Intermittent Control Strategy Research Articles

Quasi-Synchronization of Fuzzy Heterogeneous Complex Networks via Intermittent Discrete-Time State Observations Control

This article focuses on quasi-synchronization of fuzzy heterogeneous complex networks. An aperiodically intermittent control strategy based on discrete-time state observations (aperiodically intermittent discrete-time state observations control for short) is designed. Different from intermittent control strategies referred in existing literatures, the control duration of the control strategy used in this article is based on discrete-time state observations, which makes the control used in this article somewhat less demanding and more effective. Under the aperiodically intermittent discrete-time state observations control strategy, a valid approach combining Lyapunov method with graph theory is proposed in this article. Throughout this article, a theorem and a corollary to the quasi-synchronization criterion of fuzzy heterogeneous complex networks are established. The results show that when the control gain is larger, the convergence domain is smaller. Finally, an illustrative example is presented and the simulation of this example shows the feasibility and validness of the obtained results.

Intermittent Event-Triggered Exponential Stabilization for State-Dependent Switched Fuzzy Neural Networks With Mixed Delays

In this article, the issue of intermittent event-triggered exponential stabilization for state-dependent switched fuzzy neural networks with mixed delays is discussed and resolved. By combining event-triggered control with intermittent control, an intermittent event-triggered control strategy is proposed, which only focuses on events during control time. Consequently, compared with some existing event-triggered control strategies, it greatly reduces the amount of samplings and saves control costs. Based on the fuzzy intermittent event-triggered controller designed in this article, two event-triggering mechanisms are proposed to determine the trigger instants. In this context, some easily testified algebraic conditions are obtained for the exponential stabilization of the state-dependent switched fuzzy neural networks with mixed delays. In addition, a positive lower bound for the inter-event time is given. The results of theoretical analysis are verified through a simulation example.

Exponential Synchronization of Inertial Complex-Valued Fuzzy Cellular Neural Networks with Time-Varying Delays via Periodically Intermittent Control

This paper mainly studies the exponential synchronization issue for the inertial complex-valued fuzzy cellular neural networks (ICVFCNNs) with time-varying delays via periodically intermittent control. To achieve exponential synchronization, we use a non-reduced order and non-separation approach, which is a supplement and innovation to the previous method. Based on directly constructing Lyapunov functional and a novel periodically intermittent control scheme, sufficient conditions for achieving the exponential synchronization of the ICVFCNNs are established. Finally, an example is given to illustrate the validity of the obtained results.

Finite-time [formula omitted] cluster consensus control for nonlinear multi-agent systems with aperiodically intermittent control

This paper investigates the finite-time H∞ cluster consensus for a class of nonlinear multi-agent systems with uncertainties and external disturbances. First, a new aperiodic intermittent controller is designed, which considers both intermittent control and cluster consensus control. Second, the problem of finite-time H∞ cluster control when the system encounters external disturbances is investigated. With the help of the Lyapunov stability criterion and linear matrix inequality analysis techniques(LMI), sufficient conditions for the system to achieve finite-time H∞ cluster consensus control under the action of intermittent control strategy are obtained. Finally, the feasibility of the theoretical analysis is verified by numerical simulation.

Exponential Stabilization of Fuzzy Memristive Neural Networks With Multiple Time Delays Via Intermittent Control

This article investigates global exponential stabilization (GES) of Takagi–Sugeno (T–S) fuzzy memristive neural networks with multiple time-varying delays (DFMNNs) via intermittent control strategy. By resorting to differential inclusion theory, comparison means, and inequality techniques, some results are developed to ensure GES of the underlying DFMNNs via a fuzzy intermittent state feedback control law within the sense of Filippov. The outcome is generalized to GES of FMNNs with infinite distributed time delays. Additionally, the global exponential stability of FMNNs with discrete time-varying delays is explored in terms of 1-norm. The derived conditions herein contain certain existing ones as special cases. Finally, three examples are presented to illuminate the validness of the outcomes.

