www.gusucode.com > ident 案例代码 matlab源码程序 > ident/EstimateOverparameterizedProcessModelUsingRegularizationExample.m
%% Estimate Over-parameterized Process Model Using Regularization % Use regularization to estimate parameters of an over-parameterized process % model. % % Assume that gain is known with a higher degree of confidence than other % model parameters. % Copyright 2015 The MathWorks, Inc. %% % Load data. load iddata1 z1; %% % Estimate an unregularized process model. m = idproc('P3UZ','K',7.5,'Tw',0.25,'Zeta',0.3,'Tp3',20,'Tz',0.02); m1 = procest(z1,m); %% % Estimate a regularized process model. opt = procestOptions; opt.Regularization.Nominal = 'model'; opt.Regularization.R = [100;1;1;1;1]; opt.Regularization.Lambda = 0.1; m2 = procest(z1,m,opt); %% % Compare the model outputs with data. compare(z1,m1,m2); %% % Regularization helps steer the estimation process towards the correct % parameter values.