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In this brief communication, we highlight several critical inaccuracies in the paper entitled "A novel methodology for a time-delayed controller to prevent nonlinear system oscillations," identified by the DOI: 10.1177/14613484231195276. The core of the non-perturbative approach discussed in this paper is the introduction of a trial solution with an indeterminate nonlinear frequency. We elucidate the technical missteps and provide necessary corrections. The scrutinized article presents ample opportunities for enhancement, and we propose several amendments. Additionally, we reveal that the numerical outcomes showcased in the mentioned paper expose deficiencies in the proposed approximate solution. With the amendments implemented herein, a more precise numerical solution is achieved. [ABSTRACT FROM AUTHOR]

The spatiotemporal arrangement of interacting populations often influences the maintenance of species diversity and is a subject of intense research. Here, we study the spatiotemporal patterns arising from the cyclic competition between three species in two dimensions. Inspired by recent experiments, we consider a generic metapopulation model comprising "rock-paper-scissors" interactions via dominance removal and replacement, reproduction, mutations, pair exchange, and hopping of individuals. By combining analytical and numerical methods, we obtain the model's phase diagram near its Hopf bifurcation and quantitatively characterize the properties of the spiraling patterns arising in each phase. The phases characterizing the cyclic competition away from the Hopf bifurcation (at low mutation rate) are also investigated. Our analytical approach relies on the careful analysis of the properties of the complex Ginzburg-Landau equation derived through a controlled (perturbative) multiscale expansion around the model's Hopf bifurcation. Our results allow us to clarify when spatial "rock-paper-scissors" competition leads to stable spiral waves and under which circumstances they are influenced by nonlinear mobility. [ABSTRACT FROM AUTHOR]

One century after the seminal work by Leonor Michaelis and Maud Menten devoted to the theoretical study of the enzymatic reactions, in this paper, we give an overview of the most recent trends concerning the mathematical modeling of several enzymatic mechanisms, focusing on its asymptotic analysis, which needs the use of advanced mathematical tools, such as center manifold theory, normal forms, and bifurcation theory. Moreover, we present some perspectives, linking the models here presented with similar models, arising from different research fields. [ABSTRACT FROM AUTHOR]

Summary: This paper investigates the finite‐time robust simultaneous stabilization problem of a set of nonlinear time‐delay systems with general forms and proposes some new simultaneous stabilization results. First, by developing an equivalent form and applying augmented technique, this paper obtains an augmented equivalent form of the original systems. Secondly, based on the equivalent form, we study finite‐time simultaneous stabilization problem and present some new stabilization results by constructing some suitable Lyapunov functionals. Thirdly, using the simultaneous stabilization results obtained, this paper investigates the finite‐time robust simultaneous stabilization problem for the set systems and proposes a delay‐dependent robust simultaneous stabilization result. Finally, the study of an illustrative example shows that the results obtained by this paper work well in the finite‐time robust simultaneous stabilization the set systems. It is shown that, by using the method in this paper, the developed conditions do not contain delay terms, which can avoid solving nonlinear mixed matrix inequalities and reduce effectively computational burden in studying nonlinear time‐delay systems. [ABSTRACT FROM AUTHOR]

The challenge for a non-linear vibration system in a fractal space is more fractal dimensions than frequency-amplitude relationship, the system energy consumption depends upon its fractal property, so its best-case scenario is to establish a relationship among the fractal dimensions, frequency and amplitude. For this purpose, this paper studies a fractal-fractional vibration system of a mass attached to a stretched elastic wire in a fractal space, and its asymptotic periodic property is elucidated, the effect of the fractal dimensions on the vibration system is discussed. This paper offers a new road to fast and reliable analysis of fractal oscillators with high accuracy. [ABSTRACT FROM AUTHOR]

This paper studies a local fractional vibration system with a damped non-linear term to reveal its frequency property and its energy consumption. A modification of He's frequency formulation is recommended for this purpose. Some examples are given to illustrate the solving process and the reliability of the method. Additionally, the effect of the initial conditions on the vibrating properties is elucidated. This paper offers a new window for fast and effective insight into local fractional vibration systems. [ABSTRACT FROM AUTHOR]