Intermittent event-triggered control for finite-time bipartite consensus of second-order multi-agent systems

This article discusses how second-order nonlinear multi-agent systems achieve bipartite consensus in finite-time using intermittent event-triggered control strategies. Due to the problem arising from antagonistic links between neighboring nodes of second-order multi-agents, the finite-time bipartite consensus analysis is investigated, which is more challenging than that with only cooperative communication links. Accounting for limitations of communication bandwidths, an intermittent framework is proposed first. By utilizing algebraic graph theories and gauge transformations, sufficient conditions are given to achieve finite-time consensus in signed second-order multi-agent systems. Second, a hybrid control mechanism combining intermittent control with event-triggered control is developed. Therefore, some finite-time synchronization conditions of second-order multi-agents on signed graphs are further studied. The proposed protocol reduces the updating frequency of the controller, which saves communication resources a lot. Finally, the Zeno behavior is excluded and some numerical examples are performed to show the effectiveness of the theoretical analysis.

Synchronization of complex networks with hybrid delays based on event intermittent control

This paper studies the exponential synchronization problem for complex networks with hybrid delays via means of the event intermittent control (EIC) strategy. Compared with the traditional aperiodically intermittent control, the control instants and the rest instants are generated when the events occur, which is more in accordance with the actual situation. An modified lemma related to delays is derived without predesigning intermittent instants. Furthermore, some synchronization criteria with less conservatism are established in terms of linear matrix inequalities (LMIs). Meanwhile, it is also shown that Zeno behavior is excluded. Finally, simulations of a numerical example are given to verify the effectiveness of the proposed EIC strategy.

Change in task conditions leads to changes in intermittency in intermittent feedback control employed by CNS in control of human stance.

Event-driven intermittent feedback control is a form of feedback control in which the corrective control action is only initiated intermittently when the variables of interest exceed certain threshold criteria. It has been reported in the literature that the CNS uses an event-driven intermittent control strategy to stabilize the human upright posture. However, whether the threshold criteria may change under different postural task conditions is not yet well understood. We employ a numerical study with inverted pendulum models and an experimental study with 51 young healthy individuals (13 females and 38 males; age: 27.8 ± 6.5 years) with stabilogram-diffusion, temporal and spectral analysis applied to COP (Center of Pressure) trajectories measured from these experiments to examine this aspect. The present study provides compelling evidence that inducing a natural arm swing during quiet stance appears to lead to higher sensory dead zone in neuronal control reflecting higher intermittency thresholds in active feedback control and a corresponding lower sensory dependence. Beyond the obvious scientific interest in understanding this aspect of how CNS controls the standing posture, an investigation of the said control strategy may subsequently help uncover insights about how control of quiet stance degrades with age and in diseased conditions. Additionally, such an understanding will also be of interest to the humanoid robotics community as it may lead to insights leading to improving control strategies for posture control in robots.

Finite-time synchronization of the drive-response networks by event-triggered aperiodic intermittent control

In this paper, the finite-time synchronization problem of complex networks with time-varying delays is investigated by event-triggered intermittent control. By mean of introducing the event-triggered control (ETC) mechanism and the aperiodic intermittent control (AIC) scheme, an event-triggered intermittent control (ETIC) synthesis for complex networks with time-varying delays is proposed, which is more in line with the actual situation. An modified lemma is derived without predeg intermittent instants. This lemma lead to the existence of the finite-time ETIC. And based on this lemma with the proposed ETIC scheme and the finite-time stability theory, sufficient conditions are presented to guarantee the achievement of finite-time synchronization for all change to time-varying delays complex networks and eliminate the Zeno behavior. Finally, numerical examples are given to verify the effectiveness of the theoretical results and the practicability of the proposed control method.

A Study on Control Strategy for Air Conditioning of Western Exposed Rooms in Subtropical Region

Recently, energy saving has been a major issue in all aspects. In buildings, air conditioning is one major part of power consumption. In this study, we examined the effect of an intermittent control strategy for air conditioning on energy saving in western-exposed rooms under subtropical weather conditions. The strategy applied periodic deactivation and reactivation to the air conditioners. Room temperatures, power consumption, and readings from sensors of air conditioners of two identical rooms were monitored and analyzed. For indoor temperatures, we found that the deactivation of the air conditioner for 15 min resulted in temperature peaks that were 4 to 5 °C higher than the control room. The reactivation of the air conditioner was able to cool down the room within 10 min based on the built-in sensor. However, due to the location and resolution of the sensor, the overall temperature from the four temperature and humidity sensors was still higher than the target setting, which may cause thermal discomfort. For power consumption, the strategy led to power peaks while reactivating, but the summation was 2.9% lower.

