Intermittent Control Research Articles

Intermittent Sampled-Data Control for Local Stabilization of Neural Networks Subject to Actuator Saturation: A Work-Interval-Dependent Functional Approach.

This article is concerned with the local stabilization of neural networks (NNs) under intermittent sampled-data control (ISC) subject to actuator saturation. The issue is presented for two reasons: 1) the control input and the network bandwidth are always limited in practical engineering applications and 2) the existing analysis methods cannot handle the effect of the saturation nonlinearity and the ISC simultaneously. To overcome these difficulties, a work-interval-dependent Lyapunov functional is developed for the resulting closed-loop system, which is piecewise-defined, time-dependent, and also continuous. The main advantage of the proposed functional is that the information over the work interval is utilized. Based on the developed Lyapunov functional, the constraints on the basin of attraction (BoA) and the Lyapunov matrices are dropped. Then, using the generalized sector condition and the Lyapunov stability theory, two sufficient criteria for local exponential stability of the closed-loop system are developed. Moreover, two optimization strategies are put forward with the aim of enlarging the BoA and minimizing the actuator cost. Finally, two numerical examples are provided to exemplify the feasibility and reliability of the derived theoretical results.

Stabilization of Highly Nonlinear Time-varying Coupled Systems with Regime Switching via Intermittent Discrete Time Observation Control

Stabilization of Highly Nonlinear Time-varying Coupled Systems with Regime Switching via Intermittent Discrete Time Observation Control

Intermittent Iterative Learning Control for Robot Manipulators Under Packet Dropouts

Intermittent Iterative Learning Control for Robot Manipulators Under Packet Dropouts

Robust Model Predictive Control for Asynchronously Switched Linear Systems with Intermittent Controller Failures

Robust Model Predictive Control for Asynchronously Switched Linear Systems with Intermittent Controller Failures

A Fixed-/Preassigned-Time Stabilization Approach for Discontinuous Systems Based on Strictly Intermittent Control

A Fixed-/Preassigned-Time Stabilization Approach for Discontinuous Systems Based on Strictly Intermittent Control

Mixed Fuzzy Intermittent Control for Nonlinear ODE-PDE Coupled Systems

Mixed Fuzzy Intermittent Control for Nonlinear ODE-PDE Coupled Systems

Asynchronously Delayed Intermittent Control for Highly Nonlinear Stochastic Delayed Large-Scale Networks

Asynchronously Delayed Intermittent Control for Highly Nonlinear Stochastic Delayed Large-Scale Networks

Periodically Intermittent Control of Hybrid Stochastic Delay Systems with Asynchronous Switching by Sampled-data Feedback

Periodically Intermittent Control of Hybrid Stochastic Delay Systems with Asynchronous Switching by Sampled-data Feedback

Transition Variable-Based Fault Estimation and Intermittent Control for Nonlinear Multiagent Systems with Multiple Disturbances

Transition Variable-Based Fault Estimation and Intermittent Control for Nonlinear Multiagent Systems with Multiple Disturbances

An improved intermittent control model of postural sway during quiet standing implemented by a data driven approach

This paper proposes a new intermittent control model during human quiet standing, which is consisted of postulated “regular intervention” and “imminent intervention”. The regular intervention is within the main control loop, and its trigger condition is equivalent to the switching frequency of center of pressure (COP) data calculated by wavelet transform. The imminent intervention will only be triggered after the postural sway angle exceeds a certain threshold. In order to prove the effectiveness of the new model, the simulation results of the new model and the model proposed by Asai et al. (2009) are compared with the experimental data. The setting parameters of both models are retrieved by Bayesian regression from the experimental data. The results show that the new model not only could exhibit two power law scaling regimes of power spectral density (PSD) of COP, but also show that indices of the probability density function distance, root mean square (RMS), Total Sway Path, displacement Range, 50% power frequency of center of mass (COP) between the simulation results and the experimental data are closer compared to the existing model. Moreover, the limit cycle oscillations (LCOs) obtained from the simulation results of the new model have a higher degree of matching with those retrieved from the experimental data.

Aperiodically Intermittent Control of Switched Stochastic Nonlinear Systems Based on Discrete-Time Observation

Aperiodically Intermittent Control of Switched Stochastic Nonlinear Systems Based on Discrete-Time Observation

Intermittent control switch characteristics of triboelectric electric hybrid energy harvesting devices and power management circuits

Renewable energy sources such as wind, vibration, and water wave energy are widely available in everyday life, where there are also scenarios where multiple renewable energy sources coexist. If multiple...

High-efficiency heating and cooling technology with embedded pipes in buildings and underground structures: A review

The thermally activated system utilizes heat exchange pipes embedded in buildings and underground structures to efficiently and stably regulate thermal and humidity environment of building and underground spaces by fully utilizing low-grade energy and heat storage characteristics of the embedded pipe structure. In this review, a comprehensive summary and analysis of the research on embedded pipe heat exchange system are provided, including TABS classification, influencing factors, enhancement strategies, system integration and optimization, application potential, and development trends. The three forms of embedded pipe structures in building enclosures, namely floors, walls, and ceilings, are thoroughly explored. Specifically, to address the demand for environmental regulation in underground spaces, embedding pipes within underground infrastructures is proposed to cater to heating needs in cold region tunnels, cooling requirements in urban tunnels, and deicing/snow melting on road pavements. Various enhancement methods for TABS are suggested to improve operational effectiveness, including utilizing phase change materials, implementing reasonable and effective intermittent operation schemes and control strategies, and integrating with auxiliary air conditioning and dehumidification systems. Future research directions are identified, such as strengthening the prefabrication of embedded pipe thermal activation systems, introducing machine learning algorithms to enhance system intelligence, and combining new technologies to improve system integration as well as integrating the thermo-active system into the fifth-generation district heating and cooling networks. This review work of thermal activation systems with embedded heat transfer pipes will be of some significance in guiding future research and application of embedded pipes heating and cooling of buildings and underground spaces.