In high voltage engineering, dielectric response analysis is a widely used tool for insulation diagnostic. Voltages used for studying dielectric response in the laboratory are usually sinusoidal in nature. But the insulation system in operation on site is often stressed by voltages that may deviate significantly from a sinusoid. Thus the use of nonsinusoidal waveform in obtaining the dielectric response is a desirable study for advanced insulation diagnostic technique. Present work involves assessing the condition of electrical insulation using dielectric response analysis under the influence of nonsinusoidal voltage waveform. In dielectric response analysis, characteristics curve of phase response over a frequency band is used to predict the insulation condition, which involves expertise. In this respect parameterization of insulation condition can make the assessment technique much simpler. But the nonlinear behavior of insulation restricts such an attempt to be accurate enough for reliable assessment of minute degradation of insulation condition. Therefore, the present work proposes a non-linear system identification technique, in an attempt to parameterize insulation condition. In this work, a suitable excitation signal has been designed so that the observed response becomes representative of the behavior of the whole system dynamics over the frequency band of interest. Tests have been performed with insulations having different moisture contents. The obtained system parameters, through nonlinear Hammerstein model, were found to be consistent over several experiments, and also accurate enough to detect small variation of moisture content. The proposed method is based on the time domain measurement of input excitation voltage and corresponding response current through the insulation. [ABSTRACT FROM PUBLISHER]

The deployment of multi-agent systems (MASs) is widely used in the fields of unmanned agricultural machineries, unmanned aerial vehicles, intelligent transportation, etc. To make up for the defect that the existing PDE-based results are overly idealistic in terms of system models and control strategies, we study the PDE-based deployment of clustered nonlinear first-order and second- order MASs over a finite-time interval (FTI). By designing special communication protocols, the collective dynamics of numerous agents are modeled by simple fist-order and second-order PDEs. Two practical factors, external disturbance and Markov switching topology, are considered in this paper to better match actual situations. Besides, T-S fuzzy technology is used to approximate the unknown nonlinearity of MASs. Then, by using boundary control scheme with collocated measurements, two theorems are obtained to ensure the finite-time H∞ deployment of first-order and second-order agents, respectively. Finally, numerical examples are provided to illustrate the effectiveness of the proposed approaches. [ABSTRACT FROM AUTHOR]

The positioning and velocity accuracy of spraying robots determine the quality of the coating, and the influence of the robotic dynamic characteristics on control precision is significant. This paper presents a method of linearizing dynamic characteristics into feedforward coefficients and designs a dual-loop control system consisting of an inner velocity loop and an outer position loop. The system is divided into three sections: a cascaded section, a feedback section, and a feedforward section. The cascaded section eliminates the nonlinear characteristics of the system; the feedback section ensures the stability of the system; the feedforward section compensates for the internal errors of the system. The main innovation of this paper lies in proposing an offline parameter tuning method, which avoids online parameter adjustments and significantly enhances the real-time performance of the control system. Additionally, this method does not require specific physical information of the system, thus avoiding the cumbersome process of parameter adjustment. The experimental results demonstrate that when facing different high-speed trajectories, the proposed control system exhibits a significant improvement in control accuracy compared to other advanced control schemes. [ABSTRACT FROM AUTHOR]

In this paper, the Cauchy problem for the nonlinear Schrodinger system {idtu1(x,t)== ∆u1(x, t)− |u1(x, t)| p−1u1(x, t)− |u2(x, t)| p−1u1(x, t), idtu2(x, t) = ∆u2(x, t) − |u2(x, t)| p−1u2(x, t) − |u1(x, t)| p−1u2(x, t), was investigated in d space dimensions. For 1 < p ≤ 1 + 2/d, the nonexistence of asymptotically free solutions for the nonlinear Schrödinger system was proved based on mathematical analysis and scattering theory methods. The novelty of this paper was to give the proof of pseudo-conformal identity on the nonlinear Schrödinger system. The present results improved and complemented these of Bisognin, Sepúlveda, and Vera(Appl. Numer. Math. 59(9)(2009): 2285–2302), in which they only proved the nonexistence of asymptotically free solutions when d = 1, p = 3. [ABSTRACT FROM AUTHOR]

