Observer-based Event-triggered Control Research Articles

Observer-based Event-triggered Fuzzy Control for Switched Multi-agent Systems with State Constraints and Sensor Faults

Observer-based Event-triggered Fuzzy Control for Switched Multi-agent Systems with State Constraints and Sensor Faults

Disturbance observer-based event-triggered impulsive control for nonlinear systems with unknown external disturbances

Input-to-state practical stability (ISpS) of a kind of nonlinear systems suffering from unknown exogenous disturbances is explored in this article, where a disturbance observer is established to estimate the information of the exogenous disturbances. To achieve ISpS of the system, the impulsive controller as well as state-feedback controller are both considered to regulate the discrete and continuous dynamics of the system, respectively. Especially, a novel disturbance observer-based event-triggered mechanism is devised to decide the release of impulsive control signal. Furthermore, several adequate conditions are given for excluding the occurrence of Zeno phenomenon. To confirm the feasibility of the proposed results, two numerical instances and their corresponding simulation results are presented.

Fast Finite-Time Observer-Based Event-Triggered Consensus Control for Uncertain Nonlinear Multiagent Systems with Full-State Constraints.

This article studies a class of uncertain nonlinear multiagent systems (MASs) with state restrictions. RBFNNs, or radial basis function neural networks, are utilized to estimate the uncertainty of the system. To approximate the unknown states and disturbances, the state observer and disturbance observer are proposed to resolve those issues. Moreover, a fast finite-time consensus control technique is suggested in order to accomplish fast finite-time stability without going against the full-state requirements. It is demonstrated that every signal could be stable and boundless, and an event-triggered controller is considered for the saving of resources. Ultimately, the simulated example demonstrates the validity of the developed approach.

Observer-Based Boundary Stabilization of Coupled Semilinear Reaction-Diffusion Neural Networks With Spatially Varying Coefficients via Event-Triggered Controller.

The aim of this article is to propose an observer-based event-triggered Robin boundary control strategy for the exponential stabilization of the coupled semilinear reaction-diffusion neural networks with spatially varying coefficients. Toward this aim, we design an observer to estimate the value of system states by using some of these system values as the available measurement. An observer-based event-triggered boundary stabilizer is then presented to exponentially stabilize the considered systems with the Zeno behavior being excluded. Throughout this article, the main used method is backstepping, which yields an explicit expression of the control formulae. Moreover, we see that the proposed event-triggered boundary control scheme can ensure the desired level of control performance with fewer control law updates. A numerical example is finally given to illustrate the effectiveness of our proposed method.

Observer-based event-triggered time-varying formation control of linear multi-agent systems with distributed infinite delays

Compared with bounded delays, distributed infinite delays are more general in practical systems. Event-triggered control can effectively reduce energy consumption and communication costs. This paper addresses time-varying formation control of general linear multi-agent systems with distributed infinite delays in both of their inputs and outputs. An observer-based event-triggered formation control protocol considering distributed infinite delays is proposed, which is related to the combined observed information and some formation compensation signals at triggering time instants. By utilizing inequality techniques, the desired time-varying formation can be implemented while Zeno-behavior is excluded. Some numerical simulations are carried out for demonstrating the validity of theoretical results.

Disturbance Observer-Based Event-Triggered Control of Switched Positive Systems

Disturbance Observer-Based Event-Triggered Control of Switched Positive Systems

Disturbance Observer-Based Event-Triggered Control of Vehicle Suspension With Finite-Time Prescribed Performance

In this article, we develop a disturbance observer-based event-triggered control strategy for uncertain active suspension systems (ASSs), while guaranteeing the transient behavior and reducing the communication burden over the controller area network (CAN). In order to improve the transient and steady-state performances of ASSs, a novel global finite-time prescribed performance function is proposed. Unlike the existing vehicle suspension results on prescribed performance control, the proposed scheme is able to relax the restriction that the initial value depends on the prescribed function. Meanwhile, the proposed approach ensures that the tracking error is stabilized in a prescribed zone in a finite time independent of the initial condition. Then, a performance function dependent event-triggered mechanism is suggested to alleviate the bandwidth occupancy on the CAN while obtaining satisfactory tracking performance. In addition, a disturbance observer is employed to estimate the lumped uncertainty in ASSs. All signals in the resulting close-loop ASSs are ensured bounded. Finally, the effectiveness of the developed methodology are demonstrated in simulation results.

