Asynchronous dynamic quantization for nonlinear systems with one-bit data transmission

The attention of this article is mainly paid to the finite‐time fault detection (FD) problem for nonlinear delayed system with dynamic quantization and multiple packet dropouts. The probabilistic interval time‐varying delay is addressed, which might fall into two intervals with known probability. The measurement signals are quantized by a dynamic quantizer and then transmitted over communication network, where the multiple packet dropouts might occur. The main objective of the considered problem is to design a finite‐time FD filter such that the FD system is stochastically finite‐time stable (SFTS) with guaranteed performance in the presence of probabilistic interval time‐varying delay, dynamic quantization and multiple packet dropouts. Based on Lyapunov stability theory, sufficient criteria for the presence of the desired finite‐time FD filter are presented. Afterwards, the desired filter gain matrices are given via solving certain linear matrix inequalities (LMIs). Finally, a simulation example is used to show the applicability of the obtained finite‐time FD algorithm.

In this paper, the finite-time state estimation problem is studied for nonlinear systems. For reducing the waste of resources which is caused by data transmission, an event-triggered mechanism is adopted to release the measurement output of nonlinear systems to the estimator when the triggered function is satisfied. The error system is obtained by estimating the state of nonlinear systems. We obtain the finite-time bounded criterion of the error system according to the Lyapunov stability theory and the finite-time bounded theory. At last, the effectiveness of the proposed results is proved by two examples.

We study the localization of energy in a nonlinear coupled system, exhibiting so-called breather modes, using quantized Hamilton dynamics (QHD). Already at the lowest order, which is only twice as complex as classical mechanics, this simple semiclassical method incorporates quantum-mechanical effects. The transition between the localized and delocalized regimes is instantaneous in classical mechanics, while it is gradual due to tunneling in both quantum mechanics and QHD. In contrast to classical mechanics, which predicts an abrupt appearance of breathers, quantum mechanics and QHD show an alternation of localized and delocalized behavior in the transient region. QHD includes zero-point energy that is reflected in a shifted energy asymptote for the localized states, providing another improvement on the classical perspective. By detailed analysis of the distribution and transfer of energy within classical mechanics, QHD, and quantum dynamics, we conclude that QHD is an efficient approach that accounts for moderate quantum effects and can be used to identify quantum breathers in large nonlinear systems.

Observer-based fuzzy feedback control for nonlinear systems subject to transmission signal quantization

This paper studies the stabilizability of an n-dimensional quantized feedforward nonlinear system. The state of that system is first quantized into a finite number of bits, and then sent through a digital network to the controller. We want to minimize the number of transmitted bits subject to maintaining asymptotic stability. In the prior literature, n bits are used to stabilize the n-dimensional system by assigning one bit to each state variable (dimension). Under the stronger assumption of global Lipschitz continuity, this paper extends that result by stabilizing the system with a single bit. Its key contribution is a dynamic quantization policy which dynamically assigns the single bit to the most “important” state variable. Under this policy, the quantization error exponentially converges to 0 and the stability of the system can, therefore, be guaranteed. Because 1 is the minimum number of quantization bits (per sampling step), the proposed dynamic quantization policy achieves the minimum stabilizable bit number for that n-dimensional feedforward nonlinear system.

Event-triggering formation control with multiple leaders in second-order nonlinear multi-agent systems is investigated in this paper. This novel distributed formation control strategy allows the event-triggering condition to be intermittently examined at sampling instants, where the data transmission is driven by an event-triggering control protocol. Based on this strategy, two different formation control protocols are presented. Then, some sufficient conditions are given to ensure the second-order nonlinear multi-agent systems converge to the desired formation shape. Finally, examples are given to show the effectiveness of theoretical results.

In a simple nonlinear quantum-dynamical system, described by a two-resonance Hamiltonian, we show that the extension of the wave function in Hilbert space, as parameters of the system are varied, is caused by the overlapping of higher-order nonlinear quantum resonances and is therefore associated with the local destruction of quantum numbers which appears to result from this overlap.