In this paper, the security issue of networked T–S fuzzy system (NTFS) is investigated under intermittent DoS jamming attack (I-DoS-JA). This kind attack often causes the hiatus of control input and output feedback in communication channels. In order to compensate the missing data caused by attacks, a model-based predictive control framework is proposed by embedding predictors within the closed-loop NTFS, in which: (1) a T–S fuzzy model is formulated with the consideration of I-DoS-JA. Based on this model, a fuzzy observer is constructed to estimate the unmeasurable system states; (2) the predictors embedded in remote plant and local controller are modeled as a synchronous T–S fuzzy system; and (3) an event-trigger mechanism is integrated in the observer-based predictor, which would take great advantages in saving bandwidth sources. Finally, a nonlinear system is given as an example to substantiate the work of this paper. [ABSTRACT FROM AUTHOR]

Buckypapers are thin sheets produced from Carbon NanoTubes (CNTs) that effectively transfer the exceptional mechanical properties of CNTs to bulk materials. To accomplish a sensible tradeoff between effectiveness and efficiency in predicting the mechanical properties of CNT buckypapers, a multi-fidelity analysis appears necessary, combining costly but high-fidelity physical experiment outputs with affordable but low-fidelity Finite Element Analysis (FEA)-based simulation responses. Unlike the existing multi-fidelity analysis reported in the literature, not all of the input variables in the FEA simulation code are observable in the physical experiments; the unobservable ones are the latent variables in our multi-fidelity analysis. This article presents a formulation for multi-fidelity analysis problems involving latent variables and further develops a solution procedure based on nonlinear optimization. In a broad sense, this latent variable-involved multi-fidelity analysis falls under the category of non-isometric matching problems. The performance of the proposed method is compared with both a single-fidelity analysis and the existing multi-fidelity analysis without considering latent variables, and the superiority of the new method is demonstrated, especially when we perform extrapolation. [ABSTRACT FROM AUTHOR]

In the traditional iterative learning control (ILC) method, the operational time interval is conventionally fixed to facilitate a seamless learning process along the iteration axis. However, this condition may frequently be contravened in real-time applications owing to unknown uncertainties and unpredictable factors. In essence, replicating a control system at a consistent time interval proves challenging in practical scenarios. This paper proposes an adaptive iterative learning control (AILC) method for the multi-input–multi-output (MIMO) nonlinear system with nonuniform trial lengths and an invertible control gain matrix. Compared to the existing AILC research that features nonuniform trial lengths, the control gain matrix of the system in this paper is assumed to be invertible. Hence, the general requirement in the conventional AILC method that the control gain matrix of the system is positive-definite (or negative-definite) or even known is relaxed. Moreover, the tracking reference allows it to be iteration-varying. Finally, to prove the convergence of the system, the composite energy function is introduced and to verify the validity of the AILC method, a robot movement imitation with an uncalibrated camera system is used. The simulation results show that the actual output can track the desired reference trajectory well, and the tracking error converges to zero after 30 iterations. [ABSTRACT FROM AUTHOR]

In this paper, our study is divided into two parts. The first part involves analyzing a coupled system of beam deflection type that involves nonlinear equations with sequential Caputo derivatives. The also system incorporates the Caputo derivatives in the initial conditions, which adds a layer of complexity and realism to the problem. We focus on proving the existence of a unique solution for this system, and highlighting the robustness and applicability of fractional derivatives in modeling complex physical phenomena. In the second part of the paper, we employ conformable fractional derivatives, as defined by Khalil, to examine another system consisting of two coupled evolution equations. By the Tanh method, we derive new progressive waves. The connection between these two parts lies in the use of fractional calculus to extend and enhance classical problems. [ABSTRACT FROM AUTHOR]

