1
|
Chen Y, Wang Z, Hu J, Han QL. Synchronization Control for Discrete-Time-Delayed Dynamical Networks With Switching Topology Under Actuator Saturations. IEEE TRANSACTIONS ON NEURAL NETWORKS AND LEARNING SYSTEMS 2021; 32:2040-2053. [PMID: 32520711 DOI: 10.1109/tnnls.2020.2996094] [Citation(s) in RCA: 6] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/11/2023]
Abstract
This article is concerned with the synchronization control problem for a class of discrete-time dynamical networks with mixed delays and switching topology. The saturation phenomenon of physical actuators is specifically considered in designing feedback controllers. By exploring the mixed-delay-dependent sector conditions in combination with the piecewise Lyapunov-like functional and the average-dwell-time switching, a sufficient condition is first established under which all trajectories of the error dynamics are bounded for admissible initial conditions and nonzero external disturbances, while the l2 - l∞ performance constraint is satisfied. Furthermore, the exponential stability of the error dynamics is ensured for admissible initial conditions in the absence of disturbances. Second, by using some congruence transformations, the explicit condition guaranteeing the existence of desired controller gains is obtained in terms of the feasibility of a set of linear matrix inequalities. Then, three convex optimization problems are formulated regarding the disturbance tolerance, the l2 - l∞ performance, and the initial condition set, respectively. Finally, two simulation examples are given to show the effectiveness and merits of the proposed results.
Collapse
|
2
|
Mean square exponential synchronization for a class of Markovian switching complex networks under feedback control and M-matrix approach. Neurocomputing 2014. [DOI: 10.1016/j.neucom.2014.04.036] [Citation(s) in RCA: 15] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/22/2022]
|
3
|
Synchronization of neutral complex dynamical networks with Markovian switching based on sampled-data controller. Neurocomputing 2014. [DOI: 10.1016/j.neucom.2014.02.048] [Citation(s) in RCA: 33] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/22/2022]
|
4
|
H ∞ cluster synchronization for a class of neutral complex dynamical networks with Markovian switching. ScientificWorldJournal 2014; 2014:785706. [PMID: 24892088 PMCID: PMC4032659 DOI: 10.1155/2014/785706] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/29/2013] [Accepted: 11/21/2013] [Indexed: 11/29/2022] Open
Abstract
H∞ cluster synchronization problem for a class of neutral complex dynamical networks (NCDNs) with Markovian switching is investigated in this paper. Both the retarded and neutral delays are considered to be interval mode dependent and time varying. The concept of H∞ cluster synchronization is proposed to quantify the attenuation level of synchronization error dynamics against the exogenous disturbance of the NCDNs. Based on a novel Lyapunov functional, by employing some integral inequalities and the nature of convex combination, mode delay-range-dependent H∞ cluster synchronization criteria are derived in the form of linear matrix inequalities which depend not only on the disturbance attenuation but also on the initial values of the NCDNs. Finally, numerical examples are given
to demonstrate the feasibility and effectiveness of the proposed theoretical results.
Collapse
|
5
|
|
6
|
Huang H, Du Q, Kang X. Global exponential stability of neutral high-order stochastic Hopfield neural networks with Markovian jump parameters and mixed time delays. ISA TRANSACTIONS 2013; 52:759-767. [PMID: 23953509 DOI: 10.1016/j.isatra.2013.07.016] [Citation(s) in RCA: 15] [Impact Index Per Article: 1.4] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 04/30/2013] [Revised: 07/15/2013] [Accepted: 07/29/2013] [Indexed: 06/02/2023]
Abstract
In this paper, a class of neutral high-order stochastic Hopfield neural networks with Markovian jump parameters and mixed time delays is investigated. The jumping parameters are modeled as a continuous-time finite-state Markov chain. At first, the existence of equilibrium point for the addressed neural networks is studied. By utilizing the Lyapunov stability theory, stochastic analysis theory and linear matrix inequality (LMI) technique, new delay-dependent stability criteria are presented in terms of linear matrix inequalities to guarantee the neural networks to be globally exponentially stable in the mean square. Numerical simulations are carried out to illustrate the main results.
