Adaptive Fuzzy Event-Triggered Control Research Articles

Finite-time adaptive fuzzy event-triggered control for nonlinear time-delay system with input quantization via command filter

This paper investigates the problem of finite-time adaptive fuzzy event-triggered control for a class of uncertain nonlinear systems with input quantization. The nonlinear systems under consideration contain unmodeled dynamics and time-varying delays. Fuzzy logic systems are used to handle unknown nonlinear terms. Additionally, finite-time filters are introduced to solve the problem of “explosion of complexity” as well as to ensure that the derivative of the virtual controller can be approximated in finite time. The Lyapunov–Krasovskii function is used to handle time-varying delays. The hysteresis quantizer is used to ensure adequate precision when there is a low transmission rate requirement. The control strategy combines event-triggered mechanisms and quantization technology to ensure that all signals of the closed-loop system remain bounded in finite time. Finally, two examples are included to demonstrate the effectiveness of the proposed controller.

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.

Discrete-Time Adaptive Fuzzy Event-Triggered Control for PMSMs With Voltage Faults via Command Filter Approximator

Discrete-Time Adaptive Fuzzy Event-Triggered Control for PMSMs With Voltage Faults via Command Filter Approximator

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

Event-based adaptive fuzzy tracking control for nonlinear systems with guaranteed performance

This article is concerned with the problem of event-based adaptive prescribed time tracking control for a class of uncertain strict-feedback nonlinear systems. To ensure that the considered system possesses the user-specified tracking performance, an improved error transformation is constructed and incorporated with a novel fixed-time performance function with an infinite initial value, completely removing the restriction that the tracking error is less than the pre-assigned performance boundary in the initial interval. Then, the utilization of command filtered technique and two single parameter estimators severally related to the upper bounds of fuzzy logic systems-based unknown constant parameters and external disturbances not only obviates the “explosion of complexity” issue but also simplifies the control design procedure. On this basis, by skillfully synthesizing adaptive technology and event-triggered mechanism within the framework of command filtered backstepping technique, a novel adaptive fuzzy event-triggered control solution is presented to save the limited network resources. Under the developed controller, the tracking error is steered to converge to an adjustable asymmetric region within a pre-specified time, and the boundedness of all closed-loop signals is ensured. Finally, simulation studies are performed to demonstrate the effectiveness and practicability of the developed control solution.

Fixed-time adaptive fuzzy event-triggered control for uncertain nonlinear systems with output constraint and actuator failures

For a category of uncertain nonlinear systems with output constraint and actuator failures, the fixed-time event-triggered control method is investigated. Output constraint and actuator failures are common in practical systems, which may affect the performance of the system. Most of the existing schemes to deal with these problems only guarantee the system's asymptotic stability. It is a challenge to design event-triggered based controllers to achieve fixed-time stability of a system with the above constraints. To handle the above problems, barrier Lyapunov functions (BLFs) and extended fuzzy logic systems (EFLSs) are introduced to the backstepping procedure. Besides, to reduce redundant data transmissions, an event-triggered mechanism (ETM) is designed. On this foundation, a fixed-time event-triggered control method is proposed. Technically, by using the proposed method, the controlled system is practically fixed-time stable, and the system output abides by the corresponding constrained requirements. Meanwhile, the communication resources are saved. Finally, some simulation examples are used to demonstrate the effectiveness of the control method.

Adaptive Fuzzy Event-Triggered Control for Non-Strict Feedback Nonlinear Systems With Input Delay and Full State Constraints

Adaptive Fuzzy Event-Triggered Control for Non-Strict Feedback Nonlinear Systems With Input Delay and Full State Constraints

Finite-Time Adaptive Fuzzy Event-Triggered Control of Constrained Nonlinear Systems via Bounded Command Filter

In this note, finite-time adaptive tracking control is studied for nonlinear systems with unmodeled dynamics, asymmetric time-varying output constraints, and uncertain disturbances. Without any growth conditions, fuzzy logic systems are applied to tackle the unknown complicated functions. A novel backstepping approach is developed by combining barrier Lyapunov functions and bounded finite-time command filter. By regulating the threshold parameters online, a new dynamic event-triggered controller is established to ensure that all the signals of the closed-loop system are bounded and the output can follows the preset signal in finite time. Meanwhile, the output is always staying in an asymmetric time-varying interval all the time. The feasibility of the proposed control algorithm is verified with a numerical example and a practical application.