Dynamics Analysis and Intermittent Energy Feedback Control of m‐HR Neuron Model under Electromagnetic Induction

It is of great practical significance to fully reveal the global discharge characteristics of neurons in electromagnetic environment and design effective energy feedback strategy for accurate prediction of neural information. Considering the effect of electromagnetic induction, a four‐dimensional modified Hindmarsh–Rose (m‐HR) neuron model is established, and its discharge mechanism is revealed by analyzing the existence and stability of equilibrium point of the model. Extensive numerical results confirm that the model has classical period‐doubling bifurcation, period‐adding bifurcation, and comb‐shaped chaotic structure. Importantly, a new intermittent energy feedback controller is designed by improving the traditional energy feedback control strategy, which can effectively modulate the desired discharge modes under the cost‐optimal energy consumption. Meanwhile, it should be emphasized that the intermittent control scheme has a wider range of regulation and robustness, which can be applied to other dynamical systems to obtain the desired oscillation modes. This will improve the beneficial discussion for the construction of brain‐like intelligent network and efficient regulation.

Exponential synchronization control of delayed memristive neural network based on canonical Bessel-Legendre inequality

<abstract><p>In this paper, we study the exponential synchronization problem of a class of delayed memristive neural networks(MNNs). Firstly, a intermittent control scheme is designed to solve the parameter mismatch problem of MNNs. A discontinuous controller with two tunable scalars is designed, and the upper limit of control gain can be adjusted flexibly. Secondly, an augmented Lyaponov-Krasovskii functional(LKF) is proposed, and vector information of N-order canonical Bessel-Legendre(B-L) inequalities is introduced. LKF method is used to obtain the stability criterion to ensure exponential synchronization of the system. The conservatism of the result decreases with the increase of the order of the B-L inequality. Finally, the effectiveness of the main results is verified by two simulation examples.</p></abstract>

Fixed-time synchronization of stochastic complex networks with mixed delays via intermittent control

This paper studies the problem of fixed-time synchronization in stochastic complex networks. Through the intermittent control strategy, a new controller is designed, so that the system is not affected by the initial value and achieves synchronization at a fixed-time. The controller avoids the influence brought by the sign function and also suitable for directed networks. Establish sufficient conditions for Lyapunov function to derive synchronization. Finally, a simulation example verifies the effectiveness of the proposed method and compares it with the finite-time synchronization.

Synchronization of fractional-order memristive recurrent neural networks via aperiodically intermittent control.

In this paper, synchronization of fractional-order memristive recurrent neural networks via aperiodically intermittent control is investigated. Considering the special properties of memristor neural network, differential inclusion theory is introduced. Similar to the aperiodically strategy of integer order, aperiodically intermittent control strategy of fractional order is proposed. Under the framework of Fillipov's solution, based on the intermittent strategy of fractional order systems and the properties Mittag-Leffler, sufficient criteria of aperiodically intermittent strategy are obtained by constructing appropriate Lyapunov functional. Some comparisons are given to demonstrate the advantages of aperiodically strategy. A simulation example is given to illustrate the derived conclusions.

Intermittent pH control strategy in sludge anaerobic fermentation: Higher short-chain fatty acids production, lower alkali consumption, and simpler control

The pH control to promote short-chain fatty acids (SCFAs) production during anaerobic alkaline fermentation basically focused on constant pH control. In this study, a simple and consumption-reducing intermittent pH control strategy at moderate temperature (23 ± 2 °C) was investigated with adjusting pH to 10 when naturally reduced to 8. The intermittent pH control strategy could alleviate the inhibition of acid-producing bacteria by strong alkaline and high FA concentration. Meanwhile, microbial diversity promoted by 6% and 69% while the relative abundance of acid-producing bacteria increased by 36% and 61% compared to blank and constant pH fermenters. The relative genes abundance related to amino acid metabolism and fatty acid production were mostly promoted and led to enhanced SCFAs production. In the long-term fermenter, the intermittent pH control strategy could result in a 68% reduction in alkali consumption and a 37% increase in SCFAs production compared to that of the constant pH at 10.

