www.gusucode.com > mpc 案例源码 matlab代码程序 > mpc/ConvertUnconstrainedMPCControllerToStateSpaceModelExample.m
%% Convert Unconstrained MPC Controller to State-Space Model % %% % To improve the clarity of the example, suppress messages about working % with an MPC controller. % Copyright 2015 The MathWorks, Inc. old_status = mpcverbosity('off'); %% % Create the plant model. G = rss(5,2,3); G.D = 0; G = setmpcsignals(G,'mv',1,'md',2,'ud',3,'mo',1,'uo',2); %% % Configure the MPC controller with nonzero nominal values, weights, and input targets. C = mpc(G,0.1); C.Model.Nominal.U = [0.7 0.8 0]; C.Model.Nominal.Y = [0.5 0.6]; C.Model.Nominal.DX = rand(5,1); C.Weights.MV = 2; C.Weights.OV = [3 4]; C.MV.Target = [0.1 0.2 0.3]; %% % |C| is an unconstrained MPC controller. Specifying |C.Model.Nominal.DX| % as nonzero means that the nominal values are not at steady state. % |C.MV.Target| specifies three preview steps. %% % Convert |C| to a state-space model. sys = ss(C); %% % The output, |sys|, is a seventh-order SISO state-space model. The seven % states include the five plant model states, one state from the default % input disturbance model, and one state from the previous move, |u(k-1)|. %% % Restore |mpcverbosity|. mpcverbosity(old_status);