Search - simulink Q

Search - simulink Q - List

[Other resource] rfid_model DL : 1: A system simulation environment in Matlab/Simulink of RFID is constructed in this paper. Special attention is emphasized on the analog/RF circuit.Negative effects are concerned in the system model,such as phase noise of the local oscillator,TX-RX coupling,reflection of the environment, AWGN noise,DC offset,I/Q mismatch,etc.Performance of the whole system can be evaluated by changing the coding method,parameters of building blocks,and operation distance.Finally,some simulation results are presented in this paper.
Update : 2008-10-13 Size : 2mb Publisher : liulang
[Communication] project8_1_QAM DL : 0: 该源码是用simulink对QAM的仿真实现-the source is used Simulink right QAM Simulation
Update : 2025-02-19 Size : 3kb Publisher : 蒋雯
[source in ebook] qam_simulink(c) DL : 0: c语言仿真qam程序，希望对大家有用，程序自己写的，望修改-c qam language simulation procedures in the hope that it may be useful right, procedures themselves have written, and hopes changes
Update : 2025-02-19 Size : 2kb Publisher : dying
[Industry research] rfid_model DL : 0: A system simulation environment in Matlab/Simulink of RFID is constructed in this paper. Special attention is emphasized on the analog/RF circuit.Negative effects are concerned in the system model,such as phase noise of the local oscillator,TX-RX coupling,reflection of the environment, AWGN noise,DC offset,I/Q mismatch,etc.Performance of the whole system can be evaluated by changing the coding method,parameters of building blocks,and operation distance.Finally,some simulation results are presented in this paper.
Update : 2025-02-19 Size : 2mb Publisher : liulang
[matlab] GMSKsim DL : 0: GMSK调制程序，采用I/Q调制，生成基带GMSK信号，供大家学习和参考！-GMSK modulation procedures, the use of I/Q modulation, to generate baseband GMSK signal for them to learn from and reference!
Update : 2025-02-19 Size : 9kb Publisher : wujingui
[Communication-Mobile] QAM_Matlab DL : 0: qam的matlab程序。m文件，非simulink。各个模块比较全面，希望有所帮助-qam matlab
Update : 2025-02-19 Size : 17kb Publisher : Carlin
[Energy industry] Powerfactor DL : 0: 原创源码。P-Q方法的功率因数计算matlab仿真。-resource about P-Q method power factor calculation
Update : 2025-02-19 Size : 1kb Publisher : 杨广
[matlab] deteminig_switching_time_svpwm DL : 0: this the simulation designed to know the switching time of the svpwm and the simulink model of the 6-pulse invetre and induction model with the krause d-q transformation is simulated -this is the simulation designed to know the switching time of the svpwm and the simulink model of the 6-pulse invetre and induction model with the krause d-q transformation is simulated .......
Update : 2025-02-19 Size : 9kb Publisher : Arvind
[matlab] ILC DL : 2: 迭代学习控制的matlab程序，m文件结合simulink实现。-Iterative Learning Control matlab program, m file with simulink realization.
Update : 2025-02-19 Size : 6kb Publisher : 韩在天
[Program doc] qam8_nograycode DL : 0: An 8-QAM communications channel simulation in Simulink, constructed from a 16-QAM model and using an I,Q correlation receiver. QAM (quadrature amplitude modulation) is a method of combining two amplitude-modulated (AM) signals into a single channel, thereby doubling the effective bandwidth. QAM is used with pulse amplitude modulation (PAM) in digital systems, especially in wireless applications. In a QAM signal, there are two carriers, each having the same frequency but differing in phase by 90 degrees (one quarter of a cycle, from which the term quadrature arises). One signal is called the ‘I’ signal, and the other is called the ‘Q’ signal. Mathematically, one of the signals can be represented by a sine wave, and the other by a cosine wave. The two modulated carriers are combined at the source for transmission. At the destination, the carriers are separated, the data is extracted from each, and then the data is combined into the original modulating information. -An 8-QAM communications channel simulation in Simulink, constructed from a 16-QAM model and using an I,Q correlation receiver. QAM (quadrature amplitude modulation) is a method of combining two amplitude-modulated (AM) signals into a single channel, thereby doubling the effective bandwidth. QAM is used with pulse amplitude modulation (PAM) in digital systems, especially in wireless applications. In a QAM signal, there are two carriers, each having the same frequency but differing in phase by 90 degrees (one quarter of a cycle, from which the term quadrature arises). One signal is called the ‘I’ signal, and the other is called the ‘Q’ signal. Mathematically, one of the signals can be represented by a sine wave, and the other by a cosine wave. The two modulated carriers are combined at the source for transmission. At the destination, the carriers are separated, the data is extracted from each, and then the data is combined into the original modulating information.
