nnpredicthelp.m

神经网络预测控制程序的源代码

function nnpredicthelp(varargin);
%NNPREDICTHELP Help text for the NN Predictive Control GUI
%
%  Synopsis
%
%   nnpredicthelp(varargin) 
%
%   displays the help text for the portion of the NN Predictive Control GUI 
%   specified by varargin. 
%
%  Warning!!
%
%    This function may be altered or removed in future
%    releases of the Neural Network Toolbox. We recommend
%    you do not write code which calls this function.
%    This function is generally being called from a Simulink block.

% Orlando De Jesus, Martin Hagan, 1-25-00
% Copyright 1992-2002 The MathWorks, Inc.
% $Revision: 1.4 $ $Date: 2002/04/14 21:11:31 $

ni=nargin;

if ni
   action=varargin{1};
else
   return
end

switch action,
case 'main',
   %---Help for the main Indirect Adaptive Control window
   helptext={'Overview', ...
         {'The NN Predictive Control GUI is an interactive environment for';
         'developing neural network predictive controllers. ';
         '';
         'There are two steps in the controller design:';
         '  1) Identification of a neural network plant model.';
         '  2) Configuration of the controller parameters.';
         '';
         'Flip through the remaining Topics for a detailed description of how ';
         'to use these and other NN Predictive 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 plant weights';
         '     b) Export Network: Export 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 NN Predictive Control GUI and all related windows.';
         '';
         '';
         '2) Window:';
         '     Show and switch between all the open windows.';
         '';
         '';
         '3) Help:';
         '     a) Main Help: Open the general NN Predictive Control GUI help text.';
         '     b) All other Help menus: Open tool specific help text.'};
      'Controller structure', ...
        {'The neural network predictive controller is an optimization algorithm';
         'that uses a neural network plant model to predict future plant behavior';
         'over a specified time horizon.  The optimization algorithm determines';
         'the control signal that optimizes plant behavior over the time horizon.';
         '';
         ''};      
      'Controller parameters', ...
         {'The controller has six parameters:';
         '';
         '   1)Cost horizon N2. The squared error between the plant output and the';
         '     reference signal is minimized over the specified cost horizon.';
         '   2)Controller horizon. The squared controller increments are minimized';
         '     over the specified controller horizon.';
         '   3)Control weighting factor. This term multiplies the squared controller';
         '     increments in the performance index.  As this term is increased, the';
         '     control signal will become smoother.';
         '   4)Minimization routine. You can select a line search routine to be used';
         '     in the optimization process.';
         '   5)Search parameter alpha.  This specifies how much the perfomance must';
         '     be reduced at each iteration of the optimization algorithm.  It should';
         '     much less than 1.';
         '   6)Iterations per sample time.  Specified the number of iterations of the';
         '     optimization algorithm that will be performed at each sampling interval.';
         '';
         ''}};
   
case 'plant_ident',
   %---Help for the Plant Identification process
   helptext = {'Plant Identification', ...
        {'You can go to the Plant Identification window to train a neural';
         'network that mimics the plant behavior.  You should identify the';
         'plant before setting the controller parameters, and you may want to';
         're-identify the plant when controller results are not satisfactory.';
         ''}};
   
case 'simulation',
   %---Help for the simulation process
   helptext={'Simulation', ...
         {'The system can be simulated once the Plant Identification is complete';
         'and the Controller Parameters are set. After you select the Apply buttons in';
         'either window, you can simulate the plant. Go back to the Simulink';
         'window and select Start under the Simulation menu to start the simulation. ';
         'If the performance is not satisfactory, you can go back to retrain the plant';
         'or change the controller parameters.';
         ''}};
         
end, % switch action

helpwin(helptext);