This article investigates the event-based dissipative filtering problem for nonlinear networked systems with dynamic quantization. The nonlinear plant is represented using a discrete-time Takagi–Sugeno (T–S) fuzzy model. The main idea of this article is that a novel dynamic event-triggered mechanism as well as a dynamic quantization strategy combined with a general online adjustment rule are introduced to comprehensively decrease the amount of data involved in network communication and realize the rational utilization of limited communication resources. This article aims to design an event-based quantized filter such that the asymptotic stability and the specified dissipative filtering performance of the filtering error system can be ensured. The design conditions for the desired filter are provided in the form of linear matrix inequalities. Lastly, the effectiveness of the proposed filter design method is demonstrated through the simulation results of a practical example.

Far from thermodynamic equilibrium, nonlinear systems can be characterized by a stationary regime known as a limit cycle. In magnetic systems with a uniaxial symmetry driven with a circularly polarized field, this regime is referred to as the P-mode [1]. P-modes have been experimentally observed in the non-linear ferromagnetic resonance [2]. Stable P-modes can play a role of the equilibrium state for the elementary excitations around them. We show that these excitations can be used in cavity magnonics to explore unique features of non-Hermitian physics such as mode attraction and exceptional points.Level attraction describes a mode coalescence that can take place in open systems. It indicates development of an instability region in the energy spectrum of the coupled system bounded by exceptional points [3]. This regime has been recently observed in a number of experiments in dissipative cavity magnonics [4].Here, we present a theory of mode attraction in periodically driven systems. Our theory can be used in conjunction with numerical micromagnetics to describe non-Markovian Floquet systems [5], which allows us to determine the regions of stability and instability and associate them with mode repulsion and attraction. In magnetic systems, our approach works for quantum and semiclassical dynamics, which makes possible to use it in combination with micromagnetic simulations.We apply this approach to demonstrate the level attraction between the excitations around the P-modes and the photons inside a microwave cavity. In a system driven with a circularly polarized field, the excitations around the P-mode form two side bands around the driving frequency (see figure). We show that when the lower side band couples to the cavity mode, it forms a mode attraction spectrum. Finally we discuss possibilities for experimental observation and predicted dependences on driving field amplitude.  Circular component of the precessing spin driven with the circularly polarized field. The central peak is the P-mode with the frequency of the driving field. Two side bands correspond to the excitation around the P-mode. Coupling to the side band with the negative frequency with respect to the driving field gives mode attraction.

Network control system (NCS) is a kind of distributed control system, which is widely used in industrial control process. The communication network is used to exchange information and control signals among various physical components of subsystems. The transmission of data and information on the communication network to achieve system control will lead to the inevitable delay of information transmission time, which will reduce the performance and even make the system unstable. Reducing network traffic is one of the most effective methods to reduce the impact of network control system delay on system performance. This paper discusses the adjustable deadband as a method to reduce network traffic in networked control systems, and proposes a modeling method of networked control systems with random delay and communication constraints based on quasi T-S fuzzy model. Based on robust fault-tolerant control theory and information scheduling theory, the integrity design of this kind of networked control system is analyzed. After detailed theoretical analysis, simulation results are given to further verify the proposed scheme.

The paper considers the problem of signal parameter estimation using a collection of distributed sensors called a sensor pack. Each sensor quantizes its data to one-bit information and sends it to a fusion processor for the estimation of the parameter. Estimation of a constant signal in additive noise is considered. Estimators are formulated based on one-bit sensor data and their mean squared error (MSE) performances are evaluated through simulation studies. It is shown that selecting certain threshold values for quantizing the sensor outputs can lower the MSE. Genetic algorithms are used to find the optimal threshold values for the sensors. Results from this study show that robust estimation of parameter is possible by using a moderately large number of one-bit quantized sensor data. This work has significance in applications that demand high reliability in sensor networks in spite of sensor failures, limited sensor dynamic range, resolution, bandwidth for data transmission or even data storage.

