Event-triggered Control Problem Research Articles

Robust $ H_\infty $ resilient event-triggered control design for T-S fuzzy systems

<p style='text-indent:20px;'>This paper investigates the resilient <inline-formula><tex-math id="M2">\begin{document}$ H_\infty $\end{document}</tex-math></inline-formula> event-triggered control problem for Takagi-Sugeno fuzzy system with time-varying delay and external disturbance. Contrary to some existing results, the considered event-triggered conditions are verified only at each sampling instant because it is difficult to prove Zeno-freeness for a continuous event-triggered mechanism in the presence of external disturbance. Furthermore, by constructing an appropriate Lyapunov-Krasovskii functional, sufficient conditions are derived in the form of linear matrix inequalities to ensure the asymptotic stability and the <inline-formula><tex-math id="M3">\begin{document}$ H_\infty $\end{document}</tex-math></inline-formula> performances of closed-loop systems. More precisely, the proposed control design not only improve robust performance but also save the communication resources. Finally, the obtained theoretical results are verified through numerical simulation, which demonstrate the efficiency and advantages of the proposed method.</p>

Fuzzy Weighted Memory Event-Triggered Control for Networked Control Systems Subject to Deception Attacks

This paper considers the event-triggered control problem for a class of Networked Control Systems (NCS) subject to transmission delays and stochastic deception attacks. A new fuzzy weighted memory event-triggered mechanism is proposed to reduce the network bandwidth consumption and data transmission rates. In this context, a new fuzzy weighted memory state feedback controller is proposed to stabilize the closed-loop NCS. Considering the security problem of NCS, a randomly occurring deception attack model is employed, assuming bounded malicious signals injected by the attacker. Based on a suitable Lyapunov-Krasovskii functional, a design methodology is proposed, in terms of linear matrix inequalities, to synthesize both trigger parameters and NCS controller gains. Finally, a numerical example is considered to illustrated the effectiveness of proposed results, compared to previous ones from the literature.

Predictor-based periodic event-triggered control for nonlinear uncertain systems with input delay

In this paper we investigate the problem of predictor-based periodic event-triggered control for a class of nonlinear uncertain systems subject to input delay. When only sampled-data output is available, a novel predictor-based continuous-discrete observer is first designed to estimate system state, and an event-triggered controller is second proposed to globally exponentially stabilize the nonlinear uncertain system. Under the proposed control method, the effects of input delay and sampling of output can be considerably compensated thanks to prediction technique. As a byproduct, the Zeno behavior is avoided in nature since the proposed event-triggering mechanism is detected in the form of discrete-time. Some sufficient stability conditions on maximum allowable sampling period and input delay are presented by using feedback domination technique and small-gain argument.

Event‐triggered adaptive neural asymptotic tracking of uncertain constrained nonlinear systems without feasibility condition

SummaryIn this article, an event triggered control problem is investigated for uncertain nonlinear systems with full state constraints. First, the original‐constrained system is converted into an equivalent totally unconstrained one by using a state dependent function. Then, an event‐triggered adaptive neural‐network controller is designed to reduce the communication burden. In addition, rigorous theoretical analyses have been conducted to show that the proposed controller can ensure that all signals in the closed‐loop control system are bounded and that the asymptotic convergence with zero tracking error is achieved. In the meanwhile, the state constrains are not violated. Finally, the effectiveness of the presented control scheme is verified through the simulation results.

Event-triggered synchronization control of complex networks with adaptive coupling strength

The event-triggered synchronization control problem is concerned for a class of complex networks with nonlinearly coupling function and adaptive coupling strength. Given a state-based event-trigger mechanism and the threshold, an event-triggered control method is introduced to make complex networks achieve exponential synchronization. By combining the Lyapunov stability theory and the knowledge of graph theory, a sufficient condition is established such that complex networks can achieve exponential synchronization. Then, the feasibility of the event-triggered control is analyzed. Moreover, the second-order Kuramoto oscillators is taken into account. And the event-triggered control strategy is used to make the oscillators achieve exponential synchronization. Meanwhile, two simulation results about the second-order Kuramoto oscillators are given to show the effectiveness of results.

