TY - GEN
T1 - Is multiple-objective model-predictive control "optimal"?
AU - Hackl, C. M.
AU - Larcher, F.
AU - Dötlinger, A.
AU - Kennel, R. M.
PY - 2013
Y1 - 2013
N2 - We consider multiple-objective model-predictive control (MPC) of a linear time-invariant (LTI) single-input single-output (SISO) system (for simplicity without input constraints and/or disturbances). The performance index is the sum of weighted convex functionals J = Σi=1nw iJi (with wi ≥ 0). Although, by theory, the overall model-predictive control problem has a unique, globally optimal solution, this does not imply optimality of each sub-performance index Ji. To achieve 'desirable' control performance, one has to find 'decent' weighting factors wi; often done by 'trial-and-error' which should be avoided, since weighting factor design might be not intuitive (even for LTI SISO systems without constraints; as we will show). The inherent difficulty lies in the mismatch between the 'human performance index' (the optimality measure in the mind of the control engineer) and the implemented performance index J. In this paper, we illustrate these difficulties for a simple, linear third-order system and present some (old and new) