furthermore, we propose a reinforcement learning (RL)-based algorithm to handle the constructed HJI equation and thus settle the studied tracking control problem. The effectiveness of the algorithm is finally validated by both theoretical analysis and simulations.

Design of Observer and Dynamic Output Feedback Control for Fuzzy Networked Systems

The observer design and dynamic output feedback control for a class of nonlinear networked systems are studied in this paper. The model of the networked systems is established by using T-S fuzzy method, and the state observer of the systems is designed when the states of the systems are unknown. On this basis, the sufficient conditions for the exponential stability of the system are explored by using the linear matrix inequality (LMI) method and Lyapunov stability theory. Then, the dynamic output feedback control of the systems is designed by using the observer states, which ensures that the states of the closed-loop systems and the error systems exponentially converge to the origin at the same time. Finally, a simulation example is given to illustrate the feasibility and effectiveness of the design method.

Robust adaptive control for a class of networked nonlinear systems under denial-of-service attacks

Robust adaptive control for a class of networked nonlinear systems under denial-of-service attacks

Comparison of Three Data-Driven Networked Predictive Control Methods for a Class of Nonlinear Systems

Dear Editor, In this letter, in order to deal with random network delays and packet losses in a class of networked nonlinear systems, three data-driven networked predictive control methods are designed. Their closed-loop systems and control increments are derived, respectively. Although the expressions of their control increments are obviously different, they are similar in form and composition, which are helpful to evaluate the effects of control actions. A comparison of the control performance of the three methods is carried out by a simulation example so as to show their advantages and disadvantages.

Neighborhood‐based distributed robust unknown input observer for fault estimation in nonlinear networked systems

In this paper, a robust distributed fault estimation is addressed for a class of nonlinear networked systems with actuator faults where influences from process disturbances are minimized. In real-time monitoring systems, a substantial challenge is to find out the size and the shape of the occurred faults, and consequently, it is significantly more difficult in multi-agent systems. To consider this concern, in this paper, a distributed fault estimation approach has been proposed for multi-agent systems such that each agent employs an augmented system owing to a designated communication graph for estimating the fault and states both in this agent and in its neighbors. Meanwhile, each agent is equipped with an unknown input observer (UIO) to decouple the partial disturbances of the process as much as possible and to reduce the disturbances that cannot be decoupled. In the form of linear matrix inequalities (LMIs), sufficient conditions are provided to guarantee stability and to obtain the parameter matrices of the introduced observer. Finally, two numerical examples are provided to verify the performance of the introduced fault estimation scheme.

Adaptive event‐triggered fault detection for nonlinear networked systems in finite‐frequency domain under stochastic cyber‐attacks

SummaryThis article investigates the fault detection problem in finite‐frequency domain for a class of nonlinear networked systems under stochastic cyber‐attacks. A novel adaptive event‐triggered scheme is introduced to mitigate the transmission burden of the network. A unified measurement model is proposed to take the randomly occurring cyber‐attacks and the transmission delays into account simultaneously. Under the consideration of fault sensitivity and disturbance robustness, the addressed fault detection problem is converted into an auxiliary filtering problem by properly augmenting the states of the original system and the fault detection filter. Intensive stochastic analysis is carried out to obtain sufficient conditions for the existence of the desired fault detection filter, and the corresponding optimal filter parameters can be easily derived by solving a convex optimization problem. Finally, an illustrative example is presented to show the effectiveness and applicability of the proposed method.

A new result on semi-synchronous event-triggered backstepping robust control for a class of non-Lipschitzian networked systems

The paper investigates the backstepping robust control problem for a class of nonlinear networked systems. The non-Lipschitz conditions of linear growth condition and Hölder condition are considered in the time-varying disturbance and uncertainty. An important innovation is that the virtual controller is designed to be piecewise constant such that the usage of the command filter is avoided. In the process of designing the robust controller, a semi-synchronous event-triggered scheme is proposed to relieve the communication pressure in high-order systems. Thus, a switched controller without using average dwell time (ADT) is considered. The finite-time practical stability with the form of fast terminal sliding mode (TSM) is also obtained. Then, the Zeno behavior is excluded and a self-triggered scheme is further proposed to avoid the continuous monitoring of the event-triggered conditions. Compared with some existing command-filtered results, the design process is simplified and more suitable for networked systems. The effectiveness of the proposed theory is validated by the numerical simulation of a hypersonic vehicle.