Finite-time event-triggered control for switched affine systems with time-varying delay under state-dependent switching

Finite-time event-triggered control problem for switched affine systems with time-varying delay is investigated in this paper. A dynamical event-triggered scheme with multiple parameter matrices is proposed to avoid the waste of communication resources, which is more general than some existing event-triggered schemes with a common parameter matrix. By applying the proposed event-triggered scheme, a state-dependent switching signal and a state feedback controller are designed. By utilising an appropriate Lyapunov–Krasovskii functional and Metzler matrices, sufficient conditions for the existence of controller gains are firstly proposed such that the closed-loop system is finite-time bounded with finite-time disturbance attenuation performance. It is also proved that there is a lower bound between two adjacent triggers, i.e. Zeno phenomenon can be avoided. Finally, two numerical examples are provided to illustrate the effectiveness of the proposed method.

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.

Periodic event-triggered formation control for multi-UAV systems with collision avoidance

In this paper, periodic event-triggered formation control problems with collision avoidance are studied for leader–follower multiple Unmanned Aerial Vehicles (UAVs). Firstly, based on the Artificial Potential Field (APF) method, a novel sliding manifold is proposed for controller design, which can solve the problem of collision avoidance. Then, the event-triggered strategy is applied to the distributed formation control of multi-UAV systems, where the evaluation of the event condition is continuous. In addition, the exclusion of Zeno behavior can be guaranteed by the inter-event time between two successive trigger events have a positive lower bound. Next, a periodic event-triggered mechanism is developed for formation control based on the continuous event-triggered mechanism. The periodic trigger mechanism does not need additional hardware circuits and sophisticated sensors, which can reduce the control cost. The stability of the control system is proved by the Lyapunov function method. Finally, some numerical simulations are presented to illustrate the effectiveness of the proposed control protocol.

A two-event-generator scheme for event-triggered control of uncertain NCSs under deception attacks

This paper addresses the event-triggered control problem of discrete-time uncertain networked control systems under random deception attacks. In order to deal with a network resource constraint, a novel two-event-generator scheme over both sensor-to-controller and controller-to-actuator channels is proposed to reduce the transmission frequency of system states and control commands, while maintaining desired system performance. More specifically, one of the event-generators is a time-varying memory-based event-triggered scheme (METS), and the other is the traditional event-triggered scheme (ETS). On the other hand, in order to incorporate network security, a new model of memory-based NCSs is established under random deception attacks. Then, sufficient conditions for preserving the asymptotic stability of uncertain NCSs are proposed by using the Lyapunov functional method. Furthermore, co-design criteria are derived for determining both the memory-based state feedback controller gains and event-triggering parameter matrices. Finally, the effectiveness of the proposed methods is verified by a quarter-car suspension system.

Dynamic Event-Triggered Predictive Control for Interval Type-2 Fuzzy Systems with Imperfect Premise Matching.

This paper investigates the dynamic event-triggered predictive control problem of interval type-2 (IT2) fuzzy systems with imperfect premise matching. First, an IT2 fuzzy systems model is proposed, including a dynamic event-triggered mechanism, which can save limited network resources by reducing the number of data packets transmitted, and a predictive controller, which can predict the state of the system between the two successful transmitted instants to deal with unreliable communication networks. Then, according to the Lyapunov stability theory and imperfect premise matching method, sufficient conditions for system stabilization and the controller gain are obtained. Finally, the validity of the proposed method is demonstrated by the numerical examples.

Event-triggered control of networked switched systems under network attacks

This paper is concerned with the event-triggered control (ETC) problem for switched systems in networked environments, which are suffered from denial-of-service (DoS) attack and deception attack. Considering that the packet in networked switched systems contains the sampled state and switching signal, DoS attack prevents the packet transmission to cause the zero input, while deception attack falsifies the packet to cause the asynchronous control input with nonlinear disturbance. First, the probabilistic characterization of invalid packet transmissions caused by two different attack models is constructed, namely the ratio of the number of packet transmissions suffering from network attacks to the total number of packet transmissions. Second, a suitable ETC scheme is designed to determine the next triggering instant, which guarantees that the value of Lyapunov function cannot exceed a given restriction and updates the control input at switching instant. After that, the average dwell time and control gains are designed to guarantee the almost sure asymptotic stability of such systems. Finally, a numerical simulation is given to verify the effectiveness of the theoretical results.