Collapse
Affiliation(s)
- Haiying Huang
- Shijiazhuang Ordnance Engineering College, Shijiazhuang 050000, PR China.
| | | | | |
Collapse
|
7
|
Wenbing Zhang, Yang Tang, Qingying Miao, Wei Du. Exponential synchronization of coupled switched neural networks with mode-dependent impulsive effects. IEEE TRANSACTIONS ON NEURAL NETWORKS AND LEARNING SYSTEMS 2013; 24:1316-1326. [PMID: 24808570 DOI: 10.1109/tnnls.2013.2257842] [Citation(s) in RCA: 78] [Impact Index Per Article: 7.1] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/03/2023]
Abstract
This paper investigates the synchronization problem of coupled switched neural networks (SNNs) with mode-dependent impulsive effects and time delays. The main feature of mode-dependent impulsive effects is that impulsive effects can exist not only at the instants coinciding with mode switching but also at the instants when there is no system switching. The impulses considered here include those that suppress synchronization or enhance synchronization. Based on switching analysis techniques and the comparison principle, the exponential synchronization criteria are derived for coupled delayed SNNs with mode-dependent impulsive effects. Finally, simulations are provided to illustrate the effectiveness of the results.
Collapse
|
8
|
Tang Y, Gao H, Zou W, Kurths J. Pinning noise-induced stochastic resonance. PHYSICAL REVIEW. E, STATISTICAL, NONLINEAR, AND SOFT MATTER PHYSICS 2013; 87:062920. [PMID: 23848761 DOI: 10.1103/physreve.87.062920] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Received: 01/15/2013] [Indexed: 06/02/2023]
Abstract
This paper proposes the concept of pinning noise and then investigates the phenomenon of stochastic resonance of coupled complex systems driven by pinning noise, where the noise has an α-stable distribution. Two kinds of pinning noise are taken into account: partial noise and switching noise. In particular, we establish a connection between switching noise and global noise when Gaussian noise is considered. It is shown that switching noise can not only achieve a stronger resonance effect, but it is also more robust to induce the resonance effect than partial noise.
Collapse
Affiliation(s)
- Yang Tang
- Institute of Physics, Humboldt University Berlin, Berlin D-12489, Germany.
| | | | | | | |
Collapse
|
9
|
Yu J, Sun G. Robust stabilization of stochastic Markovian jumping dynamical networks with mixed delays. Neurocomputing 2012. [DOI: 10.1016/j.neucom.2012.01.021] [Citation(s) in RCA: 13] [Impact Index Per Article: 1.1] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/28/2022]
|
10
|
IGLESIAS JOSEANTONIO, ANGELOV PLAMEN, LEDEZMA AGAPITO, SANCHIS ARACELI. HUMAN ACTIVITY RECOGNITION BASED ON EVOLVING FUZZY SYSTEMS. Int J Neural Syst 2012; 20:355-64. [DOI: 10.1142/s0129065710002462] [Citation(s) in RCA: 51] [Impact Index Per Article: 4.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/18/2022]
Abstract
Environments equipped with intelligent sensors can be of much help if they can recognize the actions or activities of their users. If this activity recognition is done automatically, it can be very useful for different tasks such as future action prediction, remote health monitoring, or interventions. Although there are several approaches for recognizing activities, most of them do not consider the changes in how a human performs a specific activity. We present an automated approach to recognize daily activities from the sensor readings of an intelligent home environment. However, as the way to perform an activity is usually not fixed but it changes and evolves, we propose an activity recognition method based on Evolving Fuzzy Systems.
Collapse
Affiliation(s)
- JOSE ANTONIO IGLESIAS
- Carlos III University of Madrid, Avda. Universidad, 30, Leganes, Madrid, 28914, Spain
| | - PLAMEN ANGELOV
- InfoLab21, Lancaster University, South Drive, Lancaster, LA1 4WA, United Kingdom
| | | | | |
Collapse
|
11
|
THEODORIDIS DIMITRIOS, BOUTALIS YIANNIS, CHRISTODOULOU MANOLIS. INDIRECT ADAPTIVE CONTROL OF UNKNOWN MULTI VARIABLE NONLINEAR SYSTEMS WITH PARAMETRIC AND DYNAMIC UNCERTAINTIES USING A NEW NEURO-FUZZY SYSTEM DESCRIPTION. Int J Neural Syst 2012; 20:129-48. [DOI: 10.1142/s0129065710002310] [Citation(s) in RCA: 36] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/18/2022]
Abstract
The indirect adaptive regulation of unknown nonlinear dynamical systems with multiple inputs and states (MIMS) under the presence of dynamic and parameter uncertainties, is considered in this paper. The method is based on a new neuro-fuzzy dynamical systems description, which uses the fuzzy partitioning of an underlying fuzzy systems outputs and high order neural networks (HONN's) associated with the centers of these partitions. Every high order neural network approximates a group of fuzzy rules associated with each center. The indirect regulation is achieved by first identifying the system around the current operation point, and then using its parameters to device the control law. Weight updating laws for the involved HONN's are provided, which guarantee that, under the presence of both parameter and dynamic uncertainties, both the identification error and the system states reach zero, while keeping all signals in the closed loop bounded. The control signal is constructed to be valid for both square and non square systems by using a pseudoinverse, in Moore-Penrose sense. The existence of the control signal is always assured by employing a novel method of parameter hopping instead of the conventional projection method. The applicability is tested on well known benchmarks.