In this paper, for strict-feedback nonlinear systems with positive odd rational powers, the problem of adaptive fixed-time tracking control (FTTC) is considered. With the support of fixed-time theorem and adaptive backstepping method, this paper proposes a new globally adaptive FTTC strategy, which can overcome the singular problems caused by the derivation of virtual control signal. In addition, the proposed control scheme is a universal approach that can be applied to other types of nonlinear systems. Furthermore, the designed adaptive fixed-time tracking controller ensures the boundedness of all signals in the controlled system, and it guarantees the tracking error converges to a small neighbourhood near equilibrium in fixed-time. Finally, the simulation result further verifies the feasibility of the presented control scheme. [ABSTRACT FROM AUTHOR]

This paper studies the problem of adaptive fuzzy control based on command filtering for a class of nonlinear systems characterized by an input dead zone, input saturation, and unknown control direction. First, this paper proposes a novel equivalent transformation technique that simplifies the design complexity of multiple input constraints by converting the input dead zone and saturation nonlinearities into a unified functional form. Subsequently, a fuzzy logic system is utilized to handle the unknown nonlinear functions, and the command-filtering method is employed to address the issue of complexity explosion, while the Nussbaum function is utilized to resolve the challenge of an unknown control direction. Based on Lyapunov stability, it is proven that the tracking error converges to a small neighborhood around the origin, and all closed-loop signals are bounded. Finally, a numerical simulation result and an actual simulation result of a pendulum are presented to verify the feasibility and effectiveness of the proposed control strategy. [ABSTRACT FROM AUTHOR]

The primary objective of this paper is to address the challenge of designing finite-time fault-tolerant control mechanisms for nonlinear flexible spacecraft systems, which are particularly vulnerable to randomized actuator faults. Diverging from traditional methodologies, our research harnesses the capabilities of the Takagi–Sugeno (T–S) fuzzy framework. A unique feature of our model is the representation of actuator failures as stochastic signals following a Markov process, thereby offering a robust solution for addressing timeliness concerns. In this paper, we introduce a generalized reciprocally convex inequality that includes adjustable parameters, broadening the scope of previous results by accommodating them as special cases. Through the amalgamation of this enhanced inequality and flexible independent parameters, we propose an innovative controller design strategy. This approach establishes a stability standard that guarantees mean-square H ∞ performance. In order to validate the efficacy of the suggested strategy, we present a numerical illustration involving a nonlinear spacecraft system, showcasing the practical advantages and feasibility of our proposed technique. [ABSTRACT FROM AUTHOR]

This paper investigates an L1 adaptive fault-tolerant control scheme for nonlinear systems with input constraint, external disturbances, and multiple faults, which include actuator faults and sensor faults. Faults and input constraint are important factors that affect the stability and performance of a control system. Actuators and sensors are the most vulnerable components, with the former receiving more attention in comparison. In this paper, sensor faults are first transformed into pseudo-actuator faults through the augmented matrix approach, which facilitates their handling together with actuator faults. Saturation constraints on the control signal are not conducive to the design of the controller. The conversion of an input-saturated function to a time-varying linear system is completed based on function approximation and Lagrange's mean value theorem. Moreover, a nonlinear system with unknown input gain and uncertainties is constructed using these methods. Next, an L1 adaptive fault-tolerant controller is designed to cope with uncertainties, including system uncertainties, external disturbances, faults, and approximation errors. In the L1 adaptive controller, the online estimation of the time-varying parameters allows for updating of the system state, while the combination of the two is transmitted to the control law such that it can compensate for the effects of the uncertainties. The stability and performance boundaries are further derived using the Lyapunov theory and the L1 reference system. Finally, simulations are carried out to demonstrate the effectiveness of the proposed controller. [ABSTRACT FROM AUTHOR]

To solve the control problem of time-varying state-scale nonlinear systems whose initial state is not affected by settling time, fixed-time convergence algorithms are proposed for first-order systems and higher-order systems in this paper. First, a scalar model is used to illustrate how the time-varying feedback parameter can guarantee that the system achieves asymptotic stability while achieving finite-time convergence, and it is proved that the settling time obtained in this paper is only related to the prescribed boundary. This allows us to design the settling time with an appropriate parameter based on the prescribed boundary. To exhibit the effectiveness and extensibility of the proposed algorithm for first-order scalar systems, the results are subsequently extended to general higher-order systems based on the backstepping method. By introducing numerical simulation results, this paper verifies that the proposed algorithm will make the system achieve asymptotic stability and its output can converge to a given boundary, regardless of the system's initial states. [ABSTRACT FROM AUTHOR]

