Adaptive Event-triggered Control Research Articles

Observer-based adaptive event-triggered control method for input-saturated systems

This paper presents an adaptive event-triggered control method for linear systems subject to input saturation. At the first, using convex hull properties, an observer-based controller is designed and then a generalized event-triggering mechanism is regarded. In order to extend more time interval between any two successive events, an adaptive event-triggered control method is also proposed. The proposed control methodology is based on finite-gain L2 stability. It is noteworthy that the proposed methods are designed in a co-design framework where the observer-based controller design with the event-triggering mechanisms are performed at the same time. Moreover, the presented adaptive approach offers more degrees of freedom as well as preserves the performance criteria high. Besides, Zeno avoidance analysis is studied by introducing a lower bound on inter-event times. Finally, the efficiency of the proposed methods is shown through a case-study numerical example.

Fuzzy adaptive tracking control of fractional-order multi-agent systems with partial state constraints and input saturation via event-triggered strategy

This paper addresses the problem of adaptive tracking control for fractional-order multi-agent systems subject to input saturation and partial state constraints, utilizing an event-triggered strategy with output feedback. The interconnected graph of multiple agents is assumed to be directed and contain a spanning tree. Since only the system output is available, a fractional-order state observer is designed to obtain the unmeasurable states. The nonlinear dynamics of the system are assumed to be unknown and are approximated by a fuzzy logic system. By utilizing the barrier Lyapunov function, backstepping procedure and dynamic surface control technique, an event-triggered adaptive control scheme is proposed to ensure that the constrained states remain within their bounds, all system signals are bounded, tracking error converges to a bounded set containing the origin, and no Zeno behavior occurs. Finally, the validity of the presented method is verified by simulation.

Event-triggered adaptive robust fault-tolerant control for a class of uncertain switched nonlinear systems

In this paper, the adaptive robust fault-tolerant control problem for a class of switched nonlinear systems with parameter uncertainty, disturbances and actuator failures is concerned based on event-triggered control strategy. The adaptive laws based on state-dependent switched strategy are designed to eliminate the effects of actuator faults and parameter uncertainties by using the estimations of the unknown upper bounds of uncertain parameters. Then, the robust fault-tolerant technique and multiple Lyapunov functions method are used, the designed controller can guarantee that all signals of the switched closed-loop systems are uniformly bounded. Meanwhile, the desired performance of the systems is promised. Finally, the simulation results are given to illustrate the effectiveness of the proposed design method.

Finite-time adaptive event-triggered control for USV with COLREGS-compliant collision avoidance mechanism

This paper focuses on the real time intelligent navigation scheme for unmanned surface vehicle (USV) subject to collision avoidance regulations. The proposed approach is formulated as two segments: the real time guidance principle with COLREGS-compliant collision avoidance mechanism and the finite-time adaptive event-triggered control algorithm. The pointed improvement for the artificial potential field (APF) can guarantee USV possess the excellent avoidance function in accordance with COLREGS regulations. Especially, when the obstacle makes dangerous actions, the emergency obstacle avoidance operation (EOAO) is implemented according to the real time position of obstacles. Based on the proposed guidance principle, a finite-time robust neural control algorithm is developed by fusion of the finite-time stability theory and event-triggered mechanism. The intermittent computing and communication can effectively reduce the energy and resource consumption of the control system. Moreover, the finite-time adaptive controller design contributes to smaller computation load and facilitates the implementation of the algorithm in ocean engineering. The semi global finite-time uniformly boundedness (SGFTUB) of the closed-loop system is guaranteed through the Lyapunov theory. Finally, the numerical simulation and comparison experiment are illustrated to verify the guidance and control performance of the proposed algorithm.