A Distributed Fault Estimation Approach for a Class of Continuous-Time Nonlinear Networked Systems Subject to Communication Delays

In this study, the problem of the fault estimation controller design is investigated for a class of nonlinear networked systems over a communication topology. In real systems, due to unreliable communication channels, data may be delayed or lost when it is exchanged between an agent and its neighbors. To explore this concern, in the addressed approach, each agent utilizes an augmented system based on a given communication topology for estimating the fault and the states, both within itself and in its neighbors, where information from neighbors is received with a time delay. Delay-dependent conditions in the form of linear matrix inequities (LMIs) are derived to guarantee the stability and to obtain the parameter matrices of the observer. Eventually, the simulation results are included to illustrate the performance of the addressed fault estimation approach.

The Design of a Class of Nonlinear Networked System

A class of nonlinear networked systems with external interference is designed in this paper. Currently, we have witnessed that networked control technology has played a key role in the Internet of Things (IoT). However, the amount of big data in the Internet of Things will cause network congestion in the data transmission of the network control system. In order to solve this problem, event-driven control scheme can effectively save the network resources of the network control system. But when there is interference in the system, the conventional constant threshold parameter is difficult to achieve the expected energy-saving effect. In order to solve this challenge, this paper proposes a design with a continuously variable threshold. After each trigger to transmit data, the threshold gets changed accordingly, and the sliding mode approach rate is changed simultaneously. Compared with the constant threshold event drive, the number of transmissions in this design can be greatly reduced, while sliding mode jitter is suppressed. The simulation results show that the scheme can achieve higher resource utilization efficiency and better robustness.

Attack-Resilient Event-Triggered Fuzzy Interval Type-2 Filter Design for Networked Nonlinear Systems Under Sporadic Denial-of-Service Jamming Attacks

This article is concerned with attack-resilient event-triggered <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"><tex-math notation="LaTeX">$H_{\infty }$</tex-math></inline-formula> filtering for a class of networked nonlinear systems described by an interval type-2 (IT2) fuzzy model. Suppose that data transmission from the plant to the filter is completed through a wireless sensor network subject to denial-of-service attacks (DoS). In order to save the limited network bandwidth and resist the effects of DoS attacks, a resilient event-triggered communication scheme is devised. Then, an attack-resilient IT2 filter model is introduced to estimate system states of the nonlinear plant. Based on a piecewise Lyapunov–Krasovskii functional, sufficient conditions are obtained to ensure that the filtering error system is exponentially stable and satisfies a certain <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"><tex-math notation="LaTeX">$H_{\infty }$</tex-math></inline-formula> performance level. Moreover, explicit expressions for the attack-resilient filter gain parameters and event-triggering parameters can be derived if a set of linear matrix inequalities are feasible. Finally, a practical example is provided to demonstrate the effectiveness of the proposed theoretical results.

Event‐triggered dynamic output feedback control for networked nonlinear systems

SummaryIn this article, the problem of event‐triggered dynamic output feedback control is investigated for a class of networked nonlinear systems with mixed delays and packet dropouts. By applying the cone complementary linearization technique, sufficient conditions are developed such that the resulting closed‐loop system dynamics is mean square asymptotically stable with a desired performance level. The effectiveness of the proposed method is demonstrated via an illustrative example.

Fuzzy Peak-to-Peak Filtering for Networked Nonlinear Systems With Multipath Data Packet Dropouts

In this paper, the peak-to-peak filtering problem is studied for a class of networked nonlinear systems. The nonlinear physical plant is represented by the Takagi–Sugeno fuzzy system. Assume that the data packet dropout phenomenon occurs when the measurement output signal and the performance output signal of the nonlinear systems are transmitted by the digital communication channel. Two stochastic variables satisfying the Bernoulli random binary distribution are used to model this phenomenon. The motive of this paper is to design a peak-to-peak filter such that the filtering error system is stochastically stable and the prescribed peak-to-peak performance index is guaranteed. The developed theoretical results for designing a peak-to-peak filter are expressed in the form of linear matrix inequalities. Finally, a simulation example is presented to illustrate the validity of theoretical analysis.