Observer-based event-triggered boundary control of the one-phase Stefan problem

This paper presents an observer-based event-triggered boundary control strategy for the one-phase Stefan problem, utilising the position and velocity measurements of the moving interface. The design of the observer and controller is founded on the infinite-dimensional backstepping approach. To implement the continuous-time observer-based controller in an event-triggered framework, we propose a dynamic event triggering condition. This condition specifies the instances when the control input must be updated. Between events, the control input is maintained constant in a Zero-Order-Hold manner. We demonstrate that the dwell-time between successive triggering moments is uniformly bounded from below, thereby precluding Zeno behaviour. The proposed event-triggered boundary control strategy ensures the well-posedness of the closed-loop system and the satisfaction of certain model validity conditions. Additionally, the global exponential convergence of the closed-loop system to the setpoint is established using Lyapunov approach. A simulation example is provided to validate the theoretical findings.

Coordination of large-scale systems with unknown external disturbances: an observer-based event-triggered control scheme

ABSTRACT This paper investigates the coordination control of large-scale systems (LSSs) with unknown external disturbances. The disturbances exist in the channels from the controllers to the actuators. To compensate the impact of disturbances, an extended observer using the output states is constructed, and an observer-based event-triggered controller is designed to save communication resources. Moreover, based on the event-triggering strategy, a controller using dynamic information estimation is designed, and Zeno behavior is further excluded. Finally, a DC micro-grid model is used for simulations to verify the effectiveness of the proposed control scheme.

Observer-Based Event-Triggered Optimal Control for Nonlinear Multiagent Systems With Input Delay via Reinforcement Learning Strategy

Observer-Based Event-Triggered Optimal Control for Nonlinear Multiagent Systems With Input Delay via Reinforcement Learning Strategy

Observer-Based Event-Triggered Consensus Control of Multi-Agent Systems With Time-Varying Communication Delays

Observer-Based Event-Triggered Consensus Control of Multi-Agent Systems With Time-Varying Communication Delays

Observer-based event-triggered recursive optimal tracking control for a class of strict-feedback nonlinear systems

In this paper, an innovative event-triggered optimal tracking control algorithm is proposed for input saturated strict-feedback nonlinear systems with unknown dynamics. In order to reduce the requirement of configuring a complete suit of sensors and enhance the reliability of the controlled system, a neural networks (NNs) based adaptive state observer is developed firstly to reconstruct the system states. Subsequently, based on the state estimation information, a hybrid-triggered feedforward controller is designed to transform the original tracking control problem into an equivalent regulation issue, which is then solved by developing an event-triggered optimal controller. Therefore, the final controller consists of a hybrid-triggered feedforward controller and an event-triggered optimal controller. In order to make the actual input signals of the two controllers be updated simultaneously, a synchronization-oriented triggering rule is established by using multiple triggering errors. By virtue of this unique framework, the proposed control scheme can not only minimize the predefined cost function, but also greatly reduce the data transmission. What is more, the convergence properties of the proposed control strategy are achieved by using Lyapunov theory. It is important to note that unlike the widely adopted observer-controller framework, where the separation principle holds for the design of the state observer, there is a considerable coupling relationship between the error dynamics of the state observer and the event-triggered optimal controller in this paper. The distinguishing feature of the proposed method is its ability to ensure a satisfactory level of precision in both state estimation and tracking control, even in the presence of control saturation issues. At last, the proposed control strategy is applied to the tracking control problem of a high-order robot system and marine surface vehicle to demonstrate its effectiveness.

