Mercurial > hg > octave-jordi
view scripts/control/base/dlqe.m @ 7016:93c65f2a5668
[project @ 2007-10-12 06:40:56 by jwe]
author | jwe |
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date | Fri, 12 Oct 2007 06:41:26 +0000 |
parents | 4c8a2e4e0717 |
children | a1dbe9d80eee |
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## Copyright (C) 1993, 1994, 1995 Auburn University ## ## This file is part of Octave. ## ## Octave is free software; you can redistribute it and/or modify it ## under the terms of the GNU General Public License as published by ## the Free Software Foundation; either version 3 of the License, or (at ## your option) any later version. ## ## Octave is distributed in the hope that it will be useful, but ## WITHOUT ANY WARRANTY; without even the implied warranty of ## MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU ## General Public License for more details. ## ## You should have received a copy of the GNU General Public License ## along with Octave; see the file COPYING. If not, see ## <http://www.gnu.org/licenses/>. ## -*- texinfo -*- ## @deftypefn {Function File} {[@var{l}, @var{m}, @var{p}, @var{e}] =} dlqe (@var{a}, @var{g}, @var{c}, @var{sigw}, @var{sigv}, @var{z}) ## Construct the linear quadratic estimator (Kalman filter) for the ## discrete time system ## @iftex ## @tex ## $$ ## x_{k+1} = A x_k + B u_k + G w_k ## $$ ## $$ ## y_k = C x_k + D u_k + v_k ## $$ ## @end tex ## @end iftex ## @ifinfo ## ## @example ## x[k+1] = A x[k] + B u[k] + G w[k] ## y[k] = C x[k] + D u[k] + v[k] ## @end example ## ## @end ifinfo ## where @var{w}, @var{v} are zero-mean gaussian noise processes with ## respective intensities @code{@var{sigw} = cov (@var{w}, @var{w})} and ## @code{@var{sigv} = cov (@var{v}, @var{v})}. ## ## If specified, @var{z} is @code{cov (@var{w}, @var{v})}. Otherwise ## @code{cov (@var{w}, @var{v}) = 0}. ## ## The observer structure is ## @iftex ## @tex ## $$ ## z_{k|k} = z_{k|k-1} + l (y_k - C z_{k|k-1} - D u_k) ## $$ ## $$ ## z_{k+1|k} = A z_{k|k} + B u_k ## $$ ## @end tex ## @end iftex ## @ifinfo ## ## @example ## z[k|k] = z[k|k-1] + L (y[k] - C z[k|k-1] - D u[k]) ## z[k+1|k] = A z[k|k] + B u[k] ## @end example ## @end ifinfo ## ## @noindent ## The following values are returned: ## ## @table @var ## @item l ## The observer gain, ## @iftex ## @tex ## $(A - ALC)$. ## @end tex ## @end iftex ## @ifinfo ## (@var{a} - @var{a}@var{l}@var{c}). ## @end ifinfo ## is stable. ## ## @item m ## The Riccati equation solution. ## ## @item p ## The estimate error covariance after the measurement update. ## ## @item e ## The closed loop poles of ## @iftex ## @tex ## $(A - ALC)$. ## @end tex ## @end iftex ## @ifinfo ## (@var{a} - @var{a}@var{l}@var{c}). ## @end ifinfo ## @end table ## @end deftypefn ## Author: A. S. Hodel <a.s.hodel@eng.auburn.edu> ## Created: August 1993 ## Modified for discrete time by R. Bruce Tenison (btenison@eng.auburn.edu) ## October, 1993 ## Modified by Gabriele Pannocchia <pannocchia@ing.unipi.it> ## July 2000 function [l, m, p, e] = dlqe (a, g, c, sigw, sigv, s) if (nargin != 5 && nargin != 6) error ("dlqe: invalid number of arguments"); endif ## The problem is dual to the regulator design, so transform to dlqr call. if (nargin == 5) [k, m, e] = dlqr (a', c', g*sigw*g', sigv); else [k, m, e] = dlqr (a', c', g*sigw*g', sigv, g*s); warning ("dlqe: use dkalman when there is a cross-covariance term"); endif l = m*c'/(c*m*c'+sigv); p = m - m*c'/(c*m*c'+sigv)*c*m; endfunction