Event-triggered Fuzzy Control Research Articles

Event-triggered fuzzy control for vehicle nonlinear suspension systems with time delay

This article investigates the adaptive event-triggered fuzzy control problem for vehicle suspension systems with nonlinear characteristics and time delay. First, to describe the vehicle suspension system with nonlinear components, a Takagi-Sugeno fuzzy suspension model is established via local linear regression method. Second, considering that the communication bandwidth is limited, an adaptive event-triggered strategy is employed to acquire a higher efficiency in terms of saving the transmission resource. Third, based on a time-delay principle and Lyapunov stability theory, a co-design method is proposed to obtain the event generator and the fuzzy controller simultaneously. The proposed event-triggered fuzzy control method is effective to improve performances of the suspension system and guarantee the limits of suspension travel and tire deflection. Finally, compared with the existing method, the effectiveness of the proposed method is verified by simulation tests with various road disturbances.

Fuzzy event-triggered tracking control for nonlinear unreliable networked systems

This article addresses a fuzzy event-triggered tracking control problem of unreliable networked systems. An event-based tracking controller is put forward to control the plant in fuzzy form. The looped Lyapunov–Krasovskii functional method is made use of conducting stability analysis, and sufficient conditions on the controller are determined. As a result, the tracking control performance is achieved for the controlled system. The feasibility of the presented tracking control design is verified by some examples.

Sampled-Data-Based Event-Triggered Fuzzy Control for PDE Systems Under Cyberattacks

This article presents a new sampled-data-based event-triggered pointwise security controller by pointwise measurements for partial differential equation (PDE) systems under stochastic cyberattacks. First, according to the Takagi–Sugeno fuzzy model, the considered nonlinear system is reconstructed and an event-triggered pointwise fuzzy controller is proposed with pointwise measurements. Moreover, networked control systems are introduced to improve the transmission convenience; however, two deception cyberattacks with different characteristics are brought into PDE systems for the first time. In addition, based on novel Lyapunov–Krasovskii functionals, some relaxed conditions to assure system’s exponential stability are established. Finally, the effectiveness and practicability of the designed controller are demonstrated by numerical and application examples.

Disturbance rejections of interval type-2 fuzzy systems under event-triggered control scheme

The problem of robust stabilization of interval type-2 fuzzy systems are studied by using equivalent-input-disturbance estimator-based event-triggered fuzzy control scheme. The estimator of the addressed system is designed by introducing new membership functions and then by using the same premises of the observer, the fuzzy controller is designed. To be precise, sampling-based event-triggered scheme is taken into the account in the controller design to save the communication resources and avoid the existence of Zeno behaviour. Furthermore, to compensate the impact of unknown disturbance, the equivalent-input-disturbance estimator-block is included as an internal loop of closed-loop system. To derive the stability conditions, a novel type of sampling-dependent piece-wise Lyapunov-Krasovskii functional is constructed. Then, by introducing slack matrices, the fuzzy membership function dependent stability criteria are derived. The event-triggered weighting matrix and the gains of controller and observer can be obtained by obtaining the solutions of the developed stability criteria. At last, numerical simulations are given to reflect the effectiveness and applicability of the developed theoretical results.

Global adaptive fuzzy consensus control of nonlinear multi-agent systems via distributed event-triggered communication

This paper investigates globally bounded consensus of leader-following multi-agent systems with unknown nonlinear dynamics and external disturbance via adaptive event-triggered fuzzy control. Different from existing works where filtering and backstepping techniques are applied to design controllers and event-triggered conditions, a matrix inequality is established to obtain the feedback gain matrix and event-triggered functions. To save communication resources, a new distributed event-triggered controller with fully discontinuous communication among following agents is designed. Meanwhile, a strictly positive minimum of inter-event time is provided to exclude Zeno behavior. Furthermore, to achieve globally bounded leader-following consensus, an adaptive fuzzy approximator and a parameter estimator are designed to approximate the unknown nonlinear dynamics and parameters, respectively. Finally, the effectiveness of the proposed method is validated via a simulation example.

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.

Fuzzy event-triggered control for nonlinear networked control systems

This paper is focus on an event-triggered control design problem for nonlinear networked control systems with missing data and transmission delay in the interval type-2 (IT2) fuzzy form. An event-triggered controller is presented under a sampled-state-error mechanism. By dividing the event-triggered interval into some subsets, stability analysis is carried out based on Lyapunov-Krasovskii functional (LKF), and the stability of the closed-loop system is ensured. The proposed design is applied to the continuous stirred tank reactor system (CSTR) and the manipulator system. The control strategy is effective, and the merit of the event-triggered mechanism is indicated.

