Intermittent Control Strategy Research Articles

Exponential synchronization of fractional-order T–S fuzzy complex multi-links networks with intermittent dynamic event-triggered control

In this paper, the exponential synchronization problem for fractional-order T–S fuzzy complex multi-links networks under an intermittent dynamic event-triggered control (IDE-TC) strategy is discussed. To this end, a new triggering rule with a dynamical variable is first introduced, including some available static triggering rules as its particular form. Then, it is proved that the applied dynamical variable is positive by using some properties of the Mittag-Leffler function. Hence, the inter-event time between any two successive triggering moments can be enlarged than static event-triggered results. Additionally, there is a guaranteed positive minimum inter-event time for each sample path solution of systems. Based on the Lyapunov method and the graph theory, exponential synchronization criteria of the proposed networks under the IDE-TC strategy is deduced. Finally, the validity and feasibility of the derived theoretical results are investigated by an application with simulations.

Intermittent Flow Control Schemes for Heat Stress Mitigation in Lactating Sows on a Floor Cooling Pad

The Purdue hog cooling pad has previously been demonstrated to mitigate heat stress in lactating sows by conductively transferring heat from a sow to cool water running through an integral heat exchanger. Coolant effectiveness, which describes how much heat is removed per volume of water flushed through the cooling pad, is used to compare the operation under varying conditions. Past studies have indicated that the intermittent flow of cooling water achieves a greater coolant effectiveness than continuous flow operational schemes. An electronic control system was implemented with the current cooling pad design to allow for the automated control of a solenoid valve to create the intermittent flow conditions. All testing was performed using 18 ± 1 °C inlet water. Potential control schemes were categorized into two groups, temporal and temperature threshold. The temporal schemes opened the solenoid for 30 s, enough time to flush the entire contents of the cooling coils, before closing for 3, 6, or 9 min. The temperature threshold control schemes utilized feedback from thermal probes embedded beneath the surface of the cooling pad to open the solenoid for 30 s, when a maximum surface temperature was detected. Trigger temperatures of 28.0, 29.5, or 31.0 °C were used. The temperature threshold control schemes achieved greater heat transfer rates (348, 383, 268 W) compared to the temporal control schemes (324, 128, 84 W). The cooling effectiveness for all control schemes ranged from 46.6 to 64.7 kJ/L. The tested intermittent flow control schemes in this study achieved greater cooling effectiveness than continuous flow systems from previous studies (time: 51 kJ/L; temperature: 61 kJ/L; steady: 5.8 kJ/L), although the temporal control schemes exhibited lower heat transfer rates (time: 180 W; temperature: 330 W; steady: 305 W).

Synchronization of Euler-Lagrangian networks: a periodic intermittent dynamic event-triggered control strategy

In this paper, the synchronization problem of Euler–Lagrange networks is studied by designing periodic intermittent dynamic event-triggered control strategy. The synchronization of all agents is successfully realized by injecting negative comments into the discontinuous interval of the agents described by the Euler–Lagrange systems. Different from the traditional intermittent event-triggered control strategy, the control strategy proposed in this study introduces internal dynamic variables to expand the sampling interval of the event-triggered mechanism, thereby improving resource utilization efficiency. In addition, the event trigger instants of each agent are asynchronous. By using graph theory and Lyapunov method, the synchronization criteria of Euler–Lagrange networks are derived. The effectiveness of the proposed control scheme is verified by simulations for the Euler-Lagrangian network composed of six two-link rotating manipulators.

Fixed-time consensus problem for uncertain multi-agent systems with continuous and intermittent control

This paper addresses the fixed-time consensus issue in uncertain multi-agent systems (MAS). It introduces novel estimation methods for the maximum settling time, which considers all controller components but may also have less conservatism than traditional methods. Based on these results, a distributed control scheme and the corresponding consensus criterion are proposed, enabling MAS to achieve a fixed-time consensus and provide a more accurate estimation of the maximum settling time than the traditional method. Additionally, a distributed intermittent control scheme is also provided to enable the MAS to solve the issue of practical fixed-time consensus and be controlled only in a series of disjoint periods. Moreover, considering the case where the MAS has no external disturbance, another distributed intermittent control scheme is introduced to achieve fixed-time consensus under a directed topology. Finally, the results are supported by numerical examples.

