Event-triggered Fuzzy Control Research Articles

Adaptive backstepping control of high-order fully actuated nonlinear systems with event-triggered strategy

This paper investigates the problem of adaptive event-triggered fuzzy control for nonlinear high-order fully actuated systems. In this paper, a completely unknown nonlinear function is considered, and its prior knowledge is unknown. To solve this problem, the fuzzy logic system technology is applied to approximate the unknown nonlinear function. In order to save communication resources, a novel high-order event-triggered controller is proposed under backstepping control. With the help of Lyapunov stability theory, it is proved that all signals of the closed-loop system are bounded. Finally, the theoretical results are applied to the robot system to verify their validity.

Adaptive event-triggered fuzzy tracking control for underactuated surface vehicles under external disturbances

In this paper, the tracking control problem of underactuated surface vehicles with modeling uncertainties and unknown external disturbances is studied. The fuzzy logic system is applied to approximate the uncertainties in the model. A new disturbance observer with a learning factor is introduced to compensate external disturbances. It can improve observation precision and lead to faster tracking of the system. According to this, and combining the adaptive backstepping technique with the command-filter and event-triggered mechanism, the adaptive fuzzy control method is proposed to guarantee the boundedness of all the closed-loop signals. It is also proved that the tracking errors of the position and yaw angle can keep within a certain precision in finite time. Simulation on the surface vessel verifies the feasibility, and the proposed method is insensitive to the main design parameters.

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.

Relaxed nonquadratic H∞ robust constrained event-triggered fuzzy controller design for discrete-time nonlinear systems

This paper introduces an [Formula: see text] robust constrained event-triggered fuzzy controller for discrete-time nonlinear systems in the presence of system parameter uncertainties, the parameter uncertainties of the output matrices and the disturbances, simultaneously. To reduce the communication resources and improve the robust performance, the event-triggered mechanism is incorporated with the [Formula: see text] robust fuzzy controller design. Moreover, by employing the fuzzy modeling of the actuator saturation and a nonquadratic Lyapunov function (NQLF), the ultimate bounded stability (UBS) of the closed-loop system is guaranteed subject to the amplitude limitations of the control signal. This means, a new linear matrix inequality (LMI) problem is derived to ensure the robustness and constraints in an offline scheme based on the event-triggered strategy. Besides, to meet the practical problem to further improve the controlled system performance, the control input rate constraint is also considered and a new LMI condition is provided with no online computational burden. Therefore, the computational burden of the proposed controller is greatly reduced with less conservatism. Two simulation examples including a numerical dynamic system and a truck–trailer system are employed to illustrate the less conservatism and computational complexity of the proposed method compared with the existing approaches.

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.

A New Intermittent Event-Triggered Bounded Stabilization Approach for Stochastic T–S Fuzzy Systems With External Disturbances

This article focuses on the bounded stabilization issue for stochastic Takagi–Sugeno (T–S) fuzzy systems with external disturbances under fuzzy intermittent event-triggered control. Different from the common intermittent control scheme, the intermittent control proposed is based on an event-triggered mechanism instead of a traditional time-triggered mechanism during the work intervals. As a result, it reduces unnecessary sampling times and resource waste to a great extent. Meanwhile, the minimum interexecution time is obtained for T–S fuzzy systems under the stochastic case. In addition, this article presents a novel Lyapunov function, which simplifies the proof compared to the traditional Lyapunov function for intermittent control. Based on the average control rate adopted and the Lyapunov method, a bounded stability criterion is established, which is less conservative. Then, a corollary is given under the fuzzy event-triggered control. Finally, an example is shown to illustrate the effectiveness of the results obtained.

Event-triggered fuzzy integral control for a class of nonlinear singularly perturbed systems

A fuzzy integral controller with an event-triggered strategy for a class of nonlinear continuous singularly perturbed systems is proposed in this manuscript. Since the singularly perturbed systems are characterized by the parasitic parameter ɛ, which leads the systems to have multi-time-scale dynamics, a state feedback controller is proposed and designed for manipulating the effects of the parasitic parameter with the ɛ free functions by utilizing the Takagi–Sugeno fuzzy model, integral feedback, and event-triggered mechanism. As a result, we demonstrate that the proposed method maintain almost the same performance as the conventional controllers with less steady-state error while producing fewer events, which makes the communication channels between the plant system and the controller more available, through the examples of electrical engineering problems.

Fixed-time event-triggered fuzzy adaptive control for uncertain nonlinear systems with full-state constraints

This research investigates the fixed-time event-triggered fuzzy adaptive control for uncertain nonlinear systems with full-state constraints. Due to the difficulty of modeling and the inherent characteristics of mechanical structures, uncertainties and state constraints often arise in engineering applications, and the system may suffer from network congestion. Ignoring the effects of these constraints can affect the performance of the system. In addition, the system often requires high convergence speeds to increase productivity. To cope with these problems, this study investigates the fixed-time event-triggered fuzzy adaptive control method. First, special barrier Lyapunov functions (BLFs) are constructed to ensure that the full-state constraints are not violated. Furthermore, considering that the communication resources of practical systems are limited, a fuzzy based event-triggered mechanism (ETM) is designed. On this basis, a fixed-time fuzzy adaptive controller is constructed to achieve the fast convergence of the system. Finally, simulation results verify the feasibility.

Analysis and design of control systems via parameter‐based approach

Analysis and design of control systems via parameter‐based approach

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.