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.

Switching mechanism-based event-triggered fuzzy adaptive control with prescribed performance for MIMO nonlinear systems

<p style='text-indent:20px;'>This paper investigates the switching mechanism-based event-trig-gered fuzzy adaptive control issue of multi-input and multi-output (MIMO) nonlinear systems with prescribed performance (PP). Utilizing fuzzy logic systems (FLSs) to approximate unknown nonlinear functions. By using the switching threshold strategy, the system has more flexibility in strategy selection. The proposed control scheme can better solve the communication resource limitation. On account of the Lyapunov stability theory, the stability of the controlled system is proved. And all signals of the controlled system are bounded. Moreover, the tracking errors are controlled in a diminutive realm of the origin within the PP bounded. Simultaneously, the Zeno behavior is avoided. Finally, illustrate the effectiveness of the control scheme that has been proposed by demonstrating some simulation consequences.</p>

Event-triggered fuzzy control for nonlinear time-delay system with full-state constraints and unknown hysteresis

This article considers the nonlinear time-delay system with full-state constrains and actuator hysteresis. Compared with the previous research on input hysteresis phenomenon, all states in the system are required to be constrained in a bounded compact set and the direction of hysteresis is unknown. Thus, the system is difficult to be stabilized and get perfect error tracking performance, and the design procedure is more complicated. By combining barrier Lyapunov functions (BLFs) and Nussbaum functions, a new virtual controller is designed, which combines the properties of Nussbaum function with fuzzy logic systems (FLSs). Furthermore, considering that the rate-dependent characteristic of actuator hysteresis will adversely affect the stability of networked control systems (NCSs), a first-order filter is used to solve the problem, but it brings challenges to the design of Lyapunov–Krasovskii functions (KLFs). Thus, a new LKFs is constructed to compensate for the adverse effects of state delay on the nonlinear system. What’s more, this article propose event-triggered technique to solve the coupling effect of the system communication resource constrains. The proposed adaptive control strategy ensures the boundedness of all signals and does not violate the state constraints, and the controller avoids Zeno behavior, and the tracking error fluctuates around zero in a predetermined compression range. Finally, two simulations results verify the effectiveness of the adaptive control 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.

Event-triggered fuzzy adaptive control of nonlinear switched systems with predefined accuracy and mismatched switching

A fuzzy adaptive switching event-triggered control strategy is obtained for a class of uncertain nonlinear switched systems with predefined accuracy. Since the switching may occur between two adjacent sampling instants and may lead to trigger a new event, it raises the mismatched switching and brings severe challenges to avoid the Zeno behavior of the subsystem controllers. The formidable problems are successfully addressed by a new switching event-triggering mechanism without restrictive assumptions. With the proposed fuzzy adaptive switching control approach, the adverse effects of mismatched switching between the subsystem and the controller are addressed, and no subsystem controllers exhibit the Zeno behavior. Furthermore, by using a projection operator-based adaptation strategy and constructing a class of continuous functions, the convergence accuracy of the switched system appears explicitly in design parameters. It allows designers to make decisions in advance based on the requirement of convergence accuracy. Finally, theoretical results are verified by two illustrative examples.

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

A novel fuzzy control with filter-based event-triggered mechanism for nonlinear uncertain stochastic systems suffered input hysteresis

In this paper, an adaptive fuzzy tracking control with filter-based event-triggered mechanism for stochastic nonlinear uncertain system suffered input hysteresis is presented. Considering stochastic disturbances and input hysteresis, Fuzzy Logic Systems (FLSs) are adopted to handle such issues. A time-varying vector contained weight vector and approximation error is established. Then, a class of smooth function is introduced to develop the adaptive control laws. It is aiming to avoid the chattering issue. Further, to achieve the desired tracking performance, this paper considers the discontinuous control input caused by the event-triggered control strategy. And the filter-based event-triggered strategy is presented. With the aid of Lyapunov function and Backstepping technique, the fuzzy event-triggered tracking control method is established for the considered system. It is testified that all signals are bounded under the action of the proposed method. Finally, the theoretical results are verified by the presented simulation examples.

Adaptive disturbance observer-based event-triggered fuzzy control for nonlinear system

This paper investigates the issue of tracking control of nonlinear system with external disturbance, an event-triggered fuzzy backstepping sliding-mode control strategy is proposed. Firstly, a fuzzy state estimator is designed to estimate the unmeasurable state, and a sliding-mode disturbance observer is presented on the estimation error. In which, consider the conservativeness of the observer parameter, a parameter adaptation law with a double nested structure is proposed to mitigate chattering problems caused by parameter conservativeness. Then an event-triggered mechanism along with backstepping control and sliding-mode strategy is designed to achieve tracking control and save the network resources, and the Zeno phenomenon can be avoided. Furthermore, the backstepping law combines with Lyapunov theory is used to prove that the tracking error can converge to a small bounded set and all the signals of closed-loop plant are bounded. Finally, simulation results are carried out to illustrate the potential of designed approaches.