A novel nussbaum functions based adaptive event-triggered asymptotic tracking control of stochastic nonlinear systems with strong interconnections

In this work, the issue of event-triggered-based asymptotic tracking adaptive control of stochastic nonlinear systems in pure-feedback form with strong interconnections is considered. First, a new decentralized control scheme is developed by introducing the new types of Nussbaum functions, which enables the output of each subsystem to asymptotically track the desired reference signal. Second, the nonaffine structures and the unknown control gains existing in the nonlinear systems are a part of the considered system model, which makes it more complicated to design the decentralized controllers. Therefore, the complexity caused by the nonaffine structures is faciliated by mean value theorem and the unknown control gains are handled by a novel Nussbaum function in our proposed design scheme. Meanwhile, the unknown nonlinearities of the system are approximated by using intelligent control technology. Furthermore, an event-triggered method is introduced in the design process to save communication resources effectively. It is shown that all signals of the closed-loop systems are bounded in probability and the tracking errors asymptotically converge to zero in probability. Finally, the simulation results illustrate the effectivity of the presented scheme.

Event-triggered adaptive backstepping control for plug-and-play parallel converter systems

Event-triggered adaptive backstepping control for plug-and-play parallel converter systems

Event-triggered-based fuzzy adaptive tracking control for nonstrict-feedback asymmetric state constrained systems

In this article, a fuzzy adaptive command filtered event-triggered control issue is considered for a category of nonstrict-feedback nonlinear systems under the conditions of asymmetric state constraints and time-varying input delay. Firstly, the nonlinear state constrained system is transformed into a new system without state constraints by utilizing nonlinear mappings, which achieves state constraints while removing the feasibility conditions of virtual control signals. Secondly, unknown nonlinear terms in the novel system are approached by using the fuzzy logic systems, a state observer is established to estimate the unmeasurable states in the system, and an auxiliary system is constructed to make up for the influence of time-varying input delay. In addition, the command filtered technology is introduced to overcome the complexity explosion problem in the conventional backstepping design process. It is shown that the fuzzy adaptive event-triggered control scheme can not only ensure the convergence of the tracking error at the origin and the boundedness of all closed-loop signals, but also lighten the communication burden from the controller to the actuator. Finally, a numerical example and an underwater vehicle system are simulated to verify the availability and feasibility of the developed approach.

Adaptive event-triggered synchronization of neural networks under stochastic cyber-attacks with application to Chua’s circuit

This paper focuses on the synchronization control problem for neural networks (NNs) subject to stochastic cyber-attacks. Firstly, an adaptive event-triggered scheme (AETS) is adopted to improve the utilization rate of network resources, and an output feedback controller is constructed for improving the performance of the system subject to the conventional deception attack and accumulated dynamic cyber-attack. Secondly, the synchronization problem of master–slave NNs is transformed into the stability analysis problem of the synchronization error system. Thirdly, by constructing a customized Lyapunov–Krasovskii functional (LKF), the adaptive event-triggered output feedback controller is designed to ensure the synchronization error system is asymptotically stable with a given H∞ performance index. Lastly, in the simulation part, two examples, including Chua’s circuit, illustrate the feasibility and universality of the related technologies in this paper.

Adaptive H∞ event-triggered load frequency control in islanded microgirds with limited spinning reserve constraints

Using an islanded microgrid (MG) with large-scale integration of renewable energy is the most popular way of solving the reliable power supply problem for remote areas and critical electrical users. However, compared with traditional power systems, the limited spinning reserves and network communication bandwidth may cause weak frequency stability in the presence of stochastic renewable active outputs and load demand fluctuations. In this paper, an adaptive event-triggered control (ETC) strategy for a load frequency control (LFC) system in an islanded MG is proposed. First, a bounded adaptive event-triggered communication scheme is designed. This not only saves on network resources, but also ensures that the control center has a sensitive monitoring ability for the MG operating status when the frequency deviations have been effectively damped. Secondly, by fully considering the spinning reserve constraints and uncertain communication delays, the LFC system is described as a nonlinear model with saturation terms. Design criteria for ETC parameters are strictly deduced based on Lyapunov stability theory. Finally, an ETC parameter optimization algorithm based on random direction search is developed to reconcile the bandwidth occupancy and control performance. The effectiveness of the proposed method is verified in an MG test system.

