Event-triggered Fuzzy Control Research Articles

Adaptive fuzzy event-triggered control for a class of nonlinear time-delay multi-agent systems with dead zone and partial state constraints

This paper presents an adaptive fuzzy event-triggered control (ETC) method for a class of time-delay nonlinear multi-agent systems (MASs) with dead zone (DZ) and partial state constraints (PSCs). It should be pointed out that the states considered in this paper are unmeasurable and part of the system states are constrained by time-varying boundary. By utilizing fuzzy logic systems (FLSs) and backstepping design framework, a fuzzy state observer is constructed to estimate the unmeasured states, while the introduction of a time-varying barrier Lyapunov function (BLF) addresses the partial state constrained problem. Furthermore, during the design process of the state observer, compensation for the influence of the unknown DZ input on the system is achieved through utilization of known designed event-triggered input signal and adaptive parameter. Building upon this foundation, employing the Lyapunov stability theory and adaptive backstepping technique with ETC strategy, the developed distributed control mechanism demonstrates that all variables of the closed-loop system are bounded, the consensus error of the system can converge to a small region of origin and Zeno behavior can be ruled out. Finally, two simulation examples further illustrate the proposed control strategy and theorem.

Fuzzy control for networked systems with mixed data missing under quantization based event-triggered scheme

This paper presents an innovative event-triggered fuzzy control approach for networked systems operating over unreliable network channels. Traditional complicated modeling and analysis process of network induced issues is replaced by a bran-new logarithmic quantization based event-triggered scheme method. The joint characterization of mixed data missing, arising from the event-triggered mechanism and unreliable network channels, becomes a challenging issue due to disrupted data sequences and variable relations. Consequently, this paper contributes a formulated auxiliary stochastic sequence approach to overcome the difficulty of dynamics modeling. With an formulated event driven controller, the modeling and implementation of the closed-loop systems are constructed and further simplified. Considering the difference and relation between the membership functions of plant and controller, we present a new fuzzy output feedback controller design method to obtain feasible result via uncertainty based method. Finally, we verify the validity of the designed control policy via a simulation example.

Fuzzy Event-Triggered Control for Grid-Connected PMSM Model With Stochastic Disturbances

Fuzzy Event-Triggered Control for Grid-Connected PMSM Model With Stochastic Disturbances

Adaptive Event-Triggered Fuzzy Control for Unreliable Networked Control Systems with Time-Varying Delay

Adaptive Event-Triggered Fuzzy Control for Unreliable Networked Control Systems with Time-Varying Delay

The positivity and event-triggered stabilization of Takagi-Sugeno fuzzy systems with actuator saturation

The positivity and event-triggered stabilization of Takagi-Sugeno fuzzy systems with actuator saturation are investigated in this paper. Different from the existing quadratic event-triggered mechanism (ETM), a linear ETM is constructed, which can be reduced to a time-triggered mechanism (TTM). Based on parallel distribution compensation, an event-triggered fuzzy controller is designed, and sufficient conditions under the estimation of a certain domain of attraction are proposed to ensure the ETM-based and TTM-based closed-loop systems are positive and stable. The controller gain is solved directly by the proposed conditions. And then these sufficient conditions are extended to the conditions under the estimation of the largest domain of attraction by establishing an optimization problem. Furthermore, the linear ETM is proved to exclude the Zeno behavior of the system. Finally, two simulation examples are utilized to verify the effectiveness of the proposed event-triggered control scheme.

Reinforcement Learning-Based Adaptive Event-Triggered Fuzzy Control for Cyclic Switched Stochastic Nonlinear Systems With Actuator Faults

Reinforcement Learning-Based Adaptive Event-Triggered Fuzzy Control for Cyclic Switched Stochastic Nonlinear Systems With Actuator Faults

Adaptive fuzzy event-triggered cooperative control for fractional-order delayed multi-agent systems with unknown control direction

In this paper, the cooperative control of fractional-order multi-agent systems with time delay and unknown control direction is studied by combining frequency distributed model and event-triggered mechanism. The Nussbaum function is employed to address the unmeasured control direction. Then, through the event-triggered mechanism, a corresponding controller is designed, which can guarantee that all signals are bounded while saving resources. The proposed theme is convenient for analyzing the stability of fractional-order systems based on a transformation of frequency distributed model. In particular, in order to enhance the universality of the proposed scheme in the fractional-order system stability analysis, a generalized fractional-order generalized lemma with respect to the Nussbaum function is given. Finally, the availability of the proposed method is confirmed by a simulation example.