Update : 2025-02-19 Size : 11kb Publisher : Griffin Wright
[matlab] ForcedPendulum DL : 0: This simulink model simulates the damped driven pendulum, showing it s chaotic motion. theta = angle of pendulum omega = (d/dt)theta = angular velocity Gamma(t) = gcos(phi) = Force omega_d = (d/dt) phi Gamma(t) = (d/dt)omega + omega/Q + sin(theta) Play with the initial conditions (omega_0, theta_0, phi_0 = omega(t=0), theta(t=0), phi(t=0)) and the system parameters (g, Q, omega_d) and the solver parameters/method. Chaos can be seen for Q=2, omega_d=w/3. The program outputs to Matlab time, theta(time) & omega(time). Plot the phase space via: plot(mod(theta+pi, 2*pi)-pi, omega, . ) Plot the Poincare sections using: t_P = (0:2*pi/omega_d:max(time)) plot(mod(spline(time, theta+pi, t_P), 2*pi)-pi, spline(time, omega, t_P), . ) System is described in: "Fractal basin boundaries and intermittency in the driven damped pendulum" E. G. Gwinn and R. M. Westervelt PRA 33(6):4143 (1986) -This simulink model simulates the damped driven pendulum, showing it s chaotic motion. theta = angle of pendulum omega = (d/dt)theta = angular velocity Gamma(t) = gcos(phi) = Force omega_d = (d/dt) phi Gamma(t) = (d/dt)omega+ omega/Q+ sin(theta) Play with the initial conditions (omega_0, theta_0, phi_0 = omega(t=0), theta(t=0), phi(t=0)) and the system parameters (g, Q, omega_d) and the solver parameters/method. Chaos can be seen for Q=2, omega_d=w/3. The program outputs to Matlab time, theta(time) & omega(time). Plot the phase space via: plot(mod(theta+pi, 2*pi)-pi, omega, . ) Plot the Poincare sections using: t_P = (0:2*pi/omega_d:max(time)) plot(mod(spline(time, theta+pi, t_P), 2*pi)-pi, spline(time, omega, t_P), . ) System is described in: "Fractal basin boundaries and intermittency in the driven damped pendulum" E. G. Gwinn and R. M. Westervelt PRA 33(6):4143 (1986)
Update : 2025-02-19 Size : 8kb Publisher : Mike Gao
[matlab] Qlearningcar DL : 1: Simulink 控制VR环境中的小车。小车有5个距离传感器，能够慢慢学会避开墙壁和障碍物。小车采用加强学习（Q learning），采用神经网络对Q函数逼近。由于使用了模拟退火，小车在开始的时候会经常撞击障碍物，10次后基本就不会再撞了。小车的外观模型使用了"w198406141"在本论坛的虚拟现实区发布的VR模型。-VR environment Simulink control car. There are 5 car distance sensor, can gradually learn to avoid walls and obstacles. Car used to enhance learning (Q learning), using neural networks Q function approximation. As the use of simulated annealing, the car will start when the regular crash barrier, 10 times the fundamental will no longer hit. The appearance model used car " w198406141" in this forum area of virtual reality VR model release.
Update : 2025-02-19 Size : 12kb Publisher : gao
[AI-NN-PR] Qlearningcar DL : 2: Simulink 控制VR环境中的小车。小车有5个距离传感器，能够慢慢学会避开墙壁和障碍物。小车采用加强学习（Q learning），采用神经网络对Q函数逼近。由于使用了模拟退火，小车在开始的时候会经常撞击障碍物，10次后基本就不会再撞了。 -VR environment Simulink control car. There are 5 car distance sensor, can gradually learn to avoid walls and obstacles. Car used to enhance learning (Q learning), using neural network Q function approximation. As the use of simulated annealing, the car in the beginning often hit obstacles, and then ,10 times later, it shouldn t happen.
