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Charge pump phase locked loops (CPPLLs) are nonlinear systems as a result of the nonlinear behavior of voltage-controlled oscillators (VCO). This paper aims to specify jitter generation of voltage controlled oscillator phase noise in CPPLLs, by considering approximated practical model for VCO.

CPPLL, in practice, shows nonlinear behavior, and usually in LC-VCOs, it follows second-degree polynomial function behavior. Therefore, the nonlinear differential equation of the system is obtained which shows the CPPLLs are a nonlinear system with memory, and that Volterra series expansion is useful for such systems.

In this paper, by considering approximated practical model for VCO, jitter generation of voltage controlled oscillator phase noise in CPPLLs is specified. Behavioral simulation is used to validate the analytical results. The results show a suitable agreement between analytical equations and simulation results.

The proposed method in this paper has two advantages over the conventional design and analysis methods. First, in contrast to an ideal CPPLL, in which the characteristic of the VCO’s output frequency based on the control voltage is linear, in the present paper, a nonlinear behavior was considered for this characteristic in accordance with the real situations. Besides, regarding the simulations in this paper, a behavior similar to the second-degree polynomial was considered, which caused the dependence of the produced jitter’s characteristic corner frequency on the jitter’s amplitude. Second, some new nonlinear differential equations were proposed for the system, which ensured the calculation of the produced jitter of the VCO phase noise in CPPLLs. The presented method is general enough to be used for designing the CPPLL.

The present work aims to explain how the nonlinear average model can be used in power electronic integration design as a behavioral model.

The nonlinear average model is used in power electronic integration design as a behavioral model, where it is applied to a voltage source inverter based on IGBTs. This model was chosen because it takes into account the nonlinearity of the power semiconductor components and the wiring circuit effects, which can be formalized by the virtual delay concept. In addition, the nonlinear average model cannot distinguish between slow and quick variables and this is an important feature of the model convergence.

The paper studies extensively the construction of the nonlinear average model algorithm theoretically. Detailed explanations of the application of this model to voltage source inverter design are provided. The study demonstrates how this model illustrates the effect of the nonlinearity of the power semiconductor components' characteristics on dynamic electrical quantities. It also predicts the effects due to wiring in the inverter circuit.

More simulations and experimental analysis are still necessary to improve the model's accuracy, by using other static characteristic approaches, and to validate the applicability of the model to different converter topologies.

The paper formulates a simple nonlinear average model algorithm, discussing each step. This model was described by VHDL‐AMS. On the one hand, it will assist theoretical and practical research on different topologies of power electronic converters, particularly in power integration systems design such as the integrated power electronics modules (IPEM). On the other hand, it will give designers a more precise behavioral model with a simpler design process.

The nonlinear average model used in power electronic integration design as behavioral model is a novel approach. This model reduces computational costs significantly, takes physical effects into account and is easy to implement.

The purpose of this paper is to develop a linearized equivalent electrical circuit of a photovoltaic generator. This circuit is appropriate to confront problems such as numerical instability, increased computational time and nonlinear/non‐canonical form of system equations that arise when a photovoltaic system is modelled, either with differential equations or with equivalent resistive circuits that are generated by electromagnetic transient software packages for power systems studies.

The proposed technique is based on nonlinear and well‐tested i_pv−v_pv equations which are however used in an alternative mathematical manner. The application of the Newton‐Raphson algorithm on the i_pv−v_pv equations leads to uncoupling of the i_pv and v_pv quantities in each time step of a digital simulation. This uncoupling is represented by a linearized equivalent electrical circuit.

The application of nodal analysis equivalent resistive circuits using the proposed equivalent photovoltaic generator circuit leads to a system model based on linear algebraic equations. This is in opposition to the nonlinear models that normally result when a nonlinear i_pv−v_pv equation is used. In addition, using the proposed scheme, the regular systematic methods of circuit analysis are fully capable of deriving the differential equations of a photovoltaic system in standard form, thus avoiding the time‐consuming solution process of nonlinear models.

