Nouveau-WinRAR-archive

Model Predictive Control code using Matlab software: How Plants Are Used In Model Predictive Control. Blocking and typical Sampling Instant. Prediction and Control Horizons.

用matlab实现飞机的模拟飞行并有简单的控制操作(Matlab simulation with the flight of aircraft)

Power electronics plays an important role in controlling the grid-connected renewable energy sources. This paper presents a novel adaptive neuro-fuzzy control approach for the renewable interfacing inverter. The main objective is to achieve smooth bidirectional power flow and nonlinear unbalanced load compensation simultaneously, where the conventional proportional-integral controller may fail due to the rapid change in the dynamics of the highly nonlinear system. The combined capability of neuro-fuzzy controller in handling the uncertainties and learning from the processes is proved to be advantageous while controlling the inverter under fluctuating operating conditions. The inverter is actively controlled to compensate the harmonics, reactive power, and the current imbalance of a three-phase four-wire (3P4W) nonlinear load with generated renewable power injection into the grid simultaneously.

MATLAB code to Apply DCT on the image and obtain the output and On the DCT image apply quantisation using standard quantizer

Q-learning (Watkins, 1989) is a simple way for agents to learn how to act optimally in controlled Markovian domains. It amounts to an incremental method for dynamic programming which imposes limited computational demands. It works by successively improving its evaluations of the quality of particular actions at particular states. This paper presents and proves in detail a convergence theorem for Q,-learning based on that outlined in Watkins (1989). We show that Q-learning converges to the optimum action-values with probability 1 so long as all actions are repeatedly sampled in all states and the action-values are represented discretely. We also sketch extensions to the cases of non-discounted, but absorbing, Markov environments, and where many Q values can be changed each iteration, rather than just one.

RIMM与IMM的程序比较，就是两中方法比较哪个跟踪效果比较好(RIMM IMM with the procedure, which is two methods which track the results were quite good)

matlab离散系统仿真程序电子系课程设计(Department of Electronics, curriculum design of Matlab discrete system simulation program)

This matlab script is for ploting a graph by accessing serial port data in real time. Change the com values and all variable values accroding to your requirements. Dont forget to add terminator in to your serial device program. This script can be modified to be used on any platform by changing the serialPort variable.

采用8PSK调制，用因子图进行均衡，系统无编码，加性高斯白噪声(Using 8PSK modulation, equalization of factor graph, the system without coding, additive white Gaussian noise)

hilbert时频识别（力学领域）Michael feldman编写（自由振动、强迫振动）(hilbert time-frequency identification (mechanical fields) Michael feldman prepared (free vibration, forced vibration))