Adaptive event-triggered control for networked interconnected systems with cyber-attacks

This paper investigates the secure adaptive event-triggered controller design for networked interconnected systems (NISs) with cyber-attacks. Firstly, an adaptive event-triggered mechanism (AETM) with dynamic threshold parameter is adopted to economize the limited network bandwidth which takes the abrupt data into consideration. A model of cyber-attacks is established for NISs with consideration of the malicious cyber-attacks. On account of the model of cyber-attacks and AETM, a mathematical model of NISs is established. For the built system, the sufficient condition for the asymptotic stability of the system is obtained by making use of Lyapunov stability theory and linear matrix inequality (LMI) technique, and the design algorithm of the controller is proposed. Finally, a simulation example is given to verify the validity of the theoretical results.

Event-Triggered Adaptive Security Path Following Control for Unmanned Ground Vehicles Under Sensor Attacks

This paper is concerned with the event-triggered adaptive security control (ET-ASC) for the path following of networked unmanned ground vehicles (UGVs) subject to sensor attacks. Firstly, a security model is well established to capture the dynamics of path following control of UGVs under sensor attacks. Then, the ET-ASC with respect to correction signal is proposed to mitigate the effects of such sensor attacks. In what follows, two theorems, which include both input to state stability (ISS) criterion and controller design method, are carefully derived for the path following control of UGVs under the proposed ET-ASC scheme. The advantage of the proposed ET-ASC scheme lies in that it can actively amend the sensor attacks in an adaptive way and exclude Zeno phenomenon naturally. At last, a verification simulation experiment are conducted to show the effectiveness of the proposed ET-ASC method.

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-triggered adaptive finite time trajectory tracking control for Underactuated Vessel considering unknown time-varying disturbances

Abstract This paper aims to solve the finite-time trajectory tracking problem of underactuated surface ships under the influence of dynamic uncertainty, unknown external time-varying interference and limited communication resources, an event-triggered robust adaptive finite-time trajectory tracking control method for underactuated ships is designed by combing the existing trajectory tracking control methods and engineering needs in actual navigation. It can obviously improve the tracking accuracy of the ship, and complete the tracking task safely and efficiently. This scheme transforms the composite uncertain vector synthesized by uncertain parameters and external disturbances into a linear parameterized form. Next, considering the limitation of communication resources, a relative threshold event triggering mechanism is introduced to further extend the triggering time interval on the basis of the fixed threshold triggering scheme. Then, an event-triggered robust adaptive finite-time trajectory tracking control scheme is designed for underactuated ships, and a rigorous stability proof is provided for the finite-time trajectory tracking control scheme designed above through Lyapunov stability theory. Simulation experiment is carried out in MATLAB and the results show that the finite-time trajectory tracking control scheme proposed in this paper can effectively solve the problems of dynamic uncertainty, unknown time-varying interference from the outside world, and limitation of communication resources. This paper can provide theoretical support for the autonomous navigation of intelligent ships.

Dynamic Event-Triggered Adaptive Tracking Control for Multiagent Systems with Power Exponential Function Using Fuzzy Disturbance Observer

Dynamic Event-Triggered Adaptive Tracking Control for Multiagent Systems with Power Exponential Function Using Fuzzy Disturbance Observer

Adaptive Event-Triggered Control for Nonlinear Systems With Asymmetric State Constraints: A Prescribed-Time Approach

Finite/Fixed-time control yields a promising tool to optimize a system&#x0027;s settling time, but lacks the ability to separately define the settling time and the convergence domain (known as <i>practically prescribed-time stability</i>, PPTS). We provide a sufficient condition for PPTS based on a new piecewise exponential function, which decouples the settling time and convergence domain into separately user-defined parameters. We propose an adaptive event-triggered prescribed-time control scheme for nonlinear systems with asymmetric output constraints, using an exponential-type barrier Lyapunov function. We show that this PPTS control scheme can guarantee tracking error convergence performance, while restricting the output state according to the prescribed asymmetric constraints. Compared with traditional finite/fixed-time control, the proposed methodology yields separately user-defined settling time and convergence domain without the prior information on disturbance. Moreover, asymmetric state constraints can be handled in the control structure through bias state transformation, which offers an intuitive analysis technique for general constraint issues. Simulation and experiment results on a heterogeneous teleoperation system demonstrate the merits of the proposed control scheme.