Observer-Based Adaptive Fuzzy Event-Triggered Control for Mechatronic Systems With Inaccurate Signal Transmission and Motion Constraints

This article presents an adaptive output feedback controller for a class of Euler–Lagrange (EL) mechatronic systems subject to time-delay, input hysteresis, and motion constraints; simultaneously, the event-triggered mechanism is introduced to decrease communication costs. During controller design, the proposed method <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">not only</i> relaxes additional requirements on the model structures by other methods (e.g., parameters linearly appearing in dynamics or strict triangular/cascade normal forms), <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">but also</i> estimates uncertain dynamics and approximation errors online, <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">instead of</i> utilizing “large-gain” or discontinuous terms to suppress their impacts. Regarding the inaccurate signal transmission of EL systems, this article presents a <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">modified</i> fuzzy observer with an elaborately designed auxiliary term, to recover unmeasurable variables and simultaneously deal with state time-delay. Meanwhile, the Prandtl–Ishlinskii model is employed to imitate input hysteresis, whose unknown parameters are also estimated online to improve tracking accuracy. By Lyapunov-based stability analysis, it is proven that the error signals are always limited within preset constraints and asymptotically converge to zero. As far as we know, for EL systems, this article proposes the <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">first</i> controller to address such <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">comprehensive</i> effects of <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">unreliable</i> state feedback, limited workspace, and input/output nonlinearities in practice, and also eliminate tracking errors with a <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">theoretical guarantee</i> . More importantly, the utilized event-triggered mechanism further improves the practicability of this article. Finally, based on a pneumatic artificial muscle (PAM)-actuated robot manipulator, the performance of the proposed controller is validated via hardware experiments.

Adaptive Fuzzy Event-Triggered Tracking Control for Nonstrict Nonlinear Systems

This article addresses adaptive fuzzy event-triggered controller design for nonstrict nonlinear systems. First, for estimating the unmeasurable states, the high-gain fuzzy state observer is designed. By using backstepping technique, the adaptive fuzzy controller is designed. A new switching threshold event-triggered mechanism is given to decide when the controller needs to be updated and the Zeno behavior is avoided. Stability analysis shows that the tracking error can be arbitrarily small and all variables of the closed-loop system remain bounded. At last, the effectiveness of our control strategy is illustrated through simulation.

Adaptive Fuzzy Event-Triggered Control of Aerial Refueling Hose System With Actuator Failures

In this study, we propose an adaptive fuzzy event-triggered control scheme for an autonomous aerial refueling hose system involving uncertainty, an event-triggered mechanism, and actuator failures. The unknown nonlinear function is approximated using the designed fuzzy logic systems. Through introduction of the adaptive compensation scheme, the problem of an infinite number of actuator failures, including partial and complete failures, is solved. In addition, the event-triggered control strategy is designed to achieve vibration suppression while decreasing the communication burden between the controllers and actuators. The stability of the closed-loop system is demonstrated via the Lyapunov direct method. Finally, simulation examples are presented to confirm the validity of the proposed control scheme.

Adaptive Fuzzy Event-Triggered Control for High-Order Nonlinear Systems With Prescribed Performance.

This article focuses on the design of a novel adaptive fuzzy event-triggered tracking control approach for a category of high-order uncertain nonlinear systems with prescribed performance requirements, in which a high-order tan-type barrier Lyapunov function (BLF) is employed to handle and analyze the output tracking error, fuzzy systems are adopted to identify the totally unknown nonlinear functions, and only one gain function rather than parameter estimation functions is designed to cancel out all unknowns appearing in fuzzy systems. As a result, complicated calculations are avoided and a structured simple control is achieved. The proposed controller not only ensures that the tracking error is always within a predefined region but also reduces the communication burden from the controller to the actuator. Finally, comparison simulations are presented to verify the effectiveness of the proposed control schemes.

Decentralised adaptive fuzzy event-triggered control for nonlinear switched large-scale systems with unknown backlash-like hysteresis

A decentralised adaptive fuzzy event-triggered control problem of nonlinear switched large-scale systems with unknown hysteresis is investigated in this article, in which the unknown hysteresis is expressed by several nonlinear differential equations. The unknown nonlinearities in the systems are generally approximated by fuzzy logic systems due to their excellent function approximation abilities. Through employing dynamic surface control technology, the issue of complexity explosion resulting from repeated differentiation in the traditional backstepping method is overcome. A decentralised event-triggered controller is developed through adopting the common Lyapunov function approach. In the closed-loop system, the whole signals are semi-globally uniformly ultimately bounded which can be guaranteed through adopting the proposed scheme. Ultimately, the simulation results of two examples demonstrate the validity of the proposed strategy.

Fuzzy adaptive event-triggered control for uncertain nonlinear system with prescribed performance: A combinational measurement approach

This paper addresses the adaptive fuzzy event-triggered control (ETC) problem for a class of nonlinear uncertain systems with unknown nonlinear functions. A novel ETC approach that exhibits a combinational triggering (CT) behavior is proposed to update the controller and fuzzy weight vectors, achieving the non-periodic control input signals for nonlinear systems. A CT-based fuzzy adaptive observer is firstly constructed to estimate the unmeasurable states. Based on this, an output feedback ETC is proposed following the backstepping and error transformation methods, which ensures the prescribed dynamic tracking (PDT) performance. The PDT performance indicates that the transient bounds, over-shooting and ultimate values of tracking errors are fully determined by the control parameters and functions chosen by users. The closed-loop stability is guaranteed under the framework of impulsive dynamic system. Besides, the Zeno phenomenon is circumvented. The theoretical analysis indicates that the proposed scheme guarantees control performance while considerably reducing the communication resource utilization and controller updating frequency. Finally, the numerical simulations are conducted to verify the theoretical findings.

