A simplified fuzzy model to mimic a nonlinear system, applied to aplasma source

This paper develops a fuzzy model to simulate the behaviour of a nonlinear system, in particular a plasma source, with a view to developing a control system for processing plasmas employing a helicon source. Genetic algorithms are employed to optimize fuzzy rules related to the parameters of the fuzzy model which contain a set of variable zeros and poles of the nonlinear system as well as its time delay. A practical application of the fuzzy model is to estimate the electron number density of a low-temperature plasma. Based on the membership functions of the input and output, a set of fuzzy rules by which the variable zeros and poles are identified is derived and optimized using a genetic algorithm. The principal reason for investigating the proposed fuzzy model is the subsequent computer-aided design of a fuzzy controller to control the nonlinear system. Two experimental results are presented to validate the fuzzy model method. One shows a computer simulation and the other predicts the real-time behaviour of the plasma source as its input parameters are varied     

The dynamic behavior of a cantilever beam coupled to a non-ideal unbalanced motor through numerical and experimental analysis

An excitation force that is not influenced by the system state is said to be an ideal energy source. In real situations, a direct and feedback coupling between the excitation source and the system must always exist at a certain level. This manifestation of the law of conservation of energy is known as the Sommerfeld effect. In the case of obtaining a mathematical model for such a system, additional equations are usually necessary to describe the vibration sources with limited power and its coupling with the mechanical system. In this work, a cantilever beam and a non-ideal DC motor fixed to its free end are analyzed. The motor has an unbalanced mass that provides excitation to the system which is proportional to the current applied to the motor. During the coast up operation of the motor, if the drive power is increased slowly, making the excitation frequency pass through the first natural frequency of the beam, the DC motor speed will remain the same until it suddenly jumps to a much higher value (simultaneously its amplitude jumps to a much lower value) upon exceeding a critical input power. It was found that the Sommerfeld effect depends on some system parameters and the motor operational procedures. These parameters are explored to avoid the resonance capture in the Sommerfeld effect. Numerical simulations and experimental tests are used to help gather insight of this dynamic behavior.     

等离子体天线输入阻抗测量及分析

通过矢量网络分析仪测量了不同激励功率条件下柱形等离子体天线系统的输入阻抗随频率的变化关系,实验结果表明柱形等离子体天线输入阻抗具有明显的谐振特性.结合放电管的等效电路模型与柱形等离子体天线输入电流特性,定性分析了等离子体天线输入阻抗变化与等离子体参数之间的关系.此种测量方法有助于等离子体天线动态重构特性的研究和实现快速阻抗匹配. 关键词： 等离子体天线 输入阻抗 表面波     

Mathematical modeling of ruby laser as a pumping source of a “self Q-switched” distributed feedback dye laser

A mathematical model describing the dynamic emission of the ruby laser as a pumping source of a distributed feedback dye laser (DFDL) has been adapted. The suggested model allows the temporal behavior investigation of the ruby laser and the DFDL on mode characteristics and, moreover, investigating the affect of laser input parameters on the output laser pulses in the ruby laser and in the DFDL.The numerical solutions of a coupled nonlinear rate equations system of the adapted model that predict the generation of picoseconds pulses, with neglecting the effect of refractive index variation, are discussed (feedback process is achieved only by optical gain). The model estimates the density of the emitted radiation, energy density of the first excited state, and the output power of the DFDL. The adapted mathematical model is in good agreement with the available experimental data.     

Characterisation of the plasma density with two artificial neural network models

This paper establishes two artificial neural network models by using a multi layer perceptron algorithm and radial based function algorithm in order to predict the plasma density in a plasma system.In this model,the input layer is composed of five neurons:the radial position,the axial position,the gas pressure,the microwave power and the magnet coil current.The output layer is the target output neuron:the plasma density.The accuracy of prediction is tested with the experimental data obtained by the Langmuir probe.The effectiveness of two artificial neural network models are demonstrated,the results show good agreements with corresponding experimental data.The ability of the artificial neural network model to predict the plasma density accurately in an electron cyclotron resonance-plasma enhanced chemical vapour deposition system can be concluded,and the radial based function is more suitable than the multi layer perceptron in this work.     

