Networked Takagi-Sugeno Fuzzy Systems Research Articles

Resilient Event-Triggered Dynamic Output Feedback Control for Networked Takagi–Sugeno Fuzzy Systems Under Denial-of-Service Attacks

Resilient Event-Triggered Dynamic Output Feedback Control for Networked Takagi–Sugeno Fuzzy Systems Under Denial-of-Service Attacks

Observer-based control for networked Takagi-Sugeno fuzzy systems with stochastic packet losses

This paper addressed the observer-based control problem for Takagi-Sugeno (T-S) fuzzy systems with stochastic packet losses. More specifically, an sampled-data (SD) control technique is introduced to reduce the burden of the limited bandwidth of the network, a general consecutive packet loss model is used to represent the stochastic packet loss behavior between sensor-to-controller and controller-to-actuator, and an observer scheme based on received SD output information is used to obtain the estimated system states. Based on the above scenarios, an exact discrete-time model approach is developed for stabilizing networked T-S fuzzy systems. First, the considered system with the observer-based control scheme is transformed into its discrete-time model such that subsequent analysis will be carried out in the discrete-time domain. On this basis, stability criteria are derived by fully considering the probability distribution of consecutive packet losses. Furthermore, an observer-based controller is designed by introducing some auxiliary matrices. Finally, the correctness and practicability of the designed controller is demonstrated by a mass-spring-damper system.

Quantized filtering for networked Takagi–Sugeno fuzzy systems with multipath data packet dropouts

This paper concerns the mixed and passivity‐based filtering problem for networked nonlinear systems with randomly occurring parameter uncertainties, multipath data packet dropouts, time‐varying delay, and quantization effects. The discrete‐time nonlinear plant considered in this paper is modeled as a Takagi–Sugeno fuzzy system with plant rules. The data missing phenomenon is considered in both measurement and performance output signals due to the unreliable nature of communication links. Further, to reduce the network bandwidth utilization, the measurement quantization is also employed for both the outputs before transmitting through the communication channel. Also, additive filter gain fluctuation is taken into account to reflect the imprecision in filter implementation. Stochastic variables obeying the Bernoulli distribution are incorporated in the model description to characterize the random occurrence of parameter uncertainties and data packet dropouts. A set of sufficient conditions assuring the stochastic stability of the filtering error system with mixed and passivity performance is derived according to Lyapunov stability theory. Finally, three numerical examples including mass–spring–damper and tunnel diode circuit model are established to establish the validity of the developed filter design algorithm.

Robust guaranteed cost control of networked Takagi–Sugeno fuzzy systems with local nonlinear parts and multiple quantizations

This paper researches the robust guaranteed cost (GC) control problem for a class of networked Takagi–Sugeno (T-S) fuzzy systems with local nonlinear segments and multiple quantizations, where the multiple quantizations mean that both the control input and the state are quantized through diverse dynamic quantizers. Three aspects are taken into account to perform the present study in depth. Firstly, the multiple quantizations case is investigated. Second, a novel cost function is exploited to perform the GC analysis issue, which consists of the quantized state and quantized control input. At last, a new control scheme is developed to fulfill the design of GC controller, where an additional nonlinear term is also employed besides the quantized state. By introducing auxiliary scalars and matrices, new conditions with regard to designing the dynamic quantizers and robust GC controllers are derived, which are expressed as a set of linear matrix inequalities (LMIs). Finally, a practical example is provided to verify the effectiveness of the obtained results.

Observer-based defense control for networked Takagi-Sugeno fuzzy systems against asynchronous DoS attacks

This article investigates the defense control problem for sampled-data Takagi-Sugeno (T-S) fuzzy systems with multiple transmission channels against asynchronous denial-of-service (DoS) attacks. Firstly, a new switching security control method is proposed to tolerate the asynchronous DoS attacks that act independently on each channel. Then, based on switching strategy, the resulting augmented sampled-data system can be converted into new switched systems including several stable subsystems and one open-loop subsystem. Besides, by applying the piecewise Lyapunov-Krasovskii (L-K) function method, membership functions (MFs) dependent sufficient conditions are derived to ensure the exponential stability of newly constructed switching systems. Moreover, quantitative relations among the sampling period, the exponential decay rate, and the rate of all channels being fully attacked and not being completely attacked are established. Finally, simulation examples show the effectiveness of the developed defense control approach.