Generalized synchronization of two-layer networks based on intermittent control strategy

Generalized synchronization of two-layer networks based on intermittent control strategy

How the brain can be trained to achieve an intermittent control strategy for stabilizing quiet stance by means of reinforcement learning

The stabilization of human quiet stance is achieved by a combination of the intrinsic elastic properties of ankle muscles and an active closed-loop activation of the ankle muscles, driven by the delayed feedback of the ongoing sway angle and the corresponding angular velocity in a way of a delayed proportional (P) and derivative (D) feedback controller. It has been shown that the active component of the stabilization process is likely to operate in an intermittent manner rather than as a continuous controller: the switching policy is defined in the phase-plane, which is divided in dangerous and safe regions, separated by appropriate switching boundaries. When the state enters a dangerous region, the delayed PD control is activated, and it is switched off when it enters a safe region, leaving the system to evolve freely. In comparison with continuous feedback control, the intermittent mechanism is more robust and capable to better reproduce postural sway patterns in healthy people. However, the superior performance of the intermittent control paradigm as well as its biological plausibility, suggested by experimental evidence of the intermittent activation of the ankle muscles, leaves open the quest of a feasible learning process, by which the brain can identify the appropriate state-dependent switching policy and tune accordingly the P and D parameters. In this work, it is shown how such a goal can be achieved with a reinforcement motor learning paradigm, building upon the evidence that, in general, the basal ganglia are known to play a central role in reinforcement learning for action selection and, in particular, were found to be specifically involved in postural stabilization.

An output feedback method to polynomial stabilization of hybrid pantograph stochastic systems with aperiodic sampling

This paper focuses on the polynomial stabilization problem of hybrid pantograph stochastic systems (HPSSs) with aperiodic sampling in the presence of randomly occurring transmission delay. Firstly, a sufficient condition is provided to ensure the existence, uniqueness and boundedness of solution to such systems. Next, taking advantage of the Lyapunov stability theory and the comparison method, the criteria of pth moment polynomial stability are established for the HPSSs under the feedback control and aperiodic intermittent control strategy, respectively. Finally, the proposed theoretical results of two control methods are simultaneously validated through a numerical example.

Mean-square exponential stabilization of memristive neural networks: Dealing with replay attacks and communication interruptions

This paper investigates the mean-square exponential stabilization (MSES) of memristive neural networks (MNNs) under replay attacks and communication interruptions. The research will revolve around the following two questions: Firstly, facing replay attacks and communication interruptions, how to design an appropriate controller? Secondly, how to ensure the MSES of MNNs under higher replay attack rate and communication interruption rate? To address these challenges, a novel intermittent sampled-data control scheme is established by considering the mathematical characteristics of replay attacks and communication interruptions. Furthermore, interval-dependent Lyapunov functions are constructed based on the Lyapunov stability theory and inequalities techniques, and two sufficient criteria for MSES of MNNs under the mentioned risks are derived. Thus, the control gain is obtained by solving a series of linear matrix inequalities. In addition, two algorithms are designed to investigate the maximum allowable replay attack rate and communication interruption rate for the system, respectively. Finally, two numerical examples are given to verify the effectiveness of the proposed scheme.

Fixed‐time event‐dependent intermittent control for reaction‐diffusion systems

AbstractThis article discusses the fixed‐time stabilization (FxTS) problem for reaction‐diffusion systems (RDSs). First, this article designs a fixed‐time event‐dependent intermittent control strategy by introducing four nonlinear functions. The switching of the controller between the working and resting phases is no longer time‐dependent, avoiding the relatively stringent constraint on the control ratio in the existing studies of FxTS based on discontinuous‐time control. Under the presented event‐dependent intermittent control strategy, RDSs can be stabilized within a fixed time and the settling time can be estimated as the zero point of the pre‐defined nonlinear function. In contrast to the existing estimation methods, the estimation method of this article is more universal and less conservative. Moreover, this article derives several generalized stabilization criteria for RDSs under event‐dependent intermittent control employing the Lyapunov method and mathematical induction. Finally, an example is given to clarify the validity of the fixed‐time control strategy and the FxTS criteria.

Consensus and attack-decomposition of switched one-sided Lipschitz multi-agent systems via event-triggered intermittent control

This paper considers the exponential consensus of nonlinear switched multi-agent systems (MASs) subject to random attacks. The proposed model is enhanced by introducing the concept of mode-dependent average dwell time (MDADT) and the one-sided Lipschitz (OSL) condition, making it more practical and versatile with relaxed restrictions. Due to the unavailability of direct access to the states of MASs and the vulnerability of their output signals to unknown random attacks, achieving consensus through traditional methods becomes challenging. Hence, a novel attack-decomposition approach is proposed to extract the attack-free output signals from the attacked output signals. Then, the observer is constructed by utilizing attack-free output signals and employed to estimate the states of MASs. A mode-dependent event-triggering mechanism is presented to conserve resources for the observer-controller channels. In order to save control costs, the intermittent control scheme is designed for different switching modes whose control width depends on the minimum dwell time. Finally, an illustrative example is used to showcase the advantages of the theoretical method.