Distributed Event-Triggered Fuzzy Control of Heterogeneous Switched Multiagent Systems Under Switching Topologies

Distributed Event-Triggered Fuzzy Control of Heterogeneous Switched Multiagent Systems Under Switching Topologies

A Concurrent Event-Triggered Approach for Fuzzy Adaptive Control of Nonlinear Strict-Feedback Systems.

If a control input signal constructed by backstepping is used to generate an event-triggered control signal, then not only the real control input is discontinuous, but all the virtual control signals that make up the control signal are also discontinuous and have the same triggering instants with the control input. This fact makes the control design and stability analysis more difficult and complex via backstepping. This article focuses on this problem and works at coming up a new backstepping design procedure of event-triggered fuzzy adaptive control for nonlinear strict feedback systems. A concurrent event-triggered mechanism is proposed to ensure that the real control input and the virtual control signals have the same triggering instants. Then, a systemic backstepping design procedure is developed to construct event-triggered fuzzy adaptive controller. The Lyapunov technique for nonlinear impulsive system is employed to provide the closed-loop stability analysis. It is shown that the derived event-triggered fuzzy adaptive controller ensures that the closed-loop system output well follows the desired tracking trajectory and the other closed-loop signals remain bounded. Eventually, two examples are provided to further verify the applicability and reliability of the presented control scheme.

Adaptive Fuzzy Event-Triggered Formation Control for Nonholonomic Multirobot Systems With Infinite Actuator Faults and Range Constraints

Adaptive Fuzzy Event-Triggered Formation Control for Nonholonomic Multirobot Systems With Infinite Actuator Faults and Range Constraints

State-Observer-Based Adaptive Fuzzy Event-Triggered Formation Control for Nonlinear Multiagent System

State-Observer-Based Adaptive Fuzzy Event-Triggered Formation Control for Nonlinear Multiagent System

Adaptive Event-Triggered Fuzzy Control for Stochastic Highly Nonlinear Systems With Time Delay and Nontriangular Structure Interconnections

The problem of adaptive fuzzy control based on the switching event-triggered mechanism for stochastic highly nonlinear system with time-varying delays, actuator faults and non-triangular structure interconnections is investigated in this article. By constructing the corresponding Lyapunov-Krasovskii functional and variable separation method, the complex nonlin- ear functions with time-varying delays and highly nonlinearity can be handled. With the help of the fuzzy logic systems and adaptive compensation technique, the processing difficulty of the unknown nonlinear terms and the parameters of actuator faults is reduced. Simultaneously, the proposed control scheme can greatly decrease the waste of communication resources by a switching event-triggered mechanism. Then, all signals in the system are ensured to be bounded under Lyapunov stability theorem. Ultimately, the simulation example demonstrates the availability of the developed control scheme.

Adaptive Dual-Channel Event-Triggered Fuzzy Control for Autonomous Underwater Vehicles With Multiple Obstacles Environment

Adaptive Dual-Channel Event-Triggered Fuzzy Control for Autonomous Underwater Vehicles With Multiple Obstacles Environment

Event-triggered fuzzy controller co-design for networked systems with denial-of-service attacks and its applications

This manuscript focuses on a controller co-design problem of networked interval type-2 (IT2) fuzzy systems with denial-of-service (DoS) attacks via event-triggered mechanism. A Lyapunov-Krasovskii functional with the sampling property is established to execute stability analysis. New sufficient conditions are acquired for the existence of event-triggered fuzzy controller, and relaxed results are realized. The switched closed-loop system is guaranteed to be exponential stable, and an H∞ performance is reached. At last, the presented control schemes are used in two engineering systems, which demonstrate the efficiency of the developed control strategy.