Disturbance Observer-Based Event-Triggered Adaptive Command Filtered Backstepping Control for Fractional-Order Nonlinear Systems and Its Application

This paper considers the disturbance observer-based event-triggered adaptive fuzzy tracking control issue for a class of fractional-order nonlinear systems (FONSs) with quantized signals and unknown disturbances. To improve the disturbance rejection ability, a fractional-order nonlinear disturbance observer (FONDO) is designed to estimate the unknown composite disturbances. Furthermore, by combining an improved fractional-order command-filtered backstepping control technique and an event-triggered control mechanism, an event-triggered adaptive fuzzy quantized control scheme is established, which guarantees the desired tracking performance can be achieved even in the presence of network constraint. Finally, the validity and superiority of the theoretic results are verified by a fractional-order horizontal platform system.

Distributed Observer-Based Event-Triggered Load Frequency Control of Multiarea Power Systems Under Cyber Attacks

Information and communication technology tremendously facilitates the operation efficiency and economy of modern power systems in recent years. However, risks such as bandwidth constraints and malicious attacks threaten the secure load frequency control (LFC) of power systems. To mitigate such risks, this paper proposes distributed observer-based event-triggered LFC schemes for multi-area power systems under cyber attacks. Considering the practical situation that only local system output information may be available, distributed observer-based LFC schemes are designed. Meanwhile, to reduce the communication burden, an event-triggered mechanism is adopted to design control laws, where both static and dynamic event-triggered approaches are taken and the dynamic one is proved to be more economical in terms of control cost. Verifiable sufficient conditions are established to guarantee the stability of the closed-loop system in the presence of cyber attacks and the controller gains are explicitly derived. Finally, validation studies on a three-area interconnected power system are carried out to demonstrate the proposed control schemes. <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">Note to Practitioners</i> —Load frequency is a crucial index for evaluating the quality of electric energy and thus LFC has brought considerable attention in the area of power systems control. Although many achievements have been made on the LFC of multi-area power systems, the risks such as bandwidth constraints and malicious attacks affect the normal operation of LFC due to the interconnection between different power systems. To deal with these risks, this paper focuses on designing event-triggered LFC to guarantee the stability of the frequency deviation while reducing the communication burden and mitigating cyber attacks. More importantly, the proposed event-triggered LFC is designed based on an observer and can be implemented in a distributed manner, which is relatively practical in real applications. The results presented in this paper aim to provide a helpful reference for stable and secure LFC design of multi-area power systems, such that the corresponding application research can be promoted.

Nonfragile observer-based event-triggered fuzzy tracking control for fast-sampling singularly perturbed systems with dual-layer switching mechanism and cyber-attacks

This paper investigates the problem of nonfragile observer-based tracking control for a class of fuzzy fast-sampling singularly perturbed systems (SPSs) with sensor saturation, which subject to event-triggered scheme and random cyber-attacks. The switching topology of the fast-sampling SPSs is dominated by a dual-layer switching mechanism, in this case, the Markov process in the underlying system is nonhomogeneous and its time-varying transition probabilities (TPs) are governed by a persistent dwell-time switching signal. First, in order to avoid asynchronous phenomenon of premise variable between the fuzzy fast-sampling SPSs and the fuzzy controller under network environments, the non-parallel distributed compensation (non-PDC) technique is applied to improve the design flexibility and reduce the conservativeness of the results. Furthermore, a novel fuzzy tracking control design scheme is proposed, in which integrating the fuzzy nonfragile observer and reference model signal into the synthetic design of the tracking controller can be expected to reduce the tracking error. Second, by constructing a well-designed time-delay and mode-dependent Lyapunov function, some sufficient conditions are derived such that the closed-loop system is mean-square exponential stable and with extended dissipative tracking performance. Finally, the effectiveness and applicability of the proposed control protocol are illustrated by two simulation examples.

Observer-Based Asynchronous Event-Triggered Bipartite Consensus of Multiagent Systems Under False Data Injection Attacks

This paper investigates bipartite consensus of multi-agent systems under unknown false data injection attacks. Attacks are launched in the channels from the controller to the actuator. To compensate the impact of attacks, an extended observer including the absolute output information is firstly constructed, and then an observer-based event-triggered controller is designed to save resources. Moreover, an observer-based fully asynchronous event-triggered controller is proposed to further reduce the communication cost. Sufficient criteria are deduced to guarantee bipartite consensus and Zeno behavior is further ruled out. Finally, numerical examples are given to illustrate the effectiveness of the derived results.

