- Ajuda do Scilab
 - CACSD
 - formal_representation
 - Plot and display
 - plzr
 - pol2des
 - routh_t
 - ssprint
 - syslin
 - abinv
 - arhnk
 - arl2
 - arma
 - arma2p
 - arma2ss
 - armac
 - armax
 - armax1
 - arsimul
 - augment
 - balreal
 - bilin
 - bstap
 - cainv
 - calfrq
 - canon
 - ccontrg
 - cls2dls
 - colinout
 - colregul
 - cont_mat
 - contr
 - contrss
 - copfac
 - csim
 - ctr_gram
 - damp
 - dcf
 - ddp
 - dhinf
 - dhnorm
 - dscr
 - dsimul
 - dt_ility
 - dtsi
 - equil
 - equil1
 - feedback
 - findABCD
 - findAC
 - findBD
 - findBDK
 - findR
 - findx0BD
 - flts
 - fourplan
 - freq
 - freson
 - fspec
 - fspecg
 - fstabst
 - g_margin
 - gamitg
 - gcare
 - gfare
 - gfrancis
 - gtild
 - h2norm
 - h_cl
 - h_inf
 - h_inf_st
 - h_norm
 - hankelsv
 - hinf
 - imrep2ss
 - inistate
 - invsyslin
 - kpure
 - krac2
 - lcf
 - leqr
 - lft
 - lin
 - linf
 - linfn
 - linmeq
 - lqe
 - lqg
 - lqg2stan
 - lqg_ltr
 - lqr
 - ltitr
 - macglov
 - minreal
 - minss
 - mucomp
 - narsimul
 - nehari
 - noisegen
 - nyquistfrequencybounds
 - obs_gram
 - obscont
 - observer
 - obsv_mat
 - obsvss
 - p_margin
 - parrot
 - pfss
 - phasemag
 - ppol
 - prbs_a
 - projsl
 - repfreq
 - ric_desc
 - ricc
 - riccati
 - rowinout
 - rowregul
 - rtitr
 - sensi
 - sident
 - sorder
 - specfact
 - st_ility
 - stabil
 - sysfact
 - syssize
 - time_id
 - trzeros
 - ui_observer
 - unobs
 - zeropen
 
Please note that the recommended version of Scilab is 2026.0.0. This page might be outdated.
See the recommended documentation of this function
lqr
LQ compensator (full state)
Calling Sequence
[K,X]=lqr(P12)
Arguments
- P12
 syslinlist (state-space linear system)- K,X
 two real matrices
Description
lqr  computes the linear optimal LQ full-state gain
            for the plant P12=[A,B2,C1,D12] in continuous or
            discrete time.
P12 is a syslin list (e.g. P12=syslin('c',A,B2,C1,D12)).
The cost function is l2-norm of z'*z with z=C1 x + D12 u
            i.e. [x,u]' * BigQ * [x;u] where
[C1' ] [Q S] BigQ= [ ] * [C1 D12] = [ ] [D12'] [S' R]
The gain K is such that A + B2*K is stable.
X is the stabilizing solution of the Riccati equation.
For a continuous plant:
K=-inv(R)*(B2'*X+S)
For a discrete plant:
X=A'*X*A-(A'*X*B2+C1'*D12)*pinv(B2'*X*B2+D12'*D12)*(B2'*X*A+D12'*C1)+C1'*C1;
K=-pinv(B2'*X*B2+D12'*D12)*(B2'*X*A+D12'*C1)
An equivalent form for X is
with Abar=A-B2*inv(R)*S' and Qbar=Q-S*inv(R)*S'
The 3-blocks matrix pencils associated with these Riccati equations are:
discrete continuous |I 0 0| | A 0 B2| |I 0 0| | A 0 B2| z|0 A' 0| - |-Q I -S| s|0 I 0| - |-Q -A' -S| |0 B2' 0| | S' 0 R| |0 0 0| | S' -B2' R|
![]()  | Caution: It is assumed that matrix R is non singular. In particular,
                the plant must be tall (number of outputs >= number of inputs).  | 
Examples
A=rand(2,2);B=rand(2,1); //two states, one input Q=diag([2,5]);R=2; //Usual notations x'Qx + u'Ru Big=sysdiag(Q,R); //Now we calculate C1 and D12 [w,wp]=fullrf(Big);C1=wp(:,1:2);D12=wp(:,3:$); //[C1,D12]'*[C1,D12]=Big P=syslin('c',A,B,C1,D12); //The plant (continuous-time) [K,X]=lqr(P) spec(A+B*K) //check stability norm(A'*X+X*A-X*B*inv(R)*B'*X+Q,1) //Riccati check P=syslin('d',A,B,C1,D12); // Discrete time plant [K,X]=lqr(P) spec(A+B*K) //check stability norm(A'*X*A-(A'*X*B)*pinv(B'*X*B+R)*(B'*X*A)+Q-X,1) //Riccati check
See Also
| Report an issue | ||
| << lqg_ltr | CACSD | ltitr >> | 