In this paper, a new method of using the i_pv−v_pv characteristic equations is proposed which remarkably simplifies photovoltaic systems modeling. Moreover, a very important practical application is that by using this methodology one can develop a photovoltaic generator element in electromagnetic transient programs for power systems analysis, of great value to power engineers who are involved in photovoltaic systems modeling.

The paper aims to improve convergence characteristics of the Newton–Raphson (NR) method applied to time-periodic finite element method using various line searches, as time-periodic finite element method causes deterioration of convergence characteristic of nonlinear analysis based on NR method. The study also aims to accelerate and improve accuracy of electromagnetic field analysis for improvement of the performance of electrical machine.

The paper proposes new type line searches that set approximate step size for NR method. The line search evaluated step size using higher-order interpolation of functional derivative. In addition, two criteria for applying these line search were proposed. First method set one scalar value for every NR iteration that is named constant step size. Second method define different step size in each time step of time-periodic finite element method to update solution vector that is named different step size.

The paper provides efficient line searches to improve convergence characteristics for NR method. Nonlinear magnetic field analysis of two transformer models is demonstrated. The proposed methods achieve the following results: higher-order functional NR is efficient in improving convergence characteristics, and the proposed methods succeeded about twice faster in both models.

The paper fulfills improvement of convergence characteristics of the NR method applied to time-periodic finite element method using proposed line searches and accelerate electromagnetic field analysis.

The purpose of this study is to provide some references about applying the semi-active particle damper to enhance the stability of the pipe structure.

This paper establishes the dynamical models of semi-active particle damper based on traditional dynamical theory and fractional-order theory, respectively. The semi-active particle damping vibration isolation system applied in a pipe structure is proposed, and its analytical solution compared with G-L numerical solution is solved by the averaging method. The quantitative relationships of fractional-order parameters (a and kp) are confirmed and their influences on the amplitude-frequency response of the vibration isolation system are analyzed. A fixed point can be obtained from the amplitude-frequency response curve, and the optimal parameter used for improving the vibration reduction effect of semi-active particle damper can be calculated based on this point. The nonlinear phenomenon caused by nonlinear oscillators is also investigated.

The results show that the nonlinear stiffness parameter p will cause the jump phenomenon while p is close to 87; with the variation of nonlinear damping parameter μ, the pitchfork bifurcation phenomenon will occur with an unstable branch after the transient response; with the change of fractional-order coefficient k_p, a segmented bifurcation phenomenon will happen, where an interval that k_p between 18.5 and 21.5 has no bifurcation phenomenon.

This study establishes a mathematical model of the typical semi-active particle damping vibration isolation system according to fractional-order theory and researches its nonlinear characteristics.

In this paper, mathematical properties of nonlinearity of the equations in Navier‐Stokes model of currents are studied based on the reasoning logic of systems evolutions, combined with methods of analysis and synthesis. It is discovered that the derivative terms are the same as the nonlinear forcing term, in that they all evolve with time and contain discontinuous reversing changes. Consequently, a theoretical and application system is proposed. The concept of blown‐ups constitutes a key step toward the understanding of whole evolution of non‐linear models. The range of applications of this concept is not only limited to research of almost 240‐years‐old mystery of the nonlinearity of currents, but also encompasses the reconsideration of many important principled issues in various theoretical disciplines and related applications.

The existing Nonlinear Dynamic Vibration Absorbers (NLDVAs) have the disadvantages of complex structure, high cost, high installation space requirements and difficulty in miniaturization. And most of the NLDVAs have not been applied to reality. To address the above issues, a novel Triple-magnet Magnetic Dynamic Vibration Absorber (TMDVA) with tunable stiffness, only composed of triple cylindrical permanent magnets and an acrylic tube, is designed, modeled and tested in this paper.

(1) A novel TMDVA is designed. (2) Theoretical and experimental methods. (3) Equivalent dynamics model.