Adaptive-triggered asynchronous control for stochastic jumping systems under sliding mode

This paper investigates the problem of event-triggered asynchronous control for discrete-time stochastic jumping systems. A novel adaptive event-triggered (AET) strategy is proposed to save network resources, and two asynchronous control approaches are presented. First, an asynchronous feedback control method on adaptive triggered mechanism is proposed, and the mean-square exponentially stable of the closed-loop system is analysed. Second, the reduced-order model for discrete-time stochastic system is established to deal with the actuator faults. Furthermore, combining with the AET scheme, an asynchronous sliding-mode surface is designed such that the discrete-time reduced-order sliding-mode dynamics is yielded. Third, the stability analysis for the sliding-mode dynamics is discussed and the sliding-mode parameters are solved. Moreover, in order to compensate the actuator faults, an asynchronous sliding-mode controller is synthesised, and the reachability of the sliding-mode surface is analysed. Finally, two examples are given to demonstrate the potential of the developed scheme.

Event triggered control for fault tolerant control system with actuator failure and randomly occurring parameter uncertainty

The paper investigates the event-triggered control problem for fault tolerant control system with actuator failure and randomly occurring parameter uncertainty. Firstly, the hybrid event-triggered control scheme is adopted for the fault tolerant control system subjected to actuator failure and randomly occurring parameter uncertainty in this paper, which could greatly decrease the amount of network data transmission and save communication resources. By utilizing the delay system method, the event-triggered fault tolerant control system is modeled as a delay system. Then, by constructing appropriate Lyapunov–Krasovskii functional, sufficient conditions are derived in form of linear matrix inequalities (LMIs) to guarantee the system is stochastically passive with prescribed passive performance γ. The impact of the actuator fault and the random occurring parameter uncertainty are studied under the unified framework. Eventually, two simulation examples including F-404 aircraft engine system are presented to illustrate the effectiveness of the proposed theoretical findings.

Hybrid event-triggered and impulsive control for time-delay systems

In this paper, we study the problem of hybrid event-triggered control for a class of nonlinear time-delay systems. Using a Razumikhin-type input-to-state stability result for time-delay systems, we design an event-triggered control algorithm to stabilize the given time-delay system. In order to exclude Zeno behavior, we combine the impulsive control mechanism with our event-triggered strategy. In this sense, the proposed algorithm is a hybrid impulsive and event-triggered strategy. Sufficient conditions for the stabilization of the nonlinear systems with time delay are obtained by using Lyapunov method and Razumikhin technique. Numerical simulations are provided to show the effectiveness of our theoretical results.

Event-triggered adaptive NN tracking control with dynamic gain for a class of unknown nonlinear systems

An event-triggered tracking control problem is investigated for a class of unknown nonlinear systems in this paper. First, to approximate the unknown function, the radial basis function neural network is used. Then, we propose an event-triggered adaptive neural network control scheme with dynamic gain. Both the event-triggered mechanism in the controller-to-actuator channel and the dynamic gain in the sensor-to-controller channel are considered to reduce the communication load between the controller and the actuator and in the meantime to alleviate the burden of parameter adjustment as well. This scheme makes full use of the advantage that the dynamic gain is driven by the tracking error to ensure that the system output signal can track the reference signal within a prespecified accuracy without adjusting the parameters in use. Moreover, a detailed theoretical proof is given to illustrate that Zeno behavior can be excluded under the designed event-triggered controller. Finally, a simulation example is provided to show the effectiveness of our control scheme.