Collapse
Affiliation(s)
- DIMITRIOS THEODORIDIS
- Department of Electrical and Computer Engineering, Democritus University of Thrace, 67100 Xanthi, Greece
| | - YIANNIS BOUTALIS
- Department of Electrical and Computer Engineering, Democritus University of Thrace, 67100 Xanthi, Greece
- Department of Electrical, Electronic and Communication Engineering, Chair of Automatic Control, University of Erlangen-Nuremberg, 91058 Erlangen, Germany
| | - MANOLIS CHRISTODOULOU
- Department of Electronic and Computer Engineering, Technical University of Crete, 73100 Chania, Crete, Greece
- Dipartimento di Automatica et Informatica, Politecnico di Torino, 10129 Torino, Italia
| |
Collapse
|
12
|
WU WEI, CHEN TIANPING. IMPOSSIBILITY OF ASYMPTOTIC SYNCHRONIZATION FOR PULSE-COUPLED OSCILLATORS WITH DELAYED EXCITATORY COUPLING. Int J Neural Syst 2011; 19:425-35. [DOI: 10.1142/s0129065709002129] [Citation(s) in RCA: 9] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/18/2022]
Abstract
Fireflies, as one of the most spectacular examples of synchronization in nature, have been investigated widely. In 1990, Mirollo and Strogatz proposed a pulse-coupled oscillator model to explain the synchronization of South East Asian fireflies (Pteroptyx malaccae). However, transmission delays were not considered in their model. In fact, when transmission delays are introduced, the dynamic behaviors of pulse-coupled networks change a lot. In this paper, pulse-coupled oscillator networks with delayed excitatory coupling are studied. A concept of synchronization, named weak asymptotic synchronization, which is weaker than asymptotic synchronization, is proposed. We prove that for pulse-coupled oscillator networks with delayed excitatory coupling, weak asymptotic synchronization cannot occur.
Collapse
Affiliation(s)
- WEI WU
- Fudan University, Shanghai Key Laboratory for Contemporary Applied Mathematics, Shanghai, 200433, P. R. China
| | - TIANPING CHEN
- Fudan University, Shanghai Key Laboratory for Contemporary Applied Mathematics, Shanghai, 200433, P. R. China
| |
Collapse
|
13
|
Ahmadlou M, Adeli H. Fuzzy synchronization likelihood with application to attention-deficit/hyperactivity disorder. Clin EEG Neurosci 2011; 42:6-13. [PMID: 21309437 DOI: 10.1177/155005941104200105] [Citation(s) in RCA: 118] [Impact Index Per Article: 9.1] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 11/17/2022]
Abstract
Synchronization as a measure of quantification of similarities in dynamic systems is an important concept in many scientific fields such as nonlinear science, neuroscience, cardiology, ecology, and economics. When interdependencies and connections of coupled dynamic systems are not directly accessible and measurable such as those of the neurons of the brain, quantification of similarities between their time series outputs is the best possible way to detect the existent interdependencies among them. In recent years, Synchronization Likelihood (SL) has been used as one of the most suitable algorithms in highly nonlinear and non-stationary systems. In this method, the likelihood of patterns is measured statistically, and then it is determined which patterns of the time series are similar to each other considering a threshold. But the degree of similarities is not considered in the decision. In this paper, a new measure of synchronization, fuzzy SL, is presented using the theory of fuzzy logic and Gaussian membership functions. The new fuzzy SL is compared with the conventional SL using both a standard problem from the chaos literature and a complicated real life neurological diagnostic problem, that is, the EEG-based diagnosis of Attention-Deficit/Hyperactivity Disorder (ADHD). The results of ANOVA analysis indicate the interdependencies measured by the fuzzy SL are more reliable than the conventional SL for discriminating ADHD patients from healthy individuals.
Collapse
Affiliation(s)
- Mehran Ahmadlou
- Department of Biomedical Engineering, Ohio State University, 470 Hitchcock Hall, 2070 Neil Avenue, Columbus, Ohio 43210, USA
| | | |
Collapse
|