It is found that adjusting the magnet distance can effectively optimize the vibration reduction effect of the TMDVA under different resonance conditions. When the resonance frequency of the cantilever changes, the magnet distance of the TMDVA with a high vibration reduction effect shows an approximately linear relationship with the resonance frequency of the cantilever which is convenient for the design optimization of the TMDVA.

Both the simulation and experimental results prove that the TMDVA can effectively reduce the vibration of the cantilever even if the resonance frequency of the cantilever changes, which shows the strong robustness of the TMDVA. Given all that, the TMDVA has potential application value in the passive vibration reduction of engineering structures.

With the massive use of fossil energy polluting the natural environment, clean energy has gradually become the focus of future energy development. The purpose of this article is to propose a new hybrid forecasting model to forecast the production and consumption of clean energy.

Firstly, the memory characteristics of the production and consumption of clean energy were analyzed by the rescaled range analysis (R/S) method. Secondly, the original series was decomposed into several components and residuals with different characteristics by the ensemble empirical mode decomposition (EEMD) algorithm, and the residuals were predicted by the fractional derivative grey Bernoulli model [FDGBM (p, 1)]. The other components were predicted using artificial intelligence (AI) models (least square support vector regression [LSSVR] and artificial neural network [ANN]). Finally, the fitting values of each part were added to get the predicted value of the original series.

This study found that clean energy had memory characteristics. The hybrid models EEMD–FDGBM (p, 1)–LSSVR and EEMD–FDGBM (p, 1)–ANN were significantly higher than other models in the prediction of clean energy production and consumption.

Consider that clean energy has complex nonlinear and memory characteristics. In this paper, the EEMD method combined the FDGBM (P, 1) and AI models to establish hybrid models to predict the consumption and output of clean energy.

This paper aims to present a method for improving the state estimation of a robot in the presence of noise measurement, which can improve the performance of the robot controller.

In this work, a novel nonlinear tracking differentiator (NTD) was formulated to solve the problems of phase lag, low stability and amplitude attenuation faced by traditional tracking differentiators, which can be used for the state estimation of a robot. Based on the user-defined function stu() with linear and nonlinear characteristics, the authors establish a new acceleration function of NTD and confirm its global asymptotic stability by using the Lyapunov method and the system equivalence method. Phase plane analysis shows that the origin is its stable nodal point or focus point and uncovers the basic constraint conditions for parameter regulation. In addition, the convergence property and robustness performance against noises are studied by describing function method.

Comparative simulations, robot state estimation experiments and joint trajectory tracking experiments have indicated that NTD proposed integrates tracking rapidness, accuracy and transitional stability and has high approximation and filtering effects on generalized derivatives of the signal, which contribute to an excellent performance of robot controller in stability and response speed in practice.

The main contribution of this paper lies in the design of a novel NTD, which successfully improves the state estimation of a robot joint in noisy surroundings, the tracking performance of robot controller and the stability of the system.

This study aims to predict China's carbon emission intensity and put forward a set of policy recommendations for further development of a low-carbon economy in China.

In this paper, the Interaction Effect Grey Power Model of N Variables (IEGPM(1,N)) is developed, and the Dragonfly algorithm (DA) is used to select the best power index for the model. Specific model construction methods and rigorous mathematical proofs are given. In order to verify the applicability and validity, this paper compares the model with the traditional grey model and simulates the carbon emission intensity of China from 2014 to 2021. In addition, the new model is used to predict the carbon emission intensity of China from 2022 to 2025, which can provide a reference for the 14th Five-Year Plan to develop a scientific emission reduction path.

The results show that if the Chinese government does not take effective policy measures in the future, carbon emission intensity will not achieve the set goals. The IEGPM(1,N) model also provides reliable results and works well in simulation and prediction.

The paper considers the nonlinear and interactive effect of input variables in the system's behavior and proposes an improved grey multivariable model, which fills the gap in previous studies.