Mpc@Cb Presentation En V2009 03 03

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MPC@CB is a software for model predictive control of continuous processes using Matlab. It allows the user to specify a control problem such as regulation, trajectory tracking or time optimization with constraints. The software has been applied successfully to problems like powder coating curing and vial lyophilization. To use MPC@CB for a control problem, contact the author via email.

Technology

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MPC: the idea (born in the ‘70) Reference k+Nc k+Np Process Model prediction Futur Past Control Present : k Morari, M.; Lee, J. L. Model predictive control: past, present and future. Computers and Chemical Engineering 1999, 23, 667–682

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PID (regulation) MPC@CB (dynamic optimization + constraint)  Output constraint, with a parameter error MPC@CB: application 1: powder coating curing ( Abid et al., 2007 )

PID (régulation)  Output constraint, with a parameter error MPC@CB (dynamic optimization + constraint) ,[object Object],[object Object],[object Object],[object Object],Since the output constraint is saturated, the control move decreases MPC@CB: application 1: powder coating curing ( Abid et al., 2007 )

Sublimation time minimization Maximize the sublimation front move H(t) (Contraints on the input) ( Contraint on the output ) Ending condition: stop when H(t)=L MPC@CB: application 2: vial lyophilisation ( Daraoui et al., 2007 )

End : H(t)=L MPC@CB: application 2: vial lyophilisation ( Daraoui et al., 2007 )

Since the output constraint is saturated, the control move decreases MPC@CB: application 2: vial lyophilisation ( Daraoui et al., 2007 )

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Abstract Explicit Model Predictive Control approach provides offline computation of the optimization law by Multi Parametric Quadratic Programming. The solution is Piece wise affine in nature. It is explicit representation of the system states and control inputs. Such law then can be solved using binary search tree and can be evaluated for fast dynamic systems. Implementing such controllers can be done on microcontroller or ASIC/FPGA. DC Motor Speed Control - one of the benchmark systems is discussed here in this context. Its PWA law obtained, simulation of closed loop e-MPC is presented and its implementation approach using MPT toolbox and other such toolboxes is shown in brief. Index Terms: Model Predictive Control, explicit, Piece-wise Affine, and Multi Parametric Toolbox

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Mpc@Cb Presentation En V2009 03 03

2. MPC: the idea (born in the ‘70) Reference k+Nc k+Np Process Model prediction Futur Past Control Present : k Morari, M.; Lee, J. L. Model predictive control: past, present and future. Computers and Chemical Engineering 1999, 23, 667–682

8. PID (regulation) MPC@CB (dynamic optimization + constraint)  Output constraint, with a parameter error MPC@CB: application 1: powder coating curing ( Abid et al., 2007 )

10. Sublimation time minimization Maximize the sublimation front move H(t) (Contraints on the input) ( Contraint on the output ) Ending condition: stop when H(t)=L MPC@CB: application 2: vial lyophilisation ( Daraoui et al., 2007 )

11. End : H(t)=L MPC@CB: application 2: vial lyophilisation ( Daraoui et al., 2007 )

12. Since the output constraint is saturated, the control move decreases MPC@CB: application 2: vial lyophilisation ( Daraoui et al., 2007 )

13.

Mpc@Cb Presentation En V2009 03 03

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