This article investigates the problem of secure memory adaptive event‐triggered filter design for nonlinear network systems under hybrid network attacks. First, the introduction of memory adaptive event‐triggered mechanism and numerical quantization is employed to enhance system performance, optimize network channel utilization, and prevent network congestion. Second, we consider the impact of deceptive attacks and DoS attacks occurring in the network channel on data transmission, which form the hybrid network attacks studied in this article. Subsequently, based on the established error model, we derive sufficient conditions for the mean‐square exponential stability of the system under a given performance index using Lyapunov–Krasovskii function and linear matrix inequality (LMI) techniques. Furthermore, the filter parameters are determined using the LMI method. Finally, we illustrate the feasibility and generality of the conclusions through numerical simulation examples and a tunnel diode circuit system.

This article proposes an event-triggered (ET) communication mechanism for cooperative control in a group of networked intelligent transportation systems (ITSs). The ITS is described by a class of nonlinear uncertain multi-agent system which is disturbed by a wide stationary process representing the external noise. The control input for each subsystem in the ITS faces the dead-zone constraint. We guarantee the tracking formation control for the ITS under the given circumstances. Additionally, the closed-loop networked system signals are proved to be noise-to-state practically stable in probability (NSpS-P). The transient/steady-state behavior of the tracking errors are managed by the prescribed performance control (PPC) approach. The Zeno phenomenon is then mathematically excluded for the data transmission among the agents. The simulation experiments finally quantify the effectiveness of our proposed approach in terms of reducing the burden of data transmission and providing an appropriate performance with respect to the control objectives.

This article examines the nonfragile bipartite tracking consensus issue in the context of sampled-data nonlinear multiagent systems (MASs) undergoing denial-of-service (DoS) attacks and control gain fluctuations, where both cooperative and competitive interactions between the agents over the network are taken into account. During the DoS attacks, with communication services being denied, a halt in data transmission among the agents is experienced, which might result in performance degradation, undesirable oscillatory behavior, or even hinders the agents from performing their intended tasks. Consequently, there emerges a pressing requirement for the analysis and design of a secure bipartite tracking consensus protocol for MASs under the threat of DoS attacks. In pursuit of this goal, a modified Halanay-like inequality is initially established, which provides a basis for us to derive certain sufficient conditions ensuring the MASs to achieve the bipartite tracking consensus, despite the disruptive presence of malicious DoS attacks. Additionally, the control gain matrix can be readily computed by resolving a collection of linear matrix inequalities. For specific scenarios that demand reduced computational complexity, the matrix decoupling method is introduced, enabling a reduction in the dimensionality of the matrix inequalities and, consequently, facilitating its straightforward application to large-scale MASs. This article culminates in a numerical simulation, which is performed to validate the developed results.

We present a theoretical and numerical study of nonlinear dynamics in an optoelectronic oscillator that follows Liénard-type behaviour. The system combines a resonant tunnelling diode−photodetector (RTD − PD) in series with a laser diode (LD), forming a solid-state system capable of generating ultrafast electrical oscillations while simultaneously delivering coherent optical output. Our theoretical framework unifies the Liénard oscillator formalism with laser rate equations, incorporating delayed feedback characteristics to describe the mutual interaction between the electrical and photonic subsystems. Through numerical simulations, we demonstrate how variations in input signal frequency and circuit parameters shape the dynamics of the system. Our results reveal a rich variety of well-known dynamical regimes, including self-sustained and mixed-mode oscillations, frequency division, and chaotic states confirmed through the computation of Lyapunov exponents and the 0–1 chaos test. To complement quantitative diagnostics, we introduce a sound-based representation (sonification) of time-domain signals to provide an intuitive aid for identifying dynamical transitions. While our model is purely theoretical, simulation parameters are aligned with values reported in prior experimental studies of similar devices. The findings contribute to the understanding of nonlinear optoelectronic systems and may support the design of tunable components for future integrated photonic technologies.