Switching-Like Event-Triggered Control for Networked Markovian Jump Systems Under Deception Attack

This brief deals with the event-triggered control problem for networked Markovian jump systems subject to deception attack. When deception attack is activated, it causes the asynchronous switching and falsifies the sampled state as the nonlinear disturbance. Then, based on the variation between two consecutive sampled states and the signals of switching and deception attack, a switching-like event-triggered scheme is proposed to adjust the threshold. Sufficient conditions are derived to ensure the mean-square exponential input-to-state practical stability for such systems. After that, the homotopy method is employed to obtain the state-feedback matrix with constrained structure. Finally, a model about connected vehicle systems is given to demonstrate the effectiveness of the design techniques.

Event-triggered boundary control of a flexible manipulator with uncertain end load

In this study, we consider the event-triggered boundary control problem of a single-link flexible manipulator with uncertain end load. The flexible manipulator is modelled by partial differential equations (PDEs). Based on the PDE model, an event-triggered control strategy is proposed to achieve angular position tracking and vibration elimination, while alleviating the communication burden of the signal transmission between controller and actuator. The relative threshold strategy used in triggering event mechanism can adjust the update interval according to the size of the control input. The designed adaptive law with projection mapping operator can deal with undertain end load. The proposed control scheme can guarantee that all signals in the closed-loop system are uniformly ultimately bounded, and the angular tracking error and vibration converge to small zero neighbourhoods by reasonable selection of design parameters. Moreover, the Zeno phenomenon is precluded. Numerical simulation results elucidate the effectiveness of the designed control strategy.

Resilient adaptive event-triggered H∞ control for networked stochastic control systems under denial-of-service attacks

This paper addresses the problem of resilient adaptive event-triggered control (AETC) for networked stochastic control systems (NSCSs) in the presence of the external disturbance and the energy-constrained, nonperiodic denial-of-service (DoS) attacks. A novel adaptive event-triggered scheme (AETS) that considers the effect of the energy-constrained, nonperiodic DoS attacks on the communication network is proposed to reduce the usage of system resources and adapt the variation of the plant state, and the model of closed-loop control system is established in the framework of time-delay systems and switched systems. Then, based on the Lyapunov stability theory, the stability criterion and the co-design algorithm are derived, which are used to ensure that the closed-loop control system is stochastically exponentially stable (SES) with an [Formula: see text] disturbance attenuation performance and to implement the co-design of state-feedback controller and proposed AETS, respectively. Unlike the network-based [Formula: see text] control approach for NSCSs in the existing literature, the resilient adaptive event-triggered network-based [Formula: see text] control approach proposed in this paper not only can considerably save the usage of system resources, but also can be resilient towards the energy-constrained, nonperiodic DoS attacks. Finally, a resilient AETC for the F16 aircraft system shows the effectiveness and superiority of proposed strategy.

Finite-time distributed event-triggered formation control for quadrotor UAVs with experimentation

This paper deals with the finite-time event-triggered formation control problem for multiple quadrotor unmanned aerial vehicles (UAVs) with unknown external disturbances. Novel adaptive distributed robust event-triggered controllers without/with finite-time extended state observer (FTESO) are developed based on adaptive terminal sliding mode (TSM) control method to save control update times and reduce chattering times simultaneously. It is proved that the proposed control strategies guarantee that all the closed-loop signals are practically finite-time stable. Moreover, the proposed controllers are fully distributed without the global information that is related to the communication topology matrix H. Meanwhile, the controller with FTESO is anti-disturbance. Zeno behavior is excluded by the strictly positive sampling intervals. Finally, the efficiency of the proposed control algorithms is illustrated by numerical simulations and three bebop2 quadrotor UAVs experimentation.

Event-triggered active disturbance rejection control for a class of networked systems with unmatched uncertainties: Theoretic and experimental results

In this work, an event-triggered control problem for a class of networked systems with unmatched uncertainties is investigated based on an active disturbance rejection control approach. To estimate the effect of unmatched uncertainties, a bank of extended state observers with guaranteed convergence is proposed. Based on the obtained estimates, a tracking-differentiator-enabled Zeno-free event-triggering condition is introduced with reduced sampling cost. An event-triggered controller is then designed to guarantee the closed-loop stability of the networked system with unmatched uncertainties, leveraging a backstepping control approach. Implementation issues of the proposed approach are discussed, and the effectiveness of the results is illustrated through experimental results on a DC torque motor platform.