This paper investigates the adaptive consensus with limited information for a class of uncertain nonlinear multi-agent systems (MASs). The limited information, meaning the incomplete information transmitted between agents, stems from nonzero-kernel weight matrices of communication networks, which deserves concerns owing to its practical interest such as in privacy preserving and information compression. Apart from the limited/incomplete information, the paper considers nonlinear MASs with large uncertainties (without known upper bounds). This is essentially different from the existing results of linear systems and poses challenges for the design and analysis of adaptive consensus. As for fully distributed protocol design, dynamic high gains are introduced to compensate for the system uncertainties and for the unavailable global graph information. In closed-loop consensus analysis, a new Lyapunov function is constructed by utilising weight and incidence matrices instead of Laplacian matrix. It turns out that the designed protocol can guarantee the boundedness of closed-loop MASs signals and the convergent consensus. Two numerical examples are given to demonstrate the effectiveness of the proposed control scheme. [ABSTRACT FROM AUTHOR]

This paper investigates the problem of the adaptive neural network tracking control of nonlinear cyber–physical systems (CPSs) subject to unknown deception attacks with prescribed performance. The considered system is under the influence of unknown deception attacks on both actuator and sensor networks, making the research problem challenging. The outstanding contribution of this paper is that a new anti-deception attack-prescribed performance tracking control scheme is proposed through a special coordinate transformation and funnel function, combined with backstepping and bounded estimation methods. The transient performance of the system can be ensured by the prescribed performance control scheme, which makes the indicators of the controlled system, such as settling time and tracking accuracy, able to be pre-assigned offline according to the task needs, and the applicability of the prescribed performance is tested by selecting different values of the settling time (0.5 s, 1 s, 1.5 s, 2 s, 2.5 s, and 3 s). In addition, to save the computational and communication resources of the CPS, this paper uses a finite-time differentiator to approximate the virtual control law differentiation to avoid "complexity explosion" and a switching threshold event triggering mechanism to save the communication resources for data transmission. Finally, the effectiveness of the proposed control strategy is further verified by an electromechanical system simulation example. [ABSTRACT FROM AUTHOR]

While maintaining the stability of a nonlinear system is a difficult and complicated issue, it becomes even more complicated when considering the uncertainty of system parameters. To accomplish robust stability of such systems and satisfactory performance, it is required to continuously monitor the system measurements and provide periodic control actions, which is impractical in systems with limited communication bandwidth or processing capacity. This paper considers the use of event-triggered sliding mode control (ET-SMC) in controlling a nonlinear system that has the appealing property of updating the computed control action only if an event indicates that the control error exceeds a tolerable limit. Which notably saves computations in the control task while ensuring equivalent performance. First, the ET approach is used in combination with continuous time sliding mode control (CT-SMC). Next, the ET approach is used in combination with discrete time sliding mode control (DT-SMC). Then, a comparison is held between the two controllers to show the superiority of adding the ET technique to the designed controllers (CT-SMC and DT-SMC). In both cases, the well-known Zeno Phenomenon is a possible challenge that should be avoided. In this paper, waiting for a fixed amount of time after each sampling instant and checking a state-dependent criterion is the technique used in the transmission conditions to prevent the occurrence of the Zeno phenomenon. The simulation results demonstrate the effect of adding the ET strategy to the SMC in both continuous and discrete cases. The ET-based controllers developed in this study reduce the number of samples required to generate control action by approximately 98% as compared to the classical sliding mode control schemes. In addition to maintaining robust stability and satisfactory system performance in the presence of uncertainty. [ABSTRACT FROM AUTHOR]