Adaptive event-triggered fuzzy control for hot strip finishing mill via a disturbance observer-based method

In this paper, a disturbance observer-based adaptive event-triggered control scheme is proposed for hot strip finishing mill against the problem brought by the interstand tension and the looper angle. Firstly, a standard backstepping method is adopted to the design of control scheme with the consideration that the interstand looper possesses particular structure of the dynamic model. Then, via selecting a suitable gain function, the unknown disturbance can be estimated well by the disturbance observer. Meanwhile, it is noted that the looper current control has very fast dynamics when generating the looper torque. Therefore, the actuator torque can be viewed as directly related to the control signal. In addition, since the strip tension fluctuation has an effect on width and thickness, it will be dampened until larger than looper angle fluctuation. Furthermore, unknown nonlinear terms generated by the process of finishing mills can be approximated by linear functions integrated by fuzzy logic systems. The proposed event-triggered control scheme is used to guarantee the Lyapunov stability and performance requirements of the overall system. The effectiveness of the proposed controller is illustrated in simulation results and application.

Dynamic event-triggered fuzzy control of DC microgrids under FDI attacks and imperfect premise matching

This paper investigates the T–S fuzzy control of DC microgrids subject to false data injection (FDI) attacks, premise mismatching, and network delays using a dynamic event-triggered mechanism (ETM). Unlike the static ETMs using the fixed triggering parameters, by adaptively adjusting the triggering parameters, the proposed novel discrete-time dynamic ETM can more effectively reduce excessive usage of communication resources, and the Zeno behavior is also avoided naturally. Then, a novel T–S fuzzy closed-loop system model is built, which considers the FDI attacks, dynamic ETM, delays and premise mismatching all in one unified framework. Mean-square exponential stability criteria are derived, which establish the relationship between system performance and the contributing factors. Further, unlike the two-step emulation based method, the proposed co-design method can design the injection current controller and the dynamic ETM in one step, which offers a convenient framework for the tradeoffs between control and communication performances. Both simulation and experimental results confirm the effectiveness of the proposed methods, achieving 27.5% savings of communication resources while effectively stabilizing the DC microgrid even under the situation that 13.5% of the transmitted data are tampered by the FDI attacks.

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.

Event-triggered fuzzy finite-time reliable control for dynamic positioning of nonlinear unmanned marine vehicles

This paper studies the fuzzy finite-time reliable dynamic positioning (DP) control for nonlinear unmanned marine vehicles. Firstly, the motion dynamics of nonlinear unmanned marine vehicles is modeled by the Takagi-Sugeno (T-S) fuzzy system. Secondly, a fuzzy state observer is designed to estimate the immeasurable position and velocity of unmanned marine vehicles. In order to decrease the frequency of data transmission of actuators and sensors, a dynamic event-triggered mechanism is presented based on unmanned marine vehicles information and the estimation error. Then, a fuzzy event-triggered reliable output feedback control method is presented by finite-time theory to tackle the actuator faults problem occurring in unmanned marine vehicles. The sufficient finite-time stable conditions in the form of LMIs are established via constructing finite-time Lyapunov-Krasovskii functional. Ultimately, the computer simulation results and comparisons with the existing control methods verify the advantages of the presented control method.

Finite-Time Dynamic Event-Triggered Fuzzy Output Fault-Tolerant Control for Interval Type-2 Fuzzy Systems

The finite-time dynamic event-triggered fuzzy output feedback fault-tolerant control problem is studied in this article for the interval type-2 (IT2) Takagi–Sugeno fuzzy system with parameter uncertainties and actuator faults. A fuzzy state observer is first developed to solve the immeasurable state problem. Second, by using the sampled estimating states and measured output signals, a dynamic event-triggered mechanism is formulated via integrating sensor-to-observer with observer-to-controller. Third, an observer-based finite-time event-triggered fuzzy fault-tolerant controller is synthesized via the nonparallel distribution compensation design principle. Consequently, the finite-time stable conditions of the addressed IT2 fuzzy system are established by constructing an appropriate Lyapunov function. Furthermore, an output feedback control design algorithm of solving control and observer gains is given in terms of the established sufficient finite-time stable conditions. Finally, a practical example of a nonlinear tunnel diode circuit system is provided to verify the effectiveness of the proposed IT2 fuzzy control scheme.

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.

A T-S fuzzy state observer-based model predictive reset control for a class of fuzzy nonlinear systems with event-triggered mechanism

In this study, the problem of observer-based control for a class of nonlinear systems using Takagi-Sugeno (T-S) fuzzy models is investigated. The observer-based model predictive event-triggered fuzzy reset controller is constructed by a T-S fuzzy state observer, an event-triggered fuzzy reset controller, and a model predictive mechanism. First, the proposed controller utilizes the T-S fuzzy model and is constructed based on state observations and discrete sampling output, which can greatly reduce the occupation of communication resources. Then, the model predictive strategy for reset law design is designed in this paper. With a reasonable reset of the controller state at certain instants, the performance of the reset control systems is improved. Finally, the validity of the proposed method is illustrated by simulation. The merits of the proposed controller in improving transient performance and reducing the communication occupation are demonstrated by comparing its results with the output feedback fuzzy controller and the first-order fuzzy reset controller.

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.

Fuzzy Event-Triggered Control for PDE Systems With Pointwise Measurements Based on Relaxed Lyapunov–Krasovskii Functionals

In this article, an event-triggered control problem for partial differential equation systems with pointwise measurements is investigated via relaxed Lyapunov–Krasovskii functionals. First, the Takagi–Sugeno fuzzy model is introduced to describe the nonlinear systems and a fuzzy event-triggered pointwise controller is proposed with pointwise measurements, which can make a tradeoff between the system’s performance and implementation complexity subject to limited transmission bandwidth. Second, some relaxed conditions are established to ensure the closed-loop system’s stability by using the Lyapunov method and inequality techniques. Finally, two simulation examples are provided to demonstrate the effectiveness and practicability of the designed controller.