等离子体源离子注入过程中半圆形碗状样品的两维温度分布

等离子体源离子注入过程(PSII)中样品温度是一个非常重要的参量。由于注入到样品上的能量很大，导致样品温度很高，所以在实验中获知样品的温度分布有着很重要的意义。本文利用热传导方程建立了半圆形碗状样品内部温度升高模型，研究样品内温度演化过程。以注入离子束流作为能量输入项，热辐射为能量损失项，并考虑了热辐射过程中样品的形状因子的影响。考察了离子注入过程中样品上所施加负偏压的脉冲宽度和频率对样品温度分布的影响。研究结果显示，脉冲频率达到一定值后，样品温度不再随频率增加而升高。     

GA-based optimization of a MIMO ANC system considering coupling of secondary sources in a telephone kiosk

In this paper a multi-input, multi-output (MIMO) active noise control system with the aim of global reduction of broadband noise in a telephone kiosk is addressed. The model selected for this optimization problem is the acoustic environment of an enclosure taking into account the effect of coupling of secondary sources used for control purpose. This optimization involves finding the best locations for loudspeakers and microphones inside the enclosure as well as optimizing the control signals considering secondary source coupling.Previous results show that in order to be able to reduce acoustic noise globally inside the enclosure, the frequency range of 50-300 Hz must be selected for control purpose. The mean of acoustic potential energy of the enclosure, when excited in this frequency range, is adopted as a performance measure. This performance index is penalized with the power of the signal required to excite secondary loudspeakers, in order to avoid placements that may need high voltage power amplifier for a desired performance. To find the solution of this problem, i.e. the global minimum of the performance index, several genetic algorithms are proposed and compared. In order to attain the best achievable performance in reaching the global minimum, the parameters of these genetic algorithms are tuned, and used for optimization purpose. Numerical simulations of the acoustical potential energy as well as the sound pressure at different heights of the kiosk, when active noise control (ANC) system operates, confirm the optimality of the locations proposed by the genetic algorithm.     

Prediction of the plasma distribution using artificial neural network

In this work,an artificial neural network (ANN) model is established using a back-propagation training algorithm in order to predict the plasma spatial distribution in an electron cyclotron resonance (ECR)—plasma-enhanced chemical vapor deposition (PECVD) plasma system. In our model, there are three layers:the input layer, the hidden layer and the output layer. The input layer is composed of five neurons: the radial position, the axial position, the gas pressure, the microwave power and the magnet coil current. The output layer is our target output neuron: the plasma density. The accuracy of our prediction is tested with the experimental data obtained by a Langmuir probe, and ANN results show a good agreement with the experimental data. It is concluded that ANN is a useful tool in dealing with some nonlinear problems of the plasma spatial distribution.     

双同步坐标系锁相环在AC-LINK充电电源中的应用

为提高电源在电网非理想输入情况下工作的适应性,采用解耦双同步坐标系下的三相锁相环,能够获取电网电压的相位与频率信息,并通过FIR滤波环节提取输入线电压的基波幅值,及时准确地为电源提供控制参数。建立了Matlab/Simulink仿真模型,在三相输入不平衡、频率变化、电压畸变等情况下进行仿真,并基于DSP2812芯片编写了控制程序进行测试。仿真与实验结果表明:在各种电网输入情况下,该方法都能够准确提取输入线电压的幅度、相位以及频率信息,为电源的良好运行提供保障。     

Input Resistance Calculation for Circular Microstrip Antennas Using Adaptive Neuro-Fuzzy Inference System

This paper presents a new method based on adaptive neuro-fuzzy inference system (ANFIS) to calculate the input resistance of circular microstrip patch antennas. The ANFIS is a fuzzy inference system (FIS) implemented in the framework of an adaptive fuzzy neural network. It combines the explicit knowledge representation of FIS with learning power of neural networks. A hybrid learning algorithm based on the least square approach and the backpropagation algorithm is used to optimize the parameters of ANFIS. The input resistance results predicted by ANFIS are in excellent agreement with the experimental results reported elsewhere.     

