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mpt_blockingMatrices

PURPOSE ^

MPT_BLOCKINGMATRICES Constructs matrices for the CFTOC problem for move blocking strategies

SYNOPSIS ^

function [Matrices]=mpt_blockingMatrices(Matrices,sysStruct,probStruct,Options)

DESCRIPTION ^

MPT_BLOCKINGMATRICES Constructs matrices for the CFTOC problem for move blocking strategies

 [Matrices]=mpt_blockingMatrices(Matrices,sysStruct,probStruct,Options)

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 DESCRIPTION
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 Constructs cost and constraint matrices for the finite time constrained 
 optimal control problem on linear time-invariant systems with quadratic
 cost (2-norm) in the case where inputs or their differences are fixed to be
 constant over a certain number of steps during the prediction horizon N.
 Matrices received from function mpt_constructMatrices are compressed
 depending on probStruct.inputblocking and probStruct.deltablocking. 

 Degrees of freedom are reduced from full degrees of freeedom m * N (m=number 
 of inputs, N=prediction horizon) in the non blocking case to m * M (M < N,
 M independent decision variables in blocked input sequence) in the case where
 inputs are their differences are fixed to be constant during the prediction
 horizon.


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 INPUT
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 Matrices          NORM=2
 --------
                   G,W,E,H,F,Y,Cf,Cx,Cc  - matrices of the problem, i.e. 

 sysStruct        - System structure in the sysStruct format

 probStruct       - Problem structure in the probStruct format
                  
                   - NORM=2
                                   
                  - horizon          
                     Prediction horizon N; How many time steps are considered.

                  - inputblocking
                    Fix inputs u_k to be constant over a certain number of steps
                    in the prediction horizon.
                     
                    inputblocking=[n1 n2 ... nk], \sum_{n1}^{nk} = N.
                    Entries define how many consecutive inputs are fixed to be 
                    constant. Sum of all entries has to be equal the prediction
                    horizon N.
                     
                    Example:      N = 5, inputblocking = [1 4]
                                  First predicted input is independent and the
                                  next 4 predicted inputs are fix to be constant,
                                  i.e. u1, u2=u3=u4=u5.

                  - deltablocking
                    Fix difference u_k - u_{k+1} to be constant over a certain number 
                    of steps in the prediction horizon.
                       
                    deltablocking = [1 ... nk ... N], 1 < .. < .. nk < .. < N
                    Entries defines wich inputs are independent (=decision variables),
                    inputs in between are interpolated (=constant differences).
                    
                    Example:      N = 5, deltablocking = [1 5]
                                  First input u1 and last input u5 are independent,
                                  inputs in between are interpolated, i.e.
                                  u1-u2 = u2-u3 = u3-u4 = u4-u5.


 Note: If Options is missing or some of the fields are not defined, the default
       values from mptOptions will be used

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 OUTPUT                                                                                                    
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 Matrices              NORM=2
 --------
                       Compressed matrices for fixed inputs or fixed differences in
                       prediction horizon. 

                       G,W,E,H,F,Y,Cf,Cx,Cc  - matrices of the problem, i.e. 

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 LITERATURE
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 "Move Blocking Strategies in Receding Horizon Control"
 R. Cagienard, P. Grieder, E. C. Kerrigan and M. Morari, 2004, submitted
 check http://control.ee.ethz.ch for latest info

 see also MPT_CONSTRUCTMATRICES

 Copyright is with the following author(s):

 (C) 2004 Raphael Cagienard, Automatic Control Laboratory, ETH Zurich,
 (C) 2003 Pascal Grieder, Automatic Control Laboratory, ETH Zurich,
          cagienard@control.ee.ethz.ch

CROSS-REFERENCE INFORMATION ^

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