Decentralized Dynamic Event-Triggered Communication and Active Suspension Control of In-Wheel Motor Driven Electric Vehicles with Dynamic Damping

This paper addresses the co-design problem of decentralized dynamic event-triggered communication and active suspension control for an in-wheel motor driven electric vehicle equipped with a dynamic damper. The main objective is to simultaneously improve the desired suspension performance caused by various road disturbances and alleviate the network resource utilization for the concerned in-vehicle networked suspension system. First, a T-S fuzzy active suspension model of an electric vehicle under dynamic damping is established. Second, a novel decentralized dynamic event-triggered communication mechanism is developed to regulate each sensor's data transmissions such that sampled data packets on each sensor are scheduled in an independent manner. In contrast to the traditional static triggering mechanisms, a key feature of the proposed mechanism is that the threshold parameter in the event trigger is adjusted adaptively over time to reduce the network resources occupancy. Third, co-design criteria for the desired event-triggered fuzzy controller and dynamic triggering mechanisms are derived. Finally, comprehensive comparative simulation studies of a 3-degrees-of-freedom quarter suspension model are provided under both bump road disturbance and ISO-2631 classified random road disturbance to validate the effectiveness of the proposed co-design approach. It is shown that ride comfort can be greatly improved in either road disturbance case and the suspension deflection, dynamic tyre load and actuator control input are all kept below the prescribed maximum allowable limits, while simultaneously maintaining desirable communication efficiency.

Fuzzy adaptive event-triggered output feedback control for nonlinear systems with tracking error constrained and unknown dead-zone

ABSTRACT In this paper, an adaptive fuzzy event-triggered output feedback control scheme is studied for a class of non-strict feedback systems with tracking error constrained and unknown dead-zone. Fuzzy logical systems (FLSs) are employed to solve the uncertainties of the controlled plant, and the immeasurable states are estimated by employing the fuzzy observer. In the designed observer, to compensate for the effect of unknown dead-zone by invoking the known designed event-triggered input signal, an adaptive parameter is designed. Furthermore, due to event-triggered control (ETC) places a great burden on the computing space, the dynamic surface control (DSC) technique is used to solve the problem of ‘explosion of complexity’ in each step, and the simplified barrier Lyapunov function (SBLF) is utilised to restrict the tracking error within the prescribed boundaries. Consequently, the designed parameter adaptive laws and event-triggered controller can ensure that all signals of the closed-loop system are semi-globally uniformly ultimately bounded (SGUUB). Ultimately, two numerical simulation examples are provided to illustrate the effectiveness of the proposed event-triggered control theory.

Type-2 Fuzzy Adaptive Event-Triggered Saturation Control for Photovoltaic Grid-Connected Power Systems

The adaptive interval type-2 (IT2) fuzzy event-triggered saturation control scheme is proposed for a photovoltaic power system with unknown equivalent resistances and the disturbance of the power grid voltage. As the equivalent resistors and the disturbance are uncertain, interval type-2 fuzzy logic systems (IT2FLSs) are used to handle the uncertain nonlinear dynamics. Based on backstepping control design and command filtered techniques, by considering the limited communication resources of the system, an event-triggered saturation controller is designed, and the constraint conditions of the control signal are guaranteed. According to the Lyapunov theory, it is ensured that all the variables of the closed-loop photovoltaic system are bounded. The simulation results demonstrate the effectiveness and superiority of the presented control method.

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.

Event-Based $H_\infty$ Control for Discrete-Time Fuzzy Markov Jump Systems Subject to DoS Attacks

This paper is concerned with H control problem for discrete-time Takagi-Sugeno (T-S) fuzzy Markov jump systems with event-triggering scheme (ETS) and denial-of-service (DoS) attacks. Aperiodic DoS characterized by duration and frequency is introduced. In the light of DoS attacks and event-triggered fuzzy controller, the switched fuzzy Markov jump closed-loop system is established. Particularly, in order to address the issue of mismatched behavior between membership functions of fuzzy system and fuzzy controller, a novel ETS consisting of membership functions is developed. Then with the help of multiple Lyapunov function method and iterative technique, some sufficient conditions are provided to ensure the H performance of the resulting closed-loop system. Subsequently, the explicit parameter design of controller and ETS are provided. Finally, an example is employed to verify the validity of the proposed theoretical method.