Fixed-time synchronization of complex-valued neural networks for image protection and 3D point cloud information protection

This paper studies the fixed-time synchronization (FDTS) of complex-valued neural networks (CVNNs) based on quantized intermittent control (QIC) and applies it to image protection and 3D point cloud information protection. A new controller was designed which achieved FDTS of the CVNNs, with the estimation of the convergence time not dependent on the initial state. Our approach divides the neural network into two real-valued systems and then combines the framework of the Lyapunov method to give criteria for FDTS. Applying synchronization to image protection, the image will be encrypted with a drive system sequence and decrypted with a response system sequence. The quality of image encryption and decryption depends on the synchronization error. Meanwhile, the depth image of the object is encrypted and then the 3D point cloud is reconstructed based on the decrypted depth image. This means that the 3D point cloud information is protected. Finally, simulation examples verify the efficacy of the controller and the synchronization criterion, giving results for applications in image protection and 3D point cloud information protection.

Stabilization and destabilization of impulsive Markovian switching systems via periodic stochastic controls and impulsive controls

AbstractGiven an unstable (or stable) impulsive Markovian switching system (IMSS), can it be stabilized (or destabilized) by noise? This problem has not been studied. In view of this question, this article will establish the noise stabilization and destabilization strategies of IMSS, and also study the impulsive control realized by adjusting the impulse intensity. It is worth noting that the impulse jump is the random impulse whose jump value depends on the mode, and the noise stabilization and destabilization are realized by periodic stochastic control based on Lévy noise. In order to establish these new results, we use the time‐inhomogeneous property of coefficients of the controlled system and the ergodicity of discrete‐time Markov chains based on impulse trigger time. In addition, the periodic stochastic control on diffusion and jump terms can be applied to design intermittent stochastic control.

Physical therapy exercises for improving intermittent exotropia control post-strabismus surgery: A randomized controlled study.

Exotropia control is deteriorated by post-strabismus surgery in many cases. Improving this control is considered as an important factor for success of the strabismus surgery like ocular motor alignment. To determine the therapeutic effect of postoperative eye exercises on exodeviation eye control after the strabismus surgery. Forty patients suffering from intermittent exotropia after strabismus surgery were randomly divided into experimental group and control groups. Both groups received the usual medical care, while the experimental group received different types of eye exercises using physiotherapy modalities in 24 sessions over three months (two sessions a week). The measurement of exotropia control for near target and far target using the office-based scale was done before and after the treatment. There was a significant improvement in near eye control post-treatment () in the experimental group compared with control group () as the mean difference was -3.20 and 95% CI of the difference between them was -3.645--2.755 with . Also, far eye control improved post-treatment in the experimental group () compared with control group () with mean difference of -3.250 and 95% CI of the difference between them was -3.727--2.773 with . For patients with intermittent exotropia who had undergone strabismus surgery, the addition of physiotherapy exercises for the eye provided significant improvements in exotropia control for near target and far target.

Input-to-state stability of stochastic complex networks based on aperiodically intermittent sampled control

This paper focuses on the problem of input-to-state stability (ISS) of stochastic complex networks (SCNs). In this paper, an aperiodically intermittent control strategy based on sampled control is designed. By means of graph theory and Lyapunov method, two stability criteria on ISS are derived in this paper. After giving the estimate between E∑i=1m|xi(t)−xi(δ(t))|2 and E∑i=1m|xi(t)|2, a stability criterion is proposed on ISS of the SCN under aperiodically intermittent sampled control (AISC). When AISC degenerates into sampled control, another stability criterion on ISS of SCN is acquired. Finally, a numerical example is utilized to illustrate the effectiveness and feasibility of the proposed results.

Intermittent Static Output Feedback Control for Stochastic Delayed-Switched Positive Systems With Only Partially Measurable Information

Intermittent Static Output Feedback Control for Stochastic Delayed-Switched Positive Systems With Only Partially Measurable Information

Establishment of a Mathematical Model for Parkinson's Disease Based on Complex Neural Networks and Design of Deep Brain Electrical Stimulation Treatment Plans.

This article introduces the modeling idea of complex neural networks based on the analysis of Parkinson's disease(PD) seizures. According to the Hodgkin-Huxley model of neurons and the synaptic connection theory between neurons, a theoretical model of the basal ganglia circuit was established. To reveal the working mechanism of the brain during the attack of nervous system disease. On this basis, the neural system model is combined with the control theory. Finally, an intermittent adaptive feedback controller is proposed to effectively suppress the onset of Parkinson's disease by stimulating the neuronal system accordingly.

Synchronization for stochastic large-scale systems via intermittent delay discrete observation control

This paper proposes a novel intermittent delay discrete observation control for synchronization of stochastic large-scale systems (LSs) with semi-Markov jump. Different from the existing intermittent delay control, our proposed control strategy is based on discrete-time state observations rather than continuous-time state observations during the work time. And by applying the method of average control rate, the control strategy becomes more practical. Then we establish a lower conservative differential inequality, which is significantly conducive to analyze the synchronization of LSs with multiple delays. Based on the generalized Halanay-type inequality, Lyapunov method and stochastic analysis techniques, several sufficient conditions are derived. Finally, we apply the theoretical results to Chua’s circuit with numerical examples being given.