The versions of software used for the preparation of this book were:
MATLAB | 5.3.1 |
Control System Toolbox | 4.2.1 |
Model Predictive Control Toolbox | 1.0.4 |
Optimization Toolbox | 2.0 |
Note that all the .m files available from this page are in plain text and they are all very small (max 35 kbytes).
Basic software, using MATLAB and Control Toolbox only, as described in Chapter 1.
basicmpc.m Basic predictive control of SISO system without constraints.
After Chapter 1, the
Model Predictive Control Toolbox
is needed (or comparable software). Some description of this
Toolbox is given in Appendix C of the book, but there is also a complete
tutorial available. Some of the
Toolbox functions have been modified slightly to enhance the
functionality, as described in Appendix C. These modified functions need
the
Optimization Toolbox as well as the Model Predictive
Control Toolbox.
These are available here:
scmpc2.m
Allows simulation of MPC with linear state-space model as the
plant. (Needs function qpsoft.m)
The function scmpc.m has been modified to add the following functionality:
scmpc3.m As scmpc2, but allows definition of Reference Trajectory without anticipation of future set-point trajectory. (See Figure 7.17 in book.) Thanks to Simon Redhead for implementing this modification.
scmpc4.m As scmpc2, but allows definition of Reference Trajectory with anticipation of future set-point trajectory. (See Figure 7.18 in book.) Thanks to Simon Redhead for implementing this modification.
scmpcnl2.m
Allows simulation of MPC with nonlinear Simulink model as the
plant. (Needs function qpsoft.m)
Here is a collection of Matlab software related to examples and problems which appear in the book. Most of these use the modified MPC Toolbox functions listed above.
c2dd.m Example solution to Exercise 2.9. Builds discrete-time model, accounting for computational delay.
disturb.m Pulse disturbance on Citation aircraft, with constraint on climb rate. See section 2.7.
disturb2.m Pulse disturbance on Citation aircraft, with set-point for climb rate. See section 2.7 and Exercise 3.11.
evaporator.mdl Simulink model of Newell and Lee evaporator (see Section 9.2).
gpc2mod.m Builds a state-space model, from a GPC model, in the MOD format used by the MPC Toolbox. Uses function gpc2ss.
gpc2ss.m Builds a state-space model and observer gain matrix, from a GPC model. (Follows section 4.2.5 of the book.)
makecita.m Builds linearised model of Citation aircraft for Problem 10 of Chapter 2.
mismatch.m Simulates effect of plant-model mismatch, using the MPC Toolbox and the Citation aircraft model.
mismatch2.m Simulates effect of plant-model mismatch, using the MPC Toolbox and the Citation aircraft model with soft output constraints.
mkdelta.m Builds transfer function matrix W(z) for additive uncertainty of Shell oil fractionator model, equation (9.15), after conversion to disrete time.
mkoilfr.m Builds models of the Shell heavy oil fractionator example. See Section 9.1.
oilfr20.mat Matlab data file (.mat format) to create 20-state approximate model of Shell heavy oil fractionator. See Section 9.1.3.
simevap.m Matlab file which runs simulation of the Newell and Lee evaporator, allowing experimentation with re-linearisation, as in Section 9.2 and Exercise 9.4.
swimpool.m Matlab function which simulates the swimming pool example, with disturbance model and observer. See Section 7.4 and Exercise 7.6.
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This page last updated: 16 September 2002.