Dynamic event-triggered fuzzy control for nonlinear singular semi-Markovian jump systems via state decomposition approach

This paper addresses the dynamic event-triggered fuzzy control problem of nonlinear singular semi-Markovian jump systems. Firstly, the interval type-2 fuzzy model is utilized to approximate nonlinear singular semi-Markovian jump systems. Secondly, by employing the state decomposition approach, the interval type-2 fuzzy singular system is decomposed into a differential equation and an algebraic equation. Thirdly, a new periodic dynamic event-triggered scheme with the adaptive variable is proposed to further relieve the communication pressure while ensuring the system performance. The hidden semi-Markov model is used to describe the phenomenon that the modes of fuzzy controller and the modes of original system are asynchronously operational. By designing the asynchronous event-triggered fuzzy controller based on quantized decomposed state vectors and constructing suitable Lyapunov-Krasovskii functional, sufficient conditions are derived to guarantee that the closed-loop fuzzy singular system is stochastically admissible. Finally, two simulation examples are provided to verify the validity and advantages of obtained results.

Adaptive Event-Triggered Fuzzy Control of State-Constrained Stochastic Nonlinear Systems Using IBLFs

In this article, an adaptive tracking control problem is addressed for nonstrict-feedback stochastic nonlinear systems subject to state constraints. Fuzzy logic systems (FLSs) are used to model unknown nonlinearities and avoid the algebraic loop arising from the system structure. Appropriate integral Barrier Lyapunov functions (IBLFs) are chosen so that time-varying full state constraints can be guaranteed directly rather than by transforming the constraint object. In the framework of backstepping technology, the relative threshold strategy is introduced to modify the adaptive control scheme so that the controller can be updated only after the trigger condition has been met, which reduces the update frequency of the controller and the loss of the actuator. Combined with Lyapunov stability theory, it is shown that all closed-loop signals are bounded in probability, in which the states remain within the specified constraints, and there is no Zeno behavior. A series of simulation results are given to reveal the effectiveness of the constructed control scheme.

Distributed event-triggered fuzzy control for nonlinear interconnected systems

This paper deals with the asynchronous distributed event-triggered control of continuous-time nonlinear interconnected systems. The nonlinear dynamics of the subsystems are represented by Takagi–Sugeno fuzzy models via the sector nonlinearity approach. Moreover, the nonlinear interconnections among the subsystems are assumed to be known and sector-bounded. In the event-triggered control setup, where the state information is asynchronously available to the local controllers only in specific time instants, it is necessary to deal with the asynchronous premise variables because they introduce extra difficulties to derive suitable co-design conditions. To deal with this issue, we propose a new triggering strategy such that the local event-triggering mechanisms (ETMs) counteract the effects of asynchronous premise variables. With this new distributed ETM, a co-design condition is proposed, and the existence of a strictly positive minimum inter-event time is proved to exclude Zeno behaviour. Moreover, a multi-objective optimization procedure is introduced to enlarge the estimate of the domain of attraction of the closed-loop equilibrium and minimize the number of transmissions provided by the ETMs. Finally, the approach is validated through the synchronization of interconnected oscillators.

Finite-Time Adaptive Fuzzy Event-Triggered Control for Nonstrict Feedback Stochastic Nonlinear Systems With Multiple Constraints

Finite-Time Adaptive Fuzzy Event-Triggered Control for Nonstrict Feedback Stochastic Nonlinear Systems With Multiple Constraints

Stability and Stabilization of Fuzzy Event-Triggered Control for Positive Nonlinear Systems

Stability and Stabilization of Fuzzy Event-Triggered Control for Positive Nonlinear Systems

Event-Triggered Adaptive Fuzzy Finite-Time Output Feedback Control for Stochastic Nonlinear Systems With Input and Output Constraints

This paper focuses on the problem of designing an adaptive fuzzy event-triggered finite-time output feedback control for stochastic nonlinear systems with input and output constraints. A fuzzy observer is designed to estimate the unmeasured states. The quartic asymmetric time-varying barrier Lyapunov function is established to ensure constraint satisfaction. By utilizing the stochastic theory, finite-time command filtered backstepping method and event-triggered mechanism, a finite-time event-triggered controller is recursively designed, which can not only guarantee finite-time convergent property, but also reduce communication pressure. Meanwhile, the matter of “explosion of complexity” is removed by introducing the finite-time command filter and the effect of filtered errors is offset by constructing error compensation signals. Moreover, an auxiliary system is introduced to handle the input constraint. Finally, the effectiveness of the theoretical results is demonstrated by the simulation example.