Adaptive Fuzzy Event-triggered Control for a Class of Switched Nonlinear Systems with Dead Zone Nonlinearity

Adaptive Fuzzy Event-triggered Control for a Class of Switched Nonlinear Systems with Dead Zone Nonlinearity

Adaptive fuzzy event-triggered control for nonstrict-feedback switched stochastic nonlinear systems with state constraints

Due to the frequent occurrence of random disturbances in practical physical systems, the control design of stochastic systems has a significant application background. This article presents an event-triggered adaptive fuzzy control scheme for nonstrict-feedback switched stochastic nonlinear systems with state constraints. The barrier Lyapunov functions are deployed to make all states maintain the prescribed regions. In addition, the event-triggered mechanism is incorporated into the backstepping framework to mitigate the data transmission. The fuzzy logic systems are exploited to cope with the system uncertainties, and then the adaptive fuzzy control strategy is recursively constructed. The devised event-triggered adaptive fuzzy controller can not only surmount the influence of state constraints but also decrease unnecessary resource consumption. In virtue of common Lyapunov function method, it is shown that all system signals are bounded under switching signals and the predefined constraints are not violated. Finally, the validity of the presented scheme is elucidated by simulation results.

COLREGs-Constrained Adaptive Fuzzy Event-Triggered Control for Underactuated Surface Vessels With the Actuator Failures

This article investigates the adaptive fuzzy event-triggered control for the underactuated surface vessels (USVs), considering constraints of the International Regulations for Preventing Collisions at Sea (COLREGs) and the actuator failures. The proposed scheme can be divided into the guidance module and the control module. An improved logic virtual ship guidance principle, considering the ship-to-ship collision avoidance, is developed to generate the real-time reference signal for USVs. The main characteristic of the guidance principle is to ensure USVs sailing in the path following mode and collision avoidance mode. Especially for the collision avoidance mode, the collision avoidance guidance is targetedly designed for three sailing situations (the head-on situation, the overtaking situation, and the crossing situation), which is consistent with the COLREGs. Furthermore, an adaptive fuzzy event-triggered law is designed to control the USVs to converge to the desired path. The model unknown terms and the basic fault of the actuator are identified by the fuzzy logic system, and the fuzzy logic state observer is designed to estimate the unmeasured states of the USVs. Unlike the existing results, the communication burden from the controller to the actuators is reduced for the merits of the input event-triggered rule. Through the Lyapunov theory, it is proved that all the signals of the closed-loop control system are the semiglobal uniform ultimate bounded. Finally, the simulated examples are provided to illustrate the validity of the proposed control approach.

Event-Triggered Adaptive Fuzzy Fault-Tolerant Control for Stochastic Nonlinear Systems via Command Filtering

This article investigates the command filtering-based event-triggered adaptive fuzzy control problem for a class of stochastic nonlinear systems with stochastic faults and input saturation. The unknown nonlinear functions and system dynamic changes that caused by stochastic faults are approximated by fuzzy logic systems (FLSs). In order to reduce the computational burden, the command filtering design technique is incorporated into the adaptive fuzzy event-triggered control strategy. Finally, the effectiveness of the proposed method is verified by simulation studies, in which the uniform ultimate boundedness of the system is guaranteed and all the signals in the closed-loop system are bounded.

Event-Triggered Adaptive Fuzzy Control for Stochastic Nonlinear Systems With Unmeasured States and Unknown Backlash-Like Hysteresis

This article investigates the event-triggered control problem for stochastic nonlinear systems with unmeasured states and unknown backlash-like hysteresis. Based on the fuzzy logic systems, the unknown nonlinear functions can be identified. Then, by utilizing a fuzzy state observer, the unmeasured states of the considered system can be estimated. Moreover, by introducing an event-triggered mechanism, the communication load can be largely reduced. By employing the backstepping control strategy and the adaptive control method, a novel adaptive fuzzy event-triggered control method is constructed. It is shown that whole signals in the closed-loop systems are, ultimately, semiglobally and uniformly bounded in probability. Moreover, the tracking errors and the observer errors are located in a small neighborhood around the origin. Finally, a numerical example is given to confirm the effectiveness of the design scheme.

Adaptive Fuzzy Event-Triggered Control for Stochastic Nonlinear Systems With Full State Constraints and Actuator Faults

In this paper, an adaptive fuzzy output feedback control problem is investigated for a class of stochastic nonlinear systems in which the fuzzy logic systems are adopted to approximate the unknown nonlinear functions. A reduced-order observer and a general fault model are designed to observe the unavailable state variables and describe the actuator faults, respectively. An event-triggered control law is developed to reduce the communication burden from the controller to the actuator. Meanwhile, the barrier Lyapunov functions are constructed to guarantee that all the states of the stochastic nonlinear system are not to violate their constraints. Furthermore, an observer-based adaptive fuzzy event-triggered control strategy is proposed for the full-state-constrained nonlinear system with actuator faults based on backstepping technique, which can guarantee that all the signals in the closed-loop system are bounded and the tracking error converges to a small neighborhood of the origin in a finite time. Finally, simulation results are given to illustrate the effectiveness of the proposed control scheme.