This paper addresses the challenge of adaptive control for nonstrict-feedback nonlinear systems that involve input delay, actuator faults, and external disturbance. To deal with the complexities arising from input delay and unknown functions, we have incorporated Pade approximation and radial basis function neural networks, respectively. An adaptive controller has been developed by utilizing the Lyapunov stability theorem and the backstepping approach. The suggested method guarantees that the tracking error converges to a compact neighborhood that contains the origin and that every signal in the closed-loop system is semi-globally uniformly ultimately bounded. To demonstrate the efficacy of the proposed method, an electromechanical system application example, and a numerical example are provided. Additionally, comparative analysis was conducted between the Pade approximation proposed in this paper and the auxiliary systems in the existing method. Furthermore, error assessment criteria have been employed to substantiate the effectiveness of the proposed method by comparing it with existing results. [ABSTRACT FROM AUTHOR]

In this paper, we deal with the global dynamics of a Lotka-Volterra competition-diffusion-advection system with nonlinear boundary conditions, including the existence, nonexistence and global stability of coexistence steady states. We start with the investigation of the principal eigenvalue of linearized system to get the local stability of steady states and then discuss the global dynamics in terms of competition coefficients. [ABSTRACT FROM AUTHOR]

This paper presents a new direct adaptive control (DAC) technique using Caputo's definition of the fractional-order derivative. This is the first time a fractional-order adaptive law is introduced to work together with an integer-order stable manifold for approximating the uncertainty of a class of nonlinear systems. The DAC approach uses universal function approximators such as multi-layer perceptrons with one hidden layer or fuzzy systems to approximate the controller. This paper presents a new lemma, which elucidates and clarifies the link between the Caputo and the Riemann–Liouville definitions. The introduced lemma is useful in developing a Lyapunov candidate to prove the stability of using the proposed fractional-order adaptive law. This is further explained by a numerical example, which is provided to elucidate the practicality of using the fractional-order derivative for updating the approximator parameters. The main novelty of the results in this paper is a rigorous stability proof of the fractional DAC approach for a class of nonlinear systems that is subjected to unstructured uncertainty and deals with the adaptation mechanism using a traditional integer-order stable manifold. This makes the control scheme easier to implement in practice. The fractional-order adaptation law provides greater degrees of freedom and a potentially larger functional control structure than the conventional adaptive control. Finally, the paper demonstrates that traditional integer-order DAC is a special case of the more general fractional-order DAC scheme introduced here. [ABSTRACT FROM AUTHOR]

This paper proposes a novel solution to the problem of robust ripple‐free hybrid robust regulator ensuring the elimination of intersample ripples. The paper considers a structurally stable regulation approach in the hybrid framework. A regulator is designed using this technique under periodic sampling and is applied to the nonlinear model of a quadrotor. The control of unmanned autonomous vehicles has become a research topic that is important by itself, particularly in the case of multi‐rotor systems due to their versatility in various applications. Tracking a reference signal for such vehicles can be challenging, particularly when the frequency of communication is limited, or the control station is located far away. The proposed controller is hence tested for this challenging application. [ABSTRACT FROM AUTHOR]

Hydro-viscous clutch has already become an inevitable choice for special vehicle transmission in the present and future. As a nonlinear system with a large hysteresis loop, its speed control performance is affected by input rotational speed, lubricating oil temperature, lubrication pressure, and other factors. The traditional control method cannot adjust the temperature and rotational speed, which will lead to problems of narrow speed range, poor rotational speed stability, and large dynamic load impact. In order to solve the above problems, this paper studies the control method of an integrated multi-parameter hydro-viscous speed control system (HSCS) in a controlled environment. Through the mechanism analysis of the law of HSCS, the influence law of speed and temperature during the system operation is found. The temperature closed loop based on model predictive control (MPC) is introduced to control the rotational speed, and then the traditional PID control results are compensated according to the speed closed loop. Next, a novel double closed loop control method of temperature and rotational speed for HSCS is formed. Finally, the simulating verification is carried out. Compared with the traditional control method, the design method in this paper can adjust the control parameters according to the temperature of the lubricating oil and the input rotational speed and effectively expand the domain of HSCS and the speed control stability. The effective transmission ratio is extended to 0.2~0.8, and the hydro-viscous torque and speed fluctuation under the engine rotational speed fluctuation are reduced by more than 30%. The novel control method of HSCS designed in this paper can effectively improve the influence of input rotational speed and lubricating oil temperature on the speed control performance of HSCS and can be widely used in nonlinear HSCS such as hydro-viscous clutch. [ABSTRACT FROM AUTHOR]

