TAILIEUCHUNG - Neural networks for modelling and control

A comprehensive introduction to the most popular class of neural network, the multilayer perceptron, showing how it can be used for system identification and control. The book provides readers with a sufficient theoretical background to understand the characteristics of different methods, and to be aware of the pit-falls so as to make the correct decisions in all situations. This is a very application-oriented text that gives detailed and pragmatic recommendations to guide users through the plethora of methods suggested in the literature. Furthermore, it introduces sound working procedures that can lead to efficient neural network solutions. Invaluable to the practitioner. | Neural networks for modelling and control Eric Ronco and Peter J. Gawthrop Centre for System and Control Department of Mechanical Engineering University of Glasgow ericr@ peterg@ Technical Report CSC97008 November 10 1997 Abstract This report is a review of the main neurcecontrol technologies. Two main kinds of neuro-control approaches are distinguished. One entails developing a single controller from a neural network and the other one embeds a number of controllers inside a neural network. The single neuro-control approaches are mainly system inverse the inverse of the system dynamics is used to control the system in an open loop manner. The Multi-Layer Perceptron MLP is widely used for this purpose although there is no guarantee that. it. can succeed in learning to control the plant and that more importantly the unclear representation it achieves prohibits the analysis of its learned control properties. These problems and the fact that open loop control is not suitable for many systems highly restricts the usefulness of the MLP for control purposes. However the non-linear modelling capability of the MLP could be exploited to enhance model based predictive control approaches since essentially an accurate model of the plant is all that is required to apply this method. The second neurcwontrol approach can be seen as a modular approach since different controllers are used for the control of different components of the systems. The main modular neuro-controllers are listed. They are all characterised by a gating system used to select the the modular units . controllers or models valid for the computing of a current input pattern. These neural networks are referred to as the Gated Modular Neural Networks GMNNs . Two of these networks are particularly fitted for modelling oriented control purposes. They are the Local Model Network LMN and the Multiple Switched Models MSM . Since the local models of the plant are linear it is fairly easy .

• Tự động hoá
• neural network
• network structures
• achieving practica
• effective systems
• manufacturing
• electrical
• mechanical
• Sliding mode control
• Dynamic surface control
• Surface ship
• Adaptive Neural Network Dynamic Surface Control
• Neural network and deep learning
• Neural network and deep learning: A textbook
• Multilayer neural networks
• Common neural architectures
• Training deep neural networks
• Radial basis function networks
• Traffic flow prediction model
• Neighbouring roads using neural network and multiple regression
• Neural network and multiple regression
• Neural network traffic flow prediction model
• Multiple regression method
• Simulation modeling
• Evaluate Russian banks performance
• Application of neural network
• Neural network and simulation modeling
• Neural Networks
• Neural Networks Representation
• Appropriate problems for Neural Network Learning
• Multilayer Networks
• Remarks on the Backpropagation algorithm
• Neural network application development
• Journal of technology and science education
• Model detecting learning styles with artificial neural network
• Model detecting learning styles
• Artificial neural network
• Singular Value Decomposition
• Latent Semantic Indexing
• Information and communication technology
• Motion learning using spatio temporal neural network
• Spatio temporal neural network
• Reward modulated spike timing dependent plasticity
• Long short term memory
• Recurrent Neural Network (RNN)
• Convolution Neural Network (CNN)
• Traditional neural networks
• Mạng hồi quy LSTM
• LSTM model
• Finding Minimal Neural Networks
• Neural Networks for Business Intelligence Applications
• Feed forward neural networks
• Rule extraction
• Business intelligence applications
• Neural network training
• Elman neural network
• Recurrentneural network
• Groundwater level forecasting
• Simulation of groundwater level
• International Journal of Computer Science & Communication Networks
• Design of intrusion detection system
• Artificial neural network and application of rough set
• Intrusions in a network
• Design template in cellular neural network
• Mathematical logic architecture
• Solving PDE using CNN
• Journal of computer science and information technology
• Convolutional neural network application in biomedical signals
• Convolutional neural network application
• Identify the future research direction
• Recent improvements in big data
• Nuclear engineering and technology
• Prediction of hydrogen concentration
• Containment during severe accidents using fuzzy neural network
• Fuzzy neural network
• Loss of Coolant Accident
• Artificial neural network in textiles
• Biological nervous systems
• Process information
• Highly interconnected processing elements
• Numerical Model
• Storm surge
• Tropical cyclone
• Neural network models
• Electrical Energy Demand Forecasting
• Recurrent Neural Network
• Non linear factor
• Time series analysis
• Building maintenance contractor
• Multi criteria decision making methods
• Artificial neural network model
• Spearman correlation coefficients
• Groundwater level
• Levenberg marquardt algorithm
• Groundwater level prediction
• Power output of the wind turbine
• Pitch angle control using RBF neural network
• RBF neural network
• Blade pitch angles
• The generator remains at 188 5 rad/s
• Ứng dụng mạng neural network
• Mạng neural network
• Hệ thống kiểm tra linh kiện điện tử
• Linh kiện điện tử thời gian thực
• Dự đoán một vật thể
• Rules generation
• Spam filtering
• Multilayer neural network model
• SpamAssassin rules
• Journal of Chemistry
• Heterogeneous Fenton
• Nanoporous clinoptilolite
• Artificial neural network (ANN)
• Radiation interaction position in plastic rod scintillators
• Fast and simple technique
• Position sensitive detector
• Bài giảng Máy học nâng cao
• Máy học nâng cao
• Bài giảng Máy học
• Backpropagation algorithm