www.gusucode.com > control 案例程序 matlab源码代码 > control/CreateTunableSecondOrderFilterExample.m
%% Create Tunable Second-Order Filter % This example shows how to create a parametric model of the second-order % filter: % % $$F\left( s \right) = \frac{{\omega _n^2}}{{{s^2} + 2\zeta {\omega _n}s + \omega _n^2}},$$ % % where the damping $\zeta$ and the natural frequency ${\omega _n}$ are tunable parameters. %% % Define the tunable parameters using |realp|. wn = realp('wn',3); zeta = realp('zeta',0.8); %% % |wn| and |zeta| are |realp| parameter objects, with initial values |3| % and |0.8|, respectively. %% % Create a model of the filter using the tunable parameters. F = tf(wn^2,[1 2*zeta*wn wn^2]); %% % The inputs to |tf| are the vectors of numerator and denominator % coefficients expressed in terms of |wn| and |zeta|. %% % |F| is a |genss| model. The property |F.Blocks| lists the two tunable % parameters |wn| and |zeta|. F.Blocks %% % You can examine the number of tunable blocks in a generalized model % using |nblocks|. nblocks(F) %% % |F| has two tunable parameters, but the parameter |wn| appears five times % - Twice in the numerator and three times in the denominator. %% % To reduce the number of tunable blocks, you can rewrite |F| as: % % $$F\left( s \right) = \frac{1}{{{{\left( {\frac{s}{{{\omega _n}}}} % \right)}^2} + 2\zeta \left( {\frac{s}{{{\omega _n}}}} \right) + 1}}.$$ % % Create the alternative filter. F = tf(1,[(1/wn)^2 2*zeta*(1/wn) 1]); %% % Examine the number of tunable blocks in the new model. nblocks(F) %% % In the new formulation, there are only three occurrences of the tunable % parameter |wn|. Reducing the number of occurrences of % a block in a model can improve the performance of calculations involving % the model. However, the number of occurrences does not affect the results % of tuning the model or sampling it for parameter studies.