Secure intermittent impulsive consensus control for fractional-order multiagent systems under denial-of-service and deception attacks

This article addresses the secure consensus problem of fractional-order multiagent systems (FOMASs) under denial-of-service (DoS) and deception attacks in the intermittent impulsive control framework. Unlike previous cyber attack models, the multiple attacks are considered, which the agent-to-agent communication channels and the controller-to-actuator channels are randomly subjected to deception and DoS attacks, respectively. Some random variables that follow the Bernoulli distribution are proposed, which are related to the communication channels between adjacent agents to describe deceptive attack behavior. To reduce control costs and resist cyber attacks, a novel intermittent impulsive control strategy is designed to make the FOMASs achieve consensus faster, when DoS attacks are sleeping. The designed intermittent impulsive control includes the advantages of discrete sampling control and intermittent control, which means that it can reduce the injection of erroneous data by constraining the frequency of information transmission. Furthermore, some sufficient criteria including the parameters of multiple attacks are yielded to ensure mean-square quasi-consensus of FOMASs. Finally, two examples are provided to validate the rationality for the presented security control method in this study from the perspective of numerical simulation experiments.

Event-Based Intermittent Formation Control of Multi-UAV Systems Under Deception Attacks.

This article investigates the problem of event-based intermittent formation control for multi-UAV systems subject to deception attacks. Compared to the available research studies on multi-UAV systems with continuous control strategy, the proposed intermittent control strategy saves a large amount of computation resources. An average method is introduced in developing the event-triggered mechanism (ETM) such that the amount of unexpected triggering events induced by uncertain disturbances is greatly reduced. Moreover, such a mechanism can further decrease the average data-releasing rate, thereby alleviating the burden of network bandwidth. Sufficient conditions for multi-UAV systems with deception attacks to achieve the predefined formation are obtained with the aid of Lyapunov stability theory. Finally, the validity of the proposed theoretical results is demonstrated via a simulation example.

Nonsmooth dynamics of a Filippov predator–prey ecological model with antipredator behavior

This article proposes a class of nonsmooth Filippov pest–predator ecosystems with intermittent control strategies based on the pest’s antipredator behavior. aiming to investigate the influence of control strategies and switching thresholds on pest control. First, a comprehensive theoretical analysis of various equilibria within the Filippov system is undertaken, emphasizing the presence and stability of sliding mode dynamics and pseudoequilibrium. Secondly, through numerical simulations, the article discusses boundary-focus, boundary-node, and boundary-saddle bifurcation. Finally, the nonexistence of limit cycles in the Filippov system is theoretically studied. The research indicates that the solution trajectories of the model ultimately stabilize either at the real equilibria or at pseudoequilibrium on the model’s switching surface. Moreover, when the model has multiple coexisting real equilibrium and pseudoequilibrium, the pest-control strategy is correlated with the initial density of both the pest and the predator population.

Finite-time synchronisation for Markovian master-slave neural networks with weighted try-once-discard protocol and static intermittent control

ABSTRACT This paper studies the finite-time synchronisation (FTS) issue for Markovian master-slave neural networks (NNs). A weighted try-once-discard (WTOD) protocol is introduced to overcome communication constraints, and an intermittent control strategy is employed to surmount energy constraints. A WTOD and parameter dependent static feedback controller is designed for the slave neural networks. Then, sufficient conditions are developed to achieve FTS for the considered master-slave NNs, and the controller design method is obtained. Finally, a numerical example is provided to demonstrate and verify the derived results.

Exponential synchronization of complex networks via intermittent dynamic event-triggered control

In this paper, the exponential synchronization in mean square (ESMS) of complex networks (CNs) under intermittent dynamic event-triggered control strategy (IE-TCS) is discussed. Compared with the existing literature, the intermittent control strategy (ICS) proposed is awakened when a certain situation occurs rather than periodically, which can better improve the control efficiency. The average control rate in this paper is more flexible. Furthermore, we give a positive lower bound for the event-triggered intervals to ensure that Zeno behavior does not occur. Combining the graph-theoretic approach with the Lyapunov method, some criteria for ESMS are obtained. In particular, we also discuss the ESMS of non-strongly connected CNs under IE-TCS. Besides, we combine the self-triggered control strategy (S-TCS) with the ICS, which is called the intermittent S-TCS, to study the ESMS of CNs. For practicability, the theoretical results are applied to research the ESMS of the microgrid system, and some relevant sufficient conditions are derived. Eventually, numerical simulations are put forward to verify the effectiveness of theoretical results.