This paper studies the $ {H_\infty } $ H ∞ filtering problem for a class of discrete-time semi-Markov switching repeated scalar nonlinear systems with an event-triggered scheme. Considering the limitation of bandwidth, the mode-dependent event-triggered mechanism is introduced to determine whether the currently sampled sensor data is transmitted to the filter, in which the parameters of the event generator depend on the system mode. By means of a constructed time-varying Lyapunov function, the two stages of the systems jump instant and mode residence are analysed, and a linear matrix inequality technique is used to ensure the mean-square stability and $ {H_\infty } $ H ∞ performance of the filter error system. Accordingly, the co-design method of the mode-dependent time-varying filter and the event-triggered mechanism is derived for semi-Markov switching systems. Finally, a numerical simulation is given to illustrate the effectiveness and feasibility of the method proposed in this paper. [ABSTRACT FROM AUTHOR]

The DC circuit breaker is a crucial equipment for eliminating faults in DC transmission lines. The electromagnetic release functions as a critical component that restricts the circuit breaker's lifespan. It is essential to prioritize its safety and reliability during usage and predicting its remaining useful life (RUL) is paramount. This paper proposes a new prediction technique based on particle filtering (PF) and the whale optimization algorithm (WOA) for the remaining useful life of electromagnetic release. The particle filtering algorithm is a commonly used technique in practical engineering fields such as target tracking and RUL prediction. It is a mainstream method for solving the parameter estimation of non-linear non-Gaussian systems. The WOA is introduced to improve the PF algorithm in order to ensure the diversity of particles and lessen the effect of particle degradation. The WOA replaces the traditional resampling process, and after each computation is finished, the weights of the particles in the particle set are reassigned in order to improve the particle distribution and increase algorithm accuracy. The rate of loss of the spring reaction force and the striker counterforce are chosen as the degradation characteristics after the degradation factors of electromagnetic release are analyzed. The degradation curves at different temperatures of electromagnetic release are obtained using the accelerated life test, and the full-life data during normal operation are derived using the Arrhenius equation. Finally, the RUL is predicted by comparing this paper's method with the conventional PF method. The experimental results demonstrate that the method presented in this paper can more accurately predict the RUL of the electromagnetic release and has a higher prediction accuracy. [ABSTRACT FROM AUTHOR]

This paper is bound up with the distributed consensus recursive filtering subject to random nonlinear disturbances systems under round-robin (RR) protocol. In order to describe the system model more realistically, the nonlinear time delay is introduced into the system. RR protocol is used in this paper to reduce the network burden of information transmission among nodes. In the developed consensus recursive filtering algorithm, each node only uses the information of itself and neighboring nodes. The objective of the issue is to design a nonlinear filter for each node and calculate the corresponding filter gain matrix. The filter gain matrix is obtained by minimizing the upper bound. The upper bound of the filtering error covariance can be got by solving two matrix difference equations. By mathematical induction, it is proved that the filtering error covariance is convergent. In the end, several simulation pictures are shown to demonstrate the effectiveness of the designed filtering scheme. [ABSTRACT FROM AUTHOR]

In this paper, hybrid models of Kalman filter and neural network for state estimation are reviewed of their corresponding academic achievements, the creation of which is a noteworthy development in state estimation. This paper aims to provide a summary of research progress on such hybrid models and emphasize their functions and advantages. First of all, the concept and feature are paid attention to about Kalman filter, and its transmutative modes are taken into consideration. Then several popular neural network algorithms are introduced in brief. Subsequently, research results on hybrid models are analysed and discussed comprehensively. Not only Kalman filter and neural network can be adopted in succession, but also can be mixed in structure. The mixed models can also be divided into two types, the equations or parameters of state--space model are trained by neural network for Kalman filter and the parameters of neural network are updated by Kalman filter. It is proved that the hybrid models outperform than single model of Kalman filter or neural network in accuracy and generalization. Last but not least, the effectiveness of state--space equations of Kalman filter can be established by neural network in nonlinear systems is verified. [ABSTRACT FROM AUTHOR]