Fuzzy Network Control System Research Articles

Attack-Dependent Adaptive Event-Triggered Security Fuzzy Control for Nonlinear Networked Cascade Control Systems Under Deception Attacks

This article investigates the issue of H∞ security output feedback control for a nonlinear networked cascade control system with deception attacks. First, to further reduce the amount of communication data, reasonably schedule network resources, and alleviate the impact of multi-channel deception attacks, an attack-dependent adaptive event-triggered mechanism is introduced into the primary network channel, and its adaptive triggered threshold can be adjusted according to the random attack probability. Secondly, the output dynamic quantization of the secondary network channel is considered. Then, a novel security cascade output feedback controller design framework based on the Takagi–Sugeno (T-S) fuzzy networked cascade control system under deception attacks is established. In addition, by introducing the Lyapunov–Krasovskii stability theory, the design conditions of the controller are given. Finally, the effectiveness and superiority of the proposed design strategies are verified by two simulation examples of power plant boiler–turbine system and power plant boiler power generation control system.

Observer-Based Quantized Guaranteed Cost Control of Fuzzy Networked Control Systems With Unreliable Links and Its Applications

Observer-Based Quantized Guaranteed Cost Control of Fuzzy Networked Control Systems With Unreliable Links and Its Applications

[formula omitted] control of uncertain T–S fuzzy networked control systems with actuator faults under stochastic packet loss-dependent event-triggered schemes

In this paper, the H∞ control problem of uncertain T–S fuzzy networked control systems (NCSs) with actuator faults under stochastic packet loss-dependent event-triggered schemes (SPDETS) is investigated. First, in order to improve the efficiency of communication networks, an innovative SPDETS is proposed, which relies on stochastic packet losses during data transmission and event-triggered conditions. Second, a packet loss-dependent switching-like controller is designed to maintain the control performance of the system. Third, some potential actuator faults are taken into account, besides considering system uncertainty and network-induced delay. Using the Lyapunov–Krasovskii theorem, sufficient conditions to guarantee the system stability for a specified performance index are presented, and design conditions are given for a switching-like fault-tolerant controller that compensates for the actuator efficiency loss. Finally, the effectiveness of the proposed control scheme is verified through the CSTR simulation example.

Stability Analysis and Event-Triggered Control for IT2 Discrete-Time Positive Polynomial Fuzzy Networked Control Systems With Time Delay

Stability Analysis and Event-Triggered Control for IT2 Discrete-Time Positive Polynomial Fuzzy Networked Control Systems With Time Delay

Finite-Time Resilient Filtering for Discrete-Time T-S Fuzzy Networked Control Systems with Switching Communication Channels under Cyber Attacks

Finite-Time Resilient Filtering for Discrete-Time T-S Fuzzy Networked Control Systems with Switching Communication Channels under Cyber Attacks

Stabilization of Interval Type-2 Polynomial Fuzzy Networked Control Systems under Cyber-Attacks

Stabilization of Interval Type-2 Polynomial Fuzzy Networked Control Systems under Cyber-Attacks

Design of Anti-disturbance Reliable Control for Fuzzy Networked Control Systems with Multiple Disturbances

Design of Anti-disturbance Reliable Control for Fuzzy Networked Control Systems with Multiple Disturbances

Reliable Sampling Mechanism for Takagi–Sugeno Fuzzy NCSs Under Deception Cyberattacks for the Application of the Inverted Pendulum System

This article investigates the stability problem of Takagi–Sugeno fuzzy networked control systems (TSNCSs) under deception cyberattacks via a reliable sampling mechanism, which has important research value for applications in network security. First, a fuzzy weight functional method is introduced, and a new Lyapunov–Krasovskii functional is developed, which better incorporates nonlinear problems in the model. Then, in order to reduce the initial constraints, improved time delay closed-loop functions are constructed that consider the delay information and the characteristics of the sampling time points. Furthermore, considering the reliability issues of controllers in real industry, we establish some sufficient conditions and implement a novel reliable sampling controller with deception attacks (DAs) to control the asymptotic stability of TSNCS. Finally, the correctness and feasibility of the proposed method are verified experimentally using an inverted pendulum system.