Adaptive Fuzzy Predictive Controller for a Class of Networked Nonlinear Systems With Time-Varying Delay

In this paper, an adaptive fuzzy predictive controller (AFPC) is designed and analyzed for a class of networked nonlinear systems with time-varying communication delay. The integration of the communication network in the control loops makes the nonlinear system has forward and feedback time-varying delays. The proposed controller compensates the network-induced delays in the forward and feedback channels. The structure of the AFPC consists of adaptive fuzzy logic control (AFLC) with state predictor located at the controlled plant and a remote adaptive smith predictive controller at the master node. The AFLC and the state predictor are utilized to identify the dynamic of the time-varying delay-free nonlinear plant in order to cancel the nonlinear term for the nonlinear control system in a canonical form. In the remote controller, adaptive smith predictor is employed to compensate the time-varying delay effect to achieve the desired tracking performance. Based on the Lyapunov theory, the stability of the closed-loop system is guaranteed in the presence of bounded external disturbance and time-varying delays. Simulated application of Van der Pol oscillator is provided to demonstrate the feasibility and effectiveness of the proposed scheme based on TrueTime toolbox.

Fault detection for a class of nonlinear networked systems under adaptive event-triggered scheme with randomly occurring nonlinear perturbations

The problem of fault detection for a class of nonlinear systems with randomly occurring nonlinear perturbations under the adaptive event-triggered scheme is investigated. The phenomena of randomly occurring nonlinear perturbations are modelled as a stochastic variable satisfying a certain probability distribution. An adaptive event-triggered scheme is developed to further reduce the data transmission over the network and reduce the utilisation ratio of network resources. A full-order fault detection filter is constructed. By augmenting the states of the original system and the fault detection filter, the problem of fault detection is transformed into an auxiliary filtering for a time delay system. Sufficient conditions for the existence of the designed fault detection filter are obtained in terms of a group of linear matrix inequalities. Finally, two examples are given to illustrate the effectiveness of the proposed method.

Finite-time control for fuzzy networked systems with state delay and network-induced delay

To investigate the finite-time stabilisation control problem for a class of nonlinear networked systems, a T-S fuzzy model is employed to represent the nonlinear controlled plant with state delay and time varying network induced delay. Based on the Lyapunov stability theory and linear matrix inequality (LMI) approach, a finite-time stabilisation sufficient condition is obtained. Then, a state feedback fuzzy controller which can make the network systems finite-time stable (FTS) is designed. Finally, a numerical example is given to demonstrate the application and effectiveness of the proposed method.

Finite-time control for fuzzy networked systems with state delay and network-induced delay

To investigate the finite-time stabilisation control problem for a class of nonlinear networked systems, a T-S fuzzy model is employed to represent the nonlinear controlled plant with state delay and time varying network induced delay. Based on the Lyapunov stability theory and linear matrix inequality (LMI) approach, a finite-time stabilisation sufficient condition is obtained. Then, a state feedback fuzzy controller which can make the network systems finite-time stable (FTS) is designed. Finally, a numerical example is given to demonstrate the application and effectiveness of the proposed method.

Particle filtering for networked nonlinear systems subject to random one-step sensor delay and missing measurements

Abstract In this paper, the particle filtering problem is investigated for a class of networked nonlinear systems with random one-step sensor delay and missing measurements. The phenomena of missing measurements and random one-step sensor delay are modeled by two random variables, both obeying the Bernoulli distribution. Here, we derive an explicit expression for the likelihood function when the possible occurrence of one-step sensor delay and measurement loss is taken into consideration. Based on this likelihood function, we propose a novel particle filtering algorithm to treat the nonlinear estimation problem in the simultaneous presence of random sensor delay and measurement loss. Finally, a simulation example is given to illustrate the feasibility and advantages of the proposed filtering scheme compared with traditional particle filtering algorithm.