www.gusucode.com > nncontrol 工具箱 matlab 源码程序 > nncontrol/private/nnmodrefhelp_main.m
% OVERVIEW % % The Model Reference Control GUI is an interactive environment for % developing neural network model reference controllers. % % There are two steps in the controller design: % 1) Identification of a neural network plant model % 2) Training of the neural network controller using the identified plant % and a specified reference model. % % Flip through the remaining Topics for a detailed description of how % to use these and other Model Reference Control GUI features. % % MENUS % % The menus provide additional options for setting up and configuring % the controller. The menus available are as follows. % % 1) File: % a) Import Network: Import neural network controller and plant weights % b) Export Network: Export controller and plant weights % c) Save: Load all parameters into the Simulink controller block. % d) Save and Exit: Load all parameters into the Simulink controller block and close this menu. % e) Exit Without Saving: Close the Model Reference Control GUI and all related windows. % % 2) Window: % Show and switch between all the open windows. % % 3) Help: % a) Main Help: Open the general Model Reference Control GUI help text. % b) All other Help menus: Open tool specific help text. % % CONTROLLER STRUCTURE % % The two-layer neural network controller has an input layer with a tansig % transfer function. There are three sets of inputs to the controller: % delayed reference values, delayed controller outputs and delayed plant % outputs. The output layer of the controller network has a purelin % transfer function. You can set the size of the hidden layer. % % REFERENCE MODEL % % In order to train the controller, you must first enter the name of a % simulink file that contains the reference model. The controller is % trained so that the plant output will follow the reference model output. % % The reference model must have one inport block and one outport block. The % reference model is used to generate training data for the Model % Reference Controller training algorithm. % % CONTROLLER INPUTS % % The controller has three inputs available: % % 1)Delayed reference inputs. % 2)Delayed controller outputs. % 3)Delayed plant outputs. % % For each input you must specify the number of delays to be used. % The delays are based on the sample time defined in the Plant Identification % window. For each controller input, you can select any nonzero value for % the number of delays. % % MAX/MIN REFERENCE VALUE % % You must define bounds for the random reference to be used % in the controller training. Those bounds must have a physical relation % to the plant response obtained in the identification process. If the % controller reference bounds are outside the range of the plant response % during the identification process, the controller training may not converge. % The random reference will consist of a series of step functions of random % height and random interval. In addition to setting the min and max height, % you also set the minimum and maximum intervals. % Copyright 1992-2013 The MathWorks, Inc.