there is different way for solving dynamic programing :

1- by using  (treeviewer function)= this method use tree theory and symplex method for solving linear dynamic programming. 

2-by mfile code.

you can use ''Solving Optimization Problems using the Matlab Optimization

Toolbox - a Tutorial''

i checked this toolbox .there are some functions for linear programming not dynamic  programming!!!!!!!!!

have anyone worked on a control system which needs to use optimal control techniques specially dynamic programing? i want to know how to implement dynamic programming algorithm in MATLAB mfile?

In these slides:

http://support.dce.felk.cvut.cz/pub/roubalj/teaching/ZRS/lectures/ZRS_QOC.pdf

you can find the MATLAB code of an example of application of dynamic programming to the control of a discrete-time linear dynamical system..Maybe it is not as general as what you probably need, but it can be a good starting point

See the following link:

There are dynamic programming function and well-organized documents.

I hope this can help you.

http://www.idsc.ethz.ch/Downloads/DownloadFiles/dpm/index

It is not clear if you are interested in a backwards-in-time algorithm (which is classically solved by iterating the Bellman equation for all states) or in a forward-in-time one where you are given one state at a time. Perhaps, since you are asking about a control system which is generally applicable to non-linear systems you might want to take a look at the approximate dynamic programming and the corresponding literature. There are plenty of implementation examples.

The optimization of power management strategy of hybrid vehicles is one example where Dynamic Programming has been extensively used. The Institute for Dynamic Systems and Control at TU Zürich has developed a generic dynmaic programming function in Matlab. The function can be downloaded from:http://www.idsc.ethz.ch/Downloads/DownloadFiles/dpm/index, even though I would prefer to write my own code.

Hi. I very much wished to help you. But I am engaged to recognition of the person on the basis of photoportrait

Here is an example of DP algorithm implementation, just to start with. Define your own system model, f(x,u,w), and disturbances, P{x}(u,w). I hope it will help! 

J(N+1,:) = 0;

for k = N:(-1):1

    for xi = 1:length(S)

        if ~isempty(C{k,xi})

             EJ = inf(length(C{k,xi}),1);

            for ui = 1:length(C{k,xi})

                EJ(ui) = P{xi}(ui,:)*(g(S(xi),C{k,xi}(ui),D) + J(k+1,f(xi,C{k,xi}(ui),D))');

            end

            [J(k,xi),uiOpt] = min(EJ);

            mu{k,xi} = C{k,xi}(uiOpt);

        end

    end

end

Hi. Sorry, I with this theme am not engaged.

Can any one help me with dynamic programming of this linear quadratic regulator (LQR) system in order to find optimal control and optimal trajectory in matlab m.file

?????????????????????????i should discritisize it with Ts=0.1 and i should also do interpolations and extrapolation!!!!!!!!!!!!

Here what you was looking for. ;)

I tested it and it works as expected. Hope to be helpful. 

Alex.

--------------------------------------------

function [K,S]=lqrt(F,Q,R,A,B,t,tf)

% [K,S]=lqrt(F,Q,R,A,B,t,tf)

% Linear quadratic regulator design for continuous systems.

% Calculates the optimal feedback gain (time varing)

% matrix K(t) such that the feedback law u = -K(t)x minimizes the cost

% function:

%

% J =x(tf)'Fx(tf) + Integral {x'Qx + u'Ru} dt

%

% subject to the constraint equation:

% .

% x = Ax + Bu

%

% Also returned is S(t), the solution to the associated Riccati equation

% . -1

% S + SA + A'S - SB * R * B'S + Q = 0

%

% See also: LQR, LQRY, LQR2, and REG.

% Written by Giampiero Campa , 6-11-94.

[n,n]=size(A);

H=[A -B*inv(R)*B'; -Q -A'];

fi=expm(H*(tf-t));

fi11=fi(1:n,1:n);

fi12=fi(1:n,n+1:2*n);

fi21=fi(n+1:2*n,1:n);

fi22=fi(n+1:2*n,n+1:2*n);

S=inv(fi22-F*fi12)*(fi21-F*fi11);

K=inv(R)*B'*S;

-------------------------------------

Source: http://www.mathworks.com/matlabcentral/fileexchange/1047-mimotool/content/jtools/lqrt.m

Thanks for all sharing their thoughts. I found the answers suggested by @Inseok Park and @ Farouk Odeim very useful. However, both links are broken. I spent some time to find the correct link. It is here: http://www.idsc.ethz.ch/research-guzzella-onder/downloads.html

Though could be found by google search of the previous broken URLs.

Interesting lecture is available from here: http://sail.usc.edu/~lgoldste/Ling285/Slides/Lect25_handout.pdf