function?f=mpcsetup（ABCDpmQRx0u0）
%?MPCSETUP??Set-up?State?Space?MPC?controller
%
%???SSMPC=MPCSETUP（ABCDPMQRX0U0）?returns?a?function?handle?for?a
%???state?space?model?predictive?control?for?the?state?space?model
%???x（k+1）?=?Ax（k）?+?Bu（k）
%???y（k）???=?Cx（k）?+?Du（k）
%???with?predictive?horizon?P?and?moving?horizon?M?performance?weights?of
%???output?Q?and?of?input?R?initial?state?X0?and?initial?control?U0.
%
%???SSMPC?is?the?online?controller?which?can?be?called?as?follows?
%
%???U?=?SSMPC（YREF）?returns?the?control?input?U?（nu?by?1）?according?to
%???current?measured?output?Y?（1?by?ny）?and?future?reference?REF?（nr?by
%???ny?nr>=1）.?
%
%???The?MPC?minimize?the?following?performance?criterion:
%
%???J?=?min?Y‘QY?+?U‘RU
%
%???The?online?controller?is?implemented?as?a?nested?function?so?that?the
%???state?of?the?internal?model?can?be?kept?inside?of?the?function.?This
%???simplifies?the?input?and?output?interface?of?the?online?controller.
%
%?See?also:?mpc?dmc

%?Version?1.0?by?Yi?Cao?at?Cranfield?University?on?20?April?2008

%?Example:?2-CSTR?model
%{
%?Six-state?model
A=[?0.1555??-13.7665???-0.0604?????????0?????????0?????????0
????0.0010????1.0008????0.0068?????????0?????????0?????????0
?????????0????0.0374????0.9232?????????0?????????0?????????0
????0.0015???-0.1024???-0.0003????0.1587??-13.6705???-0.0506
?????????0????0.0061?????????0????0.0006????0.9929????0.0057
?????????0????0.0001?????????0?????????0????0.0366????0.9398];
Bu=[0.0001???????0
?????????0???????0
???-0.0036???????0
?????????0??0.0001
?????????0???????0
?????????0?-0.0028];
Bd=[??????0?????????0
??????????0?????????0
?????0.0013?????????0
??????????0?????????0
??????????0?????????0
??????????0????0.0008];
C=[0?362.995?0?0?0?0
???0?0?0?0?362.995?0];
D=zeros（22）;
%?Prediction?horizon?and?moving?horizon
p=10;
m=3;
%?Performance?wights
Q=1.5*eye（2*p）;
R=eye（2*m）;
%?MPC?set-up
ssmpc=mpcsetup（ABuCDpmQR）;
%?Simulation?length?and?variables?for?results
N=1500;
x0=zeros（61）;
Y=zeros（N2）;
U=zeros（N2）;
%?Predefined?reference
T=zeros（N2）;
T（10:N:）=1;
T（351:N:）=3;
T（600:N:）=5;
T（1100:N:）=3;
%?Simulation
for?k=1:N
????%?Process?disturbances
????w=Bd*（rand（21）-0.5）*2;
????%?Measurements?noise
????v=0.01*randn（21）;
????%?actual?measurement
????y=C*x0+v;
????%?online?controller
????u=ssmpc（yT（k:end:））;
????%?plant?update
????x0=A*x0+Bu*u+w;
????%?save?results
????Y（k:）=y‘;
????U（k:）=u‘;
end
t=（0:N-1）*0.1;
subplot（211）
plot（tYtT‘r--‘‘linewidth‘2）
title（‘output?and?setpoint‘）
ylabel（‘temp?C^\circ‘）
legend（‘T_1‘‘T_2‘‘Ref‘‘location‘‘southeast‘）
subplot（212）
stairs（tU‘linewidth‘2）
legend（‘u_1‘‘u_2‘‘location‘‘southeast‘）
title（‘input‘）
ylabel（‘flow?rate?m^3/s‘）
xlabel（‘time?s‘）
%}

%?Input?and?output?check
error（nargchk（810nargin））;
error（nargoutchk（11nargout））;

%?dimension?of?the?system
nx=size（A1）;
[nynu]=size（D）;

%

?屬性????????????大小?????日期????時(shí)間???名稱
-----------?---------??----------?-----??----
?????目錄???????????0??2015-11-13?11:04??基于狀態(tài)空間的模型預(yù)測(cè)控制ssmpc\
?????文件????????1327??2009-05-20?16:16??基于狀態(tài)空間的模型預(yù)測(cè)控制ssmpc\license.txt
?????文件????????4696??2008-04-22?00:12??基于狀態(tài)空間的模型預(yù)測(cè)控制ssmpc\mpcsetup.m
?????文件????????3819??2008-04-22?00:11??基于狀態(tài)空間的模型預(yù)測(cè)控制ssmpc\ssmpctutorial.m