Dynamic State Observer-Based Event-Triggered ISM Load Frequency Control of Power Systems With Disturbance Observer

This article proposes a new dynamic observer-based event-triggered integral sliding mode control incorporating disturbance observer (DO) for the load frequency control of a multiarea interconnected power system (IPS) considering load disturbances and uncertainties. To improve the system performance and reduce the cost implementation, first a dynamic observer is designed for the IPS to achieve the state estimation. Then, to reduce the chattering effect and improve the robust performance, a DO is designed to obtain the estimated of the unmatched disturbances. To further reduce the chattering effect and computational burden, based on the obtained state estimation and the estimated disturbances, two integral sliding surfaces are proposed. The periodic-time one that is proposed to ensure the robust performance from the initial-time and the time-triggered one that is proposed to obtain the event-triggered control law. Utilizing the Lyapunov theory, the ultimate boundedness stability of the controlled system is studied and sufficient conditions are derived by solving a set of offline linear matrix inequalities. During the system implementation, it is also verified that the controlled system is Zeno-free. Finally, the proposed control strategy is compared with some existing studies and the simulation results demonstrate the effectiveness and the superiority over the existing approaches.

Observer-Based Event-Triggered Adaptive Control for Nonlinear Multiagent Systems With Unknown States and Disturbances.

Based on radial basis function neural networks (RBF NNs) and backstepping techniques, this brief considers the consensus tracking problem for nonlinear semi-strict-feedback multiagent systems with unknown states and disturbances. The adaptive event-triggered control scheme is introduced to decrease the update times of the controller so as to save the limited communication resources. To detect the unknown state, external disturbance, and reduce calculation workload, the state observer and disturbance observer as well as the first-order filter are first jointly constructed. It is shown that all the output signals of followers can uniformly track the reference signal of the leader and all the error signals are uniformly bounded. A simulation example is carried out to further prove the effectiveness of the proposed control scheme.

Velocity Observer-Based Event-Triggered Adaptive Fuzzy Attitude Takeover Control of Spacecraft With Quantized Quaternion

In this paper, the spacecraft attitude takeover control (ATC) problem with limited communication and the unavailable angular velocity using cellular satellites is addressed. First, a dynamic uniform quantizer (DUQ) is proposed to quantize unit quaternion between sensor cellular satellites and controller cellular satellite. Second, an adaptive fuzzy observer is proposed to estimate the unavailable angular velocity. Further, between controller cellular satellite and actuator cellular satellites, an event-triggered mechanism (ETM) is provided to lighten the communication burden. By combing DUQ, adaptive fuzzy observer, the adaptive fuzzy control law and the ETM is established. The stability of the ATC systems with the proposed control method is ensured. Finally, the simulation results illustrate the effectiveness of the developed control laws.

Observer-Based Event-Triggered Control for Interval Type-2 Fuzzy Networked System With Network Attacks

This paper is focused on the adaptive event-based interval type-2 (IT-2) fuzzy security control problem for networked control systems with multiple network attacks. In order to save the network resources, this paper proposes an improved adaptive event-triggered model, which can adjust the threshold dynamically according to the change of current signal and previous triggering signal. In addition, due to the change of external environment, the impact of randomly occurring output bias is considered in the systems. Taking the effects of multiple network attacks and adaptive event-triggered scheme into consideration, a class of augmented error fuzzy system model is established. Next, some sufficient conditions are obtained for the stochastic stability with an <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"><tex-math notation="LaTeX">$H_{\infty }$</tex-math></inline-formula> performance index via the Lyapunov stability analysis method. The corresponding paraments of the IT-2 fuzzy controllers and observers are also derived by some linear matrix inequalities (LMIs). Finally, two simulation examples are given to support the advantages of the proposed method.