Update : 2025-02-19 Size : 175kb Publisher : zhangziyang
[Editor] re-hw-pro2 DL : 0: This is ac to dc conversion by using simulink matlab with control q and p
Update : 2025-02-19 Size : 182kb Publisher : lukeee
[matlab] PQ DL : 0: simulink风力发电机组的PQ计算模块，用于风电领域的集成模块-P&Q control
Update : 2025-02-19 Size : 19kb Publisher : 人细微
[Other] Wind_Turbine_Simulink DL : 0: This paper represents the modeling and simulation of 2 MW Direct Drive PMSG Wind energy conversion system (WECS). The modelling of wind turbine and PMSG is carried out in simulink to determine its parameter. WECS consists different components namely Wind turbine, Generator, rectifier-inverter, controller system including transformer, grid etc. The PMSG and converter model are established in the d-q model. Keywords: PMSG, WECS, Wind turbine, rectifier, inverter, MATLAB/SIMLINK, transformer, Grid
Update : 2025-02-19 Size : 10.51mb Publisher : winding
[Static control] 82 DL : 0: Control strategies for extracting the three-phase reference currents for shunt active power filters are compared, uating their performance under different source conditions with PI and Fuzzy Controllers in MATLAB/Simulink environment When the supply voltages are balanced and sinusoidal, the two control strategies are converge to the same compensation characteristics However, the supply voltages are distorted and/or un-balanced sinusoidal, these control strategies result in different degrees of compensation in harmonics. The compensation capabilities are not equivalent, with p-q control strategy unable to yield an adequate solution when source voltages are not ideal. Extensive simulations are carried out with PI controller and also with Fuzzy controller for both p-q and id-iq control strategies under different main voltages. -Control strategies for extracting the three-phase reference currents for shunt active power filters are compared, uating their performance under different source conditions with PI and Fuzzy Controllers in MATLAB/Simulink environment When the supply voltages are balanced and sinusoidal, the two control strategies are converge to the same compensation characteristics However, the supply voltages are distorted and/or un-balanced sinusoidal, these control strategies result in different degrees of compensation in harmonics. The compensation capabilities are not equivalent, with p-q control strategy unable to yield an adequate solution when source voltages are not ideal. Extensive simulations are carried out with PI controller and also with Fuzzy controller for both p-q and id-iq control strategies under different main voltages.
Update : 2025-02-19 Size : 1.16mb Publisher : shatha
[simulation modeling] simulinkdianji DL : 0: 基于d-q模型的感应电动机制动仿真及分析(Simulation and analysis of induction motor braking based on d-q model)
Update : 2025-02-19 Size : 454kb Publisher : BadBox
[matlab] Q.S PROJECT MANGEMENT DL : 0: tell me why i should upload this
Update : 2025-02-19 Size : 188kb Publisher : Modern
[Other] droopcontrol DL : 0: 下垂控制就是选择与传统发电机相似的频率一次下垂特性曲线（Droop Character）作为微源的控制方式，即分别通过P/f下垂控制和Q/V下垂控制来获取稳定的频率和电压，这种控制方法对微网中的微源输出的有功功率和无功功率分别进行控制，无需机组间的通信协调，实现了微源即插即用和对等控制的目标，保证了孤岛下微电网内电力平衡和频率的统一，具有简单可靠的特点(Droop control is to choose Droop Character, which is similar to the traditional generator, as the control mode of micro-source, that is, to obtain stable frequency and voltage through P/f droop control and Q/V droop control respectively. This control method controls active power and reactive power of micro-source output in micro-grid separately, without communication coordination between units. The goal of micro-source plug-and-play and peer-to-peer control is realized, which ensures the unification of power balance and frequency in the micro-grid under isolated islands, and has the characteristics of simplicity and reliability.)
Update : 2025-02-19 Size : 44kb Publisher : drfxxq

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