Exponential Synchronization of Complex Networks: An Intermittent Adaptive Event-Triggered Control Strategy

This paper investigates the exponential synchronization (ES) problem for complex networks (CNs) under an intermittent adaptive event-triggered control (IAE-TC) strategy which is based on dynamic IAE-TC during the control activation intervals. In this control mechanism, the intermittent controller has adaptability to the evolution results of the controlled networks and is activated only when the event-triggered condition is violated. Then, by employing this kind of control strategy and the Lyapunov method, some sufficient conditions are proposed to achieve the ES of CNs and it is proven that the Zeno behavior can be eliminated. Besides, an application about the islanded microgrid system and some numerical simulations are provided to verify the effectiveness of the derived theoretical results. Moreover, in the numerical simulations, it is shown that the dynamic IAE-TC strategy can decrease the number of event-triggered instants more availably than the static one.

Guaranteed‐cost finite‐time consensus of multi‐agent systems via intermittent control

The guaranteed‐cost finite‐time consensus control problem for a class of nonlinear multi‐agent systems with uncertain parameters was investigated. For a class of nonlinear multi‐agent systems with uncertain parameters, a periodic intermittent control strategy and a continuous feedback control strategy were designed, and the guaranteed‐cost consensus control of the system was investigated using Lyapunov stability theory and matrix inequality technology. Several sufficient conditions to achieve the guaranteed‐cost finite‐time consensus were obtained. It was demonstrated that the multi‐agent system could achieve consensus in a finite time under certain conditions, and the upper bound of the time was given to make the system achieve consensus in finite time. The upper bound of the guaranteed‐cost function was also obtained. Finally, simulations were provided to verify the effectiveness of the proposed method.

Finite-time bipartite synchronization of coupled neural networks with uncertain parameters

This paper investigates the finite-time bipartite synchronization (FTBS) of coupled neural networks (CNNs) with uncertain parameters. Under signed graphs, two control strategies are designed to guarantee FTBS of CNNs with or without external disturbances, respectively. For the disturbed CNNs, a discontinuous adaptive control strategy is proposed to overcome the impacts caused by uncertain parameters and disturbances with the help of non-smooth analysis and Lyapunov stability theory. For the undisturbed CNNs, a periodically intermittent adaptive control strategy is developed to achieve FTBS. Finally, two numerical examples are provided to demonstrate the effectiveness of theoretical results.

Stabilization of hybrid systems by intermittent feedback controls based on discrete‐time observations with a time delay

This paper mainly investigates stabilization of hybrid stochastic differential equations (SDEs) via periodically intermittent feedback controls based on discrete-time state observations with a time delay. First, by using the theory of M-matrix and intermittent control strategy, we establish sufficient conditions for the stability of hybrid SDEs. Then, we prove the intermittent stabilization for a given unstable nonlinear hybrid SDE by comparison theorem. Two numerical examples are discussed to support our results of theoretical analysis.

A self-powered ultra-low-power intermittent-control SSHI circuit for piezoelectric energy harvesting

PurposeExisting control circuits for piezoelectric energy harvesting (PEH) suffers from long startup time or high power consumption. This paper aims to design an ultra-low power control circuit that can harvest weak ambient vibrational energy on the order of several microwatts to power heavy loads such as wireless sensors.Design/methodology/approachA self-powered control circuit is proposed, functioning for very brief periods at the maximum power point, resulting in a low duty cycle. The circuit can start to function at low input power thresholds and can promptly achieve optimal operating conditions when cold-starting. The circuit is designed to be able to operate without stable DC power supply and powered by the piezoelectric transducers.FindingsWhen using the series-synchronized switch harvesting on inductor circuit with a large 1 mF energy storage capacitor, the proposed circuit can perform 322% better than the standard energy harvesting circuit in terms of energy harvested. This control circuit can also achieve an ultra-low consumption of 0.3 µW, as well as capable of cold-starting with input power as low as 5.78 µW.Originality/valueThe intermittent control strategy proposed in this paper can drastically reduce power consumption of the control circuit. Without dedicated cold-start modules and DC auxiliary supply, the circuit can achieve optimal efficiency within one input cycle, if the input signal is larger than voltage threshold. The proposed control strategy is especially favorable for harvesting energy from natural vibrations and can be a promising solution for other PEH circuits as well.