Hybrid‐triggered fault detection filter design for networked Takagi–Sugeno fuzzy systems subject to persistent heavy noise disturbance

SummaryIn the network environment, the single time‐triggered scheme wastes limited bandwidth resources due to all the sampled data are transmitted to the networks, and the single event‐triggered scheme may increase system error because of ignoring factors such as changes in network utilization. To reduce the design conservatism, this paper is concerned with the hybrid‐triggered L1 fault detection filter design for a class of nonlinear networked control systems (NCSs) described by Takagi–Sugeno (T‐S) fuzzy model. Taking the effects of time‐triggered scheme and event‐triggered scheme into consideration simultaneously, we construct a fuzzy fault detection system. New results on stability and L1 performance are proposed for fuzzy fault detection system by exploiting the Lyapunov–Krasovskii functional and by means of the integral inequality method. Specially, attention is focused on the design of fault detection filter that guarantees a prescribed L1 noise attenuation level . Finally, two examples are presented to demonstrate the effectiveness of the proposed method.

Practical Stabilization of Networked Takagi-Sugeno Fuzzy Systems via Improved Jensen Inequalities.

This work addresses the problem of aperiodically sampled control for the networked Takagi-Sugeno (T-S) fuzzy systems, where the aperiodically sampled input is generated by a periodic sampler and an event-triggered mechanism (ETM). The purpose of ETM is used to reduce the computational and communication burdens. For guaranteeing controller robustness, the practical stability of T-S fuzzy systems is considered by using the Lyapunov method and linear matrix inequality (LMI) technique. As one of the most powerful inequalities for deriving stability criteria using LMIs, Jensen's inequality has recently been improved by various authors for the stability analysis of delayed systems. However, these results are conservative to obtain lower bounds for integrals with an exponential term. Inspired by this, improved integral inequalities are derived in this work, and they are applied to obtain practical stability criteria for aperiodically sampled control. Finally, a numerical example on flight control of a helicopter is given to illustrate the effectiveness of the obtained practical stability criteria. Furthermore, the effectiveness of the improved Jensen inequalities on the exponential stability criteria is illustrated by numerical comparisons.

Event‐triggered H ∞ filtering for networked Takagi–Sugeno fuzzy systems with asynchronous constraints

This paper addresses event-triggered H ∞ filtering for networked Takagi-Sugeno fuzzy systems with the asynchronous constraints of the membership functions. First, an event-triggered communication (ETC) scheme is proposed to trigger the transmission only when the variation of the sampled vector exceeds a prescribed threshold condition. Second, a model of fuzzy filtering error system is built under consideration of the ETC scheme, asynchronous premise and communication delay in a unified framework. Then, less conservative criteria on H ∞ filtering analysis and design are derived by making use of the re-constructed asynchronous premises. Finally, two examples are used to show the effectiveness of the proposed method.

To Transmit or Not to Transmit: A Discrete Event-Triggered Communication Scheme for Networked Takagi–Sugeno Fuzzy Systems

This paper first proposes a discrete event-triggered communication scheme for a class of networked Takagi-Sugeno (T-S) fuzzy systems. This scheme has two main features: 1) Whether or not the sampled state should be transmitted is determined by the current-sampled state and the error between the current-sampled state and the latest transmitted state. Compared with those in a periodic time-triggered communication scheme, the communication bandwidth utilization is considerably reduced while preserving the desired control performance; and 2) it is a discrete event-triggered communication scheme due to the fact that the triggered conditions are only measured and checked at a constant sampling period. Compared with a continuous event-triggered communication scheme, the special hardware for continuous measurement and computation is no longer needed. Second, a networked T-S fuzzy model is delicately constructed, which not only considers nonuniform time scales in the networked T-S fuzzy model and the parallel distributed compensation fuzzy control rules but includes the aforementioned state error as well. Third, a stability criterion and a stabilization criterion about the networked T-S fuzzy system are derived, respectively. The stability criterion and stabilization criterion can provide a tradeoff to balance the required communication resource and the desired performance: Lowering the desired performance allows the network to allocate more limited bandwidth to other nodes in need. Finally, a numerical example is given to show the effectiveness of the proposed method.