Electron cyclotron resonance breakdown studies in a linear plasma system

Electron cyclotron resonance (ECR) plasma breakdown is studied in a small linear cylindrical system with four different gases — hydrogen, helium, argon and nitrogen. Microwave power in the experimental system is delivered by a magnetron at 2.45 ± 0.02 GHz in TE₁₀ mode and launched radially to have extra-ordinary (X) wave in plasma. The axial magnetic field required for ECR in the system is such that the fundamental ECR surface (B = 875.0 G) resides at the geometrical centre of the plasma system. ECR breakdown parameters such as plasma delay time and plasma decay time from plasma density measurements are carried out at the centre using a Langmuir probe. The operating parameters such as working gas pressure (1 × 10⁻⁵−1× 10⁻² mbar) and input microwave power (160–800 W) are varied and the corresponding effect on the breakdown parameters is studied. The experimental results obtained are presented in this paper.      

60MHz电容耦合等离子体中电子能量分布函数特性研究

甚高频(频率大于30 MHz)耦合放电源由于能产生大面积高密度的等离子体而受到了人们的广泛关注. 采用电流、电压探针以及朗缪尔探针诊断技术对60MHz射频激发产生的容性耦合等离子体的放电特性及电子行为进行了研究. 实验结果表明,等离子体的等效电阻/电容随着射频输入功率的增加而减小/增加;等离子体中电子行为不仅依赖于射频输入功率,还与放电气压密切相关;放电气压的增加导致电子能量概率分布函数(EEPF)从双温Maxwellian分布向Druyvesteyn分布转变,而且转变气压远低于文献所报道的数值,这主要是由于在60MHz容性耦合等离子体中电子反弹共振加热效率大为降低. 关键词： 甚高频容性耦合等离子体 朗缪尔探针诊断 电子加热模式     

Investigations on the effect of process parameters on the growth of vertically oriented graphene sheet in plasma-enhanced chemical vapour deposition system

A multistage numerical model comprising the plasma kinetics and surface deposition sub-models is developed to study the influence of process parameters, namely, total gas pressure and input plasma power on the plasma chemistry and growth characteristics of vertically oriented graphene sheets (VOGS) grown in the plasma-enhanced chemical vapour deposition system containing the Ar + H₂ + C₂H₂ reactive gas mixture. The spectral and spatial distributions of temperature and number densities, respectively, of plasma species, that is, charged and neutral species in the plasma reactor, are examined using inductively coupled plasma module of COMSOL Multiphysics 5.2 modelling suite. The numerical data from the computational plasma model are fed as the input parameters for the surface deposition model, and from the simulation results, it is found that there is a significant drop in the densities of various plasma species as one goes from the bulk plasma region to the substrate surface. The significant loss of the energetic electrons is observed in the plasma region at high pressure (for constant input power) and low input power (for constant gas pressure). At low pressure, the carbon species generate at higher rates on the catalyst nanoislands surface, thus enhancing the growth and surface density of VOGS. However, it is found that VOGS growth rate increases when input plasma power is raised from 100 to 300 W and decreases with further increase in the plasma power. A good comparison of the model outcomes with the available experimental results confirms the adequacy of the present model.     

Enhancing Chaos Complexity of a Plasma Model through Power Input with Desirable Random Features

The present work introduces an analysis framework to comprehend the dynamics of a 3D plasma model, which has been proposed to describe the pellet injection in tokamaks. The analysis of the system reveals the existence of a complex transition from transient chaos to steady periodic behavior. Additionally, without adding any kind of forcing term or controllers, we demonstrate that the system can be changed to become a multi-stable model by injecting more power input. In this regard, we observe that increasing the power input can fluctuate the numerical solution of the system from coexisting symmetric chaotic attractors to the coexistence of infinitely many quasi-periodic attractors. Besides that, complexity analyses based on Sample entropy are conducted, and they show that boosting power input spreads the trajectory to occupy a larger range in the phase space, thus enhancing the time series to be more complex and random. Therefore, our analysis could be important to further understand the dynamics of such models, and it can demonstrate the possibility of applying this system for generating pseudorandom sequences.     

A study on the characteristic behavior of mass inclusions added to a poro-elastic layer

Heterogeneous (HG) blankets consist of a layer of poro-elastic media with small embedded masses that replicate the behavior of a distributed mass-spring-damper system. The concept of an HG blanket used to control the sound transmission through an aircraft double-panel system has already been developed and cited in the present literature. However, deficiencies in methodical property control exist; therefore, the prime objective of this research is to provide a simple method to predict and control material properties of the heterogeneous blankets through alteration of mass and stiffness parameters. Mass inclusion size, shape, and placement were varied. If optimized heterogeneous (HG) blankets targeted to specific applications are to be successfully developed, control of these parameters is necessary.This research offers a detailed analysis of the behavior of the mass inclusions, highlighting controlled stiffness variation of the mass-spring-damper systems inside the HG blanket. Characteristic parameters of the HG blanket like the “footprint,” “effective area,” and the “mass interaction distance” are defined and confirmed through mathematical calculations and experimental results. A novel, empirical approach to predict the natural frequency of different mass shapes embedded in porous media was derived and experimentally verified for many different types of porous media, including melamine foam, polyurethane, and polyamide. A maximum error of 8% existed for all the predictions made in this document.     