Exponential Output Synchronization of Complex Networks With Output Coupling via Intermittent Event-Triggered Control

This paper considers the exponential output synchronization of complex networks with output coupling (CNOC) based on the intermittent event-triggered control (IE-TC) strategy. Unlike existing intermittent control strategies, the proposed IE-TC strategy is event-triggered instead of time-triggered during the control intervals. Moreover, the average control rate is adopted for intermittent control, which makes the results less conservative. A new Lyapunov function is proposed to simplify the proof, which does not require the traditional mathematical induction method for intermittent control. Based on the Lyapunov method and inequality technique, sufficient conditions for achieving exponential output synchronization of CNOC for undirected graph and digraph topologies are given, respectively. Moreover, the Zeno phenomenon can be excluded. Finally, an example with simulations is provided to verify the feasibility of the theoretical results.

Output information-based intermittent optimal control for continuous-time nonlinear systems with unmatched uncertainties via adaptive dynamic programming

Intermittent control stands as a valuable strategy for resource conservation and cost reduction across diverse systems. Nonetheless, prevailing research is intractable to address the challenges posed by robust optimal intermittent control of nonlinear input-affine systems with unmatched uncertainties. This paper aims to fill this gap. Initially, we introduce an enhanced finite-time intermittent control approach to ensure stability within nonlinear dynamic systems harboring bounded errors. A neural networks (NNs) state observer is constructed to estimate system information. Subsequently, an optimal intermittent controller that operates within a finite time span, guaranteeing system stability by employing the Hamilton–Jacobi–Bellman (HJB) methodology. Furthermore, we devise an output information-based event-triggered intermittent (ETI) approach rooted in the robust adaptive dynamic programming (ADP) algorithm, furnishing an optimal intermittent control law. In this process, a critic NNs is introduced to estimate the cost function and optimal intermittent controller. Simulation results show that our proposed method is superior to existing intermittent control strategies.

Guaranteed cost extended dissipative stabilization of switched IT2 fuzzy systems via intermittent control and its applications

This paper deals with the guaranteed cost extended dissipative stabilization problem of switched IT-2 fuzzy systems (SFSs) via intermittent control. Firstly, we propose a new class of system performance coefficients, taking both the extended dissipative performance and quadratic cost function performance into account. Then, by using a switched-path-dependent fuzzy Lyapunov functions (SFLFs) approach, the membership-function-shape-dependent (MFSD) existence conditions of a set of intermittent controllers are established. Furthermore, we apply the designed intermittent control scheme to three practical control problems: 1) A controller/actuator-failure-triggered intermittent controller is designed, and the guaranteed cost extended dissipative performance of SFSs is ensured in the presence of controller/actuator failures; 2) A switching-triggered intermittent controller is designed, and the guaranteed cost extended dissipative performance of SFSs is ensured in the presence of transmission delay of switching signal, and the asynchronous phenomena is eliminated; 3) A hybrid-triggered intermittent controller is designed, and the guaranteed cost extended dissipative performance of SFSs is ensured while the control resources are saved. Finally, the effectiveness of the results are demonstrated through a robot arm model.

Finite-time synchronization of delayed fuzzy inertial neural networks via intermittent control

This paper addresses the finite-time synchronization (FTS) issue of delayed fuzzy inertial neural networks (DFINNs) via intermittent control. The considered network model takes the inertia term and fuzzy logic into account, which complements some of the existing models. By an appropriate variable substitution, the second-order DFINNs are turned into first-order equation forms. Then, based on the finite-time stability theory, intermittent control strategies are adopted to ensure the FTS of DFINNs and the corresponding criteria are derived thereafter. Besides, the estimation of settling-time for FTS is presented. Finally, the numerical simulations and the image encryption application are presented to illustrate the validity of main results and the control method.

Observer-based aperiodically intermittent pinning synchronization of complex-valued dynamical networks with time-varying delay

This paper addresses the impact of time delay and unavailability of system states on synchronization in complex networks. Specifically, it focuses on observer-based synchronization of complex-valued dynamical networks (CDNs) with time-varying delays, encompassing both complex-valued node dynamics and outer coupling forms. Two aperiodically intermittent control schemes, with and without pins, are proposed to reduce control costs by minimizing control frequency and the number of controllers. The proposed schemes establish sufficient criteria for guaranteeing synchronization in CDNs with time-varying delays, utilizing a combination of Lyapunov function and inequality technology in the complex field. Numerical examples are provided to illustrate the effectiveness of the proposed theoretical results.