Event-Triggered Adaptive Time-Varying Formation Tracking of Multi-Agent System With a Leader of Nonzero Input

In this paper, the time-varying formation (TVF) tracking problem is studied for multi-agent systems (MAS) with the leader’s control input is nonzero. First assuming that the agents’ states are unavailable, the state observer is therefore designed to deal with this situation. Then, a novel kind of event-triggered (ET) adaptive output feedback TVF tracking controller for linear MASs is put forward. According to Lyapunov stability theory, the result implies that under the appropriate assumptions the proposed controller is implementable without using any global information. Furthermore, for the designed ET condition, Zeno behavior doesn’t manifest in any agent. Furthermore, numerical simulation is given to validate the performance of the design techniques.

Event-Triggered Adaptive Fuzzy PI Control of Uncertain Fractional-Order Nonlinear Systems With Full-State Constraints

This article is devoted to the adaptive fuzzy proportional-integral (PI) control of uncertain fractional-order (FO) strict-feedback nonlinear systems subject to full-state constraints (FSCs) and external disturbances via an event-triggered (ET) control technique. First, fuzzy logic systems are introduced to approximate unknown nonlinear functions. Second, a novel adaptive FOPI controller with a simple structure and low calculation cost is developed, and it is able to determine its PI gains adaptively and automatically without involving manual operation or trial and error procedures, which is an improvement compared with the traditional PI control scheme. Third, a relative-threshold-based ET controller is constructed so that the communication load from the controller to the actuator can be significantly decreased, and there is no Zeno behavior. Then, a barrier Lyapunov function is introduced into the backstepping recursive process to avoid FSC violations. Moreover, all closed-loop signals are bounded, and the output is driven to follow the desired output through the FO Lyapunov stability analysis. In particular, the proposed approach does not require a priori knowledge of the FO derivative of the reference signal. Finally, the feasibility of the proposed scheme is verified by numerical simulations.

Adaptive Dynamic Event-Triggered Fault-Tolerant Consensus for Nonlinear Multiagent Systems With Directed/Undirected Networks.

The fault-tolerant consensus of nonlinear multiagent systems (MASs) is studied by using the dynamic event-triggered control and the adaptive control techniques. First, a general dynamic adaptive event-triggered mechanism (DAETM) is proposed, which promotes and improves many existing dynamic event-triggered mechanism and static event-triggered mechanism. On this basis, a new distributed dynamic adaptive event-triggered fault-tolerant controller (DDAETFTC) is designed. Then, two simple and clear criteria are derived, respectively, to ensure consensus can be reached asymptotically for nonlinear MASs with directed networks and with undirected networks under the new DDAETFTC. The obtained results also can apply to linear MASs. Furthermore, it is proven that there is no agent to show the Zeno behavior in MASs under the new DAETM. Finally, an example is given to simulate the obtained results.

Event-Based Finite-Time Control for Nonlinear Multiagent Systems With Asymptotic Tracking

In this paper, an adaptive neural finite-time event-triggered consensus tracking problem is studied for nonlinear multi-agent systems (MASs) under directed graphs. Firstly, the unknown nonlinear functions of MASs can be approximated by neural networks. Then, a distributed adaptive event-triggered control (ETC) scheme is proposed via command filter and backstepping technique. The newly designed control scheme can not only circumvent the problem of the explosion of complexity, but also remove the singularity issue typical of conventional backstepping technique. In the meanwhile, an event-triggered mechanism with a dynamic threshold is devised to reduce the waste of network resources. Moreover, by using a novel finite-time stability criterion, it can be proved that the closed-loop system is finite-time stable and the consensus tracking errors can reach zero as time approaches to infinity. Finally, a numerical example is given to validate the feasibility of the proposed scheme.