Calculation of the external quality factor of the high power input coupler for the BEPC Ⅱ superconducting cavity

It is very important to predict the coupling between the cavity and the high power input source in the coupler design. In this paper, a time domain method is used to calculate the external quality factor Qext for the BEPC Ⅱ superconducting cavity. A comparison between simulation results and experimental results is presented. The results of simulation and measurement of Qext have a good agreement within an error of 10%.The geometry parameters related with Qext are also studied.     

Simple model of compound waveguide structures used as fiber-optic sensors

In this work we present an application of a simple quasi-geometrical model to analyze the behavior of compound waveguide structures used as fiber-optic sensors. This theoretical model is based on the adjustment of the parameters of the structure from the experimental measures to predict the observed behavior of the device. It also takes into account the non-monocromaticity of the used source. In this way, it can be used as a design criterion for this kind of structures. It is applied to a refractive index fiber-optic sensor based on the excitation of surface plasmon in a metal layer by the light guided by a monomode fiber.     

BEHAVIOR OF Ar PLASMA FORMED IN A HIGH DENSITY PLASMA SOURCE-AN ECR REACTOR

In order to develop the ultra-large scale integration(ULSI), low pressure and high density plasma apparatus are required for etching and deposit of thin films. To understand critical parameters such as the pressure, temperature, electrostatic potential and energy distribution of ions impacting on the wafer, it is necessary to understand how these parameters are influenced by the power input and neutral gas pressure. In the present work, a 2-D hybrid electron fluid-particle ion model has been developed to simulate one of the high density plasma sources-an Electron Cyclotron Resonance (ECR) plasma system with various pressures and power inputs in a non-uniform magnetic field. By means of numerical simulation, the energy distributions of argon ion impacting on the wafer are obtained and the plasma density, electron temperature and plasma electrostatic potential are plotted in 3-D. It is concluded that the plasma density depends mainly on both the power input and neutral gas pressure. However, the plasma potential and electron temperature can hardly be affected by the power input, they seem to be primarily dependent on the neutral gas pressure. The comparison shows that the simulation results are qualitatively in good agreement with the experiment measurements.     

Fuzzy coordinator compensation for balancing control of cart-seesaw system

In contrast with fully controllable systems, a super articulated mechanical system (SAMS) is a controlled underactuated mechanical system in which the dimensions of the configuration space exceed the dimensions of the control input space. The control of the cart-seesaw system is especially difficult since it is an underactuated mechanism (three degrees of freedom and only two inputs). This research develops a balancing approach for a novel SAMS model, called the cart-seesaw system, using fuzzy logic and fuzzy coordinator compensation to drive the sliding carts and keep the seesaw angle close to zero in the equilibrium state. Experimental results indicate that utilizing the proposed control methodology significantly enhances the performance. Moreover, the presentation of the fuzzy balancing controller is not considerably affected by changes in the environmental parameters, which demonstrates the effectiveness of the fuzzy controller in minimizing the seesaw tilt angle in the time domain, although the system is caused by unpredicted loading variation. Moreover, the experimental results indicate the usefulness and robustness of the proposed fuzzy control methodology. Furthermore, the proposed software/hardware platform can be beneficial for standardizing laboratory equipment and developing amusement apparatus.     

Predictive control of a chaotic permanent magnet synchronous generator in a wind turbine system

This paper investigates how to address the chaos problem in a permanent magnet synchronous generator(PMSG)in a wind turbine system.Predictive control approach is proposed to suppress chaotic behavior and make operating stable;the advantage of this method is that it can only be applied to one state of the wind turbine system.The use of the genetic algorithms to estimate the optimal parameter values of the wind turbine leads to maximization of the power generation.Moreover,some simulation results are included to visualize the effectiveness and robustness of the proposed method.