Performance Error Estimation and Elastic Integral Event Triggering Mechanism Design for T–S Fuzzy Networked Control System Under DoS Attacks

This article analyzes the mechanism of denial-of-service (DoS) attacks initiated by hackers from the perspective of computer networks. In order to effectively estimate the performance error generated by the T–S fuzzy networked control systems under DoS attacks, we transform the performance error estimation problem into the one of finding ellipsoid constraints <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"><tex-math notation="LaTeX">$\mathfrak {J}(P_{i})$</tex-math></inline-formula> . First, improved Lyapunov–Krasovskii functions (LKFs) based on fuzzy membership functions are constructed, which combine the characteristics of nonlinear problems in the system to reduce the initial constraints. Then, a second-order weight method (SOWM) is introduced to divide the time interval of sampling meticulously. Besides, the information stored in the LKFs is enhanced. Furthermore, we construct the novel looped functions by relying on the SOWM. Next, a suitable integral elastic event trigger mechanism is established to ensure that the performance errors caused by the attacks are estimated. Finally, the feasibility of the proposed method is verified by a two-degree-of-freedom helicopter system.

An Extended Dissipative Analysis of Fractional-Order Fuzzy Networked Control Systems

This study presents an extended dissipative analysis of fractional order fuzzy networked control system with uncertain parameters. First, we designed the network-based fuzzy controller for the considered model. Second, a novel Lyapunov-Krasovskii functional (LKF) approach, inequality techniques, and some sufficient conditions are established, which make the proposed system quadratically stable under the extended dissipative criteria. Subsequently, the resultant conditions are expressed with respect to linear matrix inequalities (LMIs). Meanwhile, the corresponding controller gains are designed under the larger sampling interval. Finally, two numerical examples are presented to illustrate the viability of the obtained criteria.

Quantized Sampled-Data Control Tactic for T-S Fuzzy NCS Under Stochastic Cyber-Attacks and Its Application to Truck-Trailer System

This work focuses on the dissipative analysis and quantized sampled-data control design issues for T-S fuzzy networked control system (TSFNCS) under stochastic cyber-attacks (SCAs), which have strong application backgrounds and significant theoretical research value in the field of network security. For this work, a novel time-delay-product relaxed condition (TDPRC) is introduced, which can obtain the slack constraints based on the delay information. Then, by fully considering the delay and sampling time point information, an improved boundary looped-functional (BLF) is developed to acquire more information on the Lyapunov-Krasovskii functional (LKF). In addition, based on the relationship between the sampling moments <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"><tex-math notation="LaTeX">$(t_{k+1}-t)\eta ^{T}_{3}(t)$</tex-math></inline-formula> and <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"><tex-math notation="LaTeX">$(t-t_{k})\eta ^{T}_{4}(t)$</tex-math></inline-formula> in <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"><tex-math notation="LaTeX">$V_{c}(x_{t})$</tex-math></inline-formula> , the obtained constraints may be further relaxed. Next, a new criterion and the corresponding algorithm are established using reciprocally convex matrix inequality (RCMI), proper integral inequalities, and the linear convex combination method (LCCM). In addition, a new quantitative sample data (QSD) controller under SCA is designed to ensure that TSFNCS is asymptotically stable (AS) and dissipative. Finally, the experiment of the truck-trailer system (TTS) dynamics equations proves the correctness of the theory proposed in this paper.

On designing the hybrid-triggered dynamic output feedback guaranteed cost control for uncertain T-S fuzzy networked control systems with cyber attack and actuator saturation

In this paper, we study the hybrid-triggered dynamic output feedback-based guaranteed cost control issue for uncertain Takagi-Sugeno (T-S) fuzzy networked control systems (NCSs) with cyber attack and actuator saturation. The hybrid-triggered mechanism comprising of time-triggered mechanism (TTM) and event-triggered mechanism (ETM) is provided to adjust the trigger strategy due to the variety in network resource utilization. Both the switching between two trigger mechanisms and the cyber attack phenomenon in communication network are respectively represented by two Bernoulli distributions. The data quantization is characterized by the sector bound technique and actuator saturation is addressed by invoking an auxiliary matrix. The stability of closed-loop NCSs with bounded disturbance and cyber attack is expressed by the methodology of quadratic boundedness (QB). The existence criteria and design strategies for minimizing the upper bound of performance in view of dynamic output feedback controller are constructed for any admissible uncertainties. Subsequently, in the light of the cone complementarity linearization (CCL) algorithm, the controller design issue is cast into the convex optimization issue which is capable of solving by the technique about linear matrix inequalities (LMIs). Finally, simulation example is employed to demonstrate the validity of designed controller.

Voluntary defense strategy and quantized sample-data control for T-S fuzzy networked control systems with stochastic cyber-attacks and its application

This work studies mainly the dissipative analysis issue of T-S fuzzy networked control systems (NCSs) with stochastic cyber-attacks (SCAs) and voluntary defense strategy (VDS), which has strong application background in the network information security field. Firstly, a novel time-delay-product relaxed condition (TDPRC) is introduced, which fully excavates time-varying delay (TVD) information in the established condition. Secondly, an improved boundary circulatory function (BLF) is developRed, which takes advantage of the characteristics of the sampling moments. Here, when t∈[tk,tk+1), we only require Qd(t) to be an asymmetric matrix in Vc(x(t)). Then, a novel criterion and the corresponding control algorithm are developed by using reciprocally convex matrix inequality (RCMI), proper integral inequalities, and the linear convex combination method (LCCM). Furthermore, a new quantized sample-data and VDS controller under SCAs is established, which can prove that T-S fuzzy NCSs under a better dissipative index are asymptotically stable (AS). Lastly, a numerical simulation of the dynamic equation of truck-trailer system to certify the theory’s feasibility and validity.

Research on Optimization of Fuzzy Network Control System Based on New Smith Predictive Time Delay Compensation

Aiming at the problem of network delay when the network control system transmits data, this paper adopts a new type of fuzzy control method of Smith predictor to compensate for the delay. In actual application scenarios, it is difficult to accurately match the Smith prediction model with the actual model. At the same time, the quantization factor and scale factor in the fuzzy PID controller are too dependent on experience, which makes the system’s adaptability to actual working conditions very poor. In this paper, genetic algorithm is used to optimizes fuzzy PID. According to the simulation results, when the Smith predictive model does not match the actual model, the steady-state performance and dynamic performance of the system under the fuzzy PID control optimized by the genetic algorithm are improved.

Event-Driven Fault Detection for Discrete-Time Interval Type-2 Fuzzy Systems

This article considers the event-driven fault detection (FD) problem for discrete-time interval type-2 (IT2) fuzzy networked control systems (NCSs) with nonlinear perturbations. To reduce signal transmission, an event-driven mechanism in the NCSs is introduced. A novel FD fuzzy filter is designed for generating a residual signal and detecting actuator faults by considering the event-driven strategy, nonlinear perturbations, communication delay, and mismatched membership functions. It is shown that the proposed event-driven FD technique is effective to optimize performance compared with the existing FD strategy. Finally, two examples are presented to verify the advantages of the novel design technique.

H∞ tracking control of two‐dimensional fuzzy networked systems

SummaryIn this article, the H∞ tracking control problem is first considered for two‐dimensional fuzzy networked control systems. The system is described by fuzzy blending of the so‐called second Fornasini‐Marchesini local linear state‐space model. Based on the fuzzy model, an observer‐based state feedback controller is employed to guarantee the H∞ tracking performance. The separation property is established in the case of observer‐based H∞ tracking control framework, that is, the controller gains and observer gains can be simultaneously obtained by solving two sets of linear matrix inequalities. A simulation example is given to illustrate the effectiveness of the proposed method.

Fault-tolerant H∞ filtering for fuzzy networked control systems with quantisation effects

ABSTRACTThe issue of memory filter design is investigated for a class of discrete-time Takagi–Sugeno (T-S) fuzzy networked control systems with time-varying delay and quantisation effects. The main objective of this paper is to formulate an memory filter that can guarantee the resulting filtering error system to be finite-time bounded. Further, by considering the communication limitations, the state signals are quantised before transmission through a logarithmic quantiser and the quantisation error is considered in the filter design. In particular, the quantisation effects are dealt by employing the generalised sector bound approach. Based on Lyapunov stability theory, novel sufficient constraints are established in the form of linear matrix inequalities, to ensure the finite-time boundedness of the augmented filtering error system. Then, a new fault-tolerant memory filter is formulated and also the filter gain parameters are attained by solving the derived LMI based constraints. Finally, a numerical example is furnished to support the efficacy and applicability of the developed filter design.

Dissipative-based non-fragile filtering for fuzzy networked control systems with switching communication channels

The problem of finite-time dissipative-based non-fragile filter design for a class of discrete-time nonlinear networked control systems subject to randomly occurring parameter uncertainties, external disturbances as well as packet dropouts due to unreliable communication channels and networked induced time-varying delay is discussed. The randomly occurring uncertainties are assumed to satisfy Bernoulli distribution and the considered stochastic variables are mutually independent. Multiple communication channel scenario is taken into account to enhance the data transmission performance and the channel switching phenomena is governed by a Markov chain. The intention here is to design a dissipative-based non-fragile filter for the filtering error system such that it is stochastically finite-time bounded and attains a prescribed dissipative performance attenuation level. Lyapunov stability theory and linear matrix inequality approach are exploited to develop a set of sufficient criterion for the existence of the desired filter. Finally, the filter design framework is applied to the truck-trailer model to demonstrate its effectiveness.

Non-Fragile Robust H∞ Filtering of Takagi-Sugeno Fuzzy Networked Control Systems with Sensor Failures.

The fault-tolerant robust non-fragile H∞ filtering problem for networked control systems with sensor failures is studied in this paper. The Takagi-Sugeno fuzzy model which can appropriate any nonlinear systems is employed. Based on the model, a filter which can maintain stability and H∞ performance level under the influence of gain perturbation of the filter and sensor failures is designed. Moreover, the gain matrix of sensor failures is converted into a dynamic interval to expand the range of allowed failures. And the sufficient condition for the existence of the desired filter is derived in terms of linear matrix inequalities (LMIs) solutions. Finally a simulation example is given to illustrate the effectiveness of the proposed method.

Dynamic Output Feedback Control Based on Descriptor Redundancy Approach for Networked Control Systems With Multiple Mixed Time-Varying Delays and Unmatched Disturbances

This paper studies the dynamic output feedback control for a class of nonlinear uncertain Takagi–Sugeno (T–S) fuzzy networked control systems with multiple mixed time-varying delays and unmatched disturbances. The T–S fuzzy model is employed to approximate the nonlinear uncertain networked control system. The dynamic output feedback controller is constructed based on the T–S fuzzy model and descriptor redundancy approach. The nonquadratic stability conditions in the form of linear matrix inequalities (LMIs) are derived by introducing the descriptor redundancy approach and nonquadratic fuzzy Lyapunov functional, such that the solutions of the closed-loop system converge to an adjustable bounded region. Then, the control design conditions are relaxed and design flexibility is enhanced. By introducing the descriptor redundancy approach and nonquadratic fuzzy Lyapunov functional, the numerous crossing terms in the LMIs are avoided in the control system design. Finally, two simulation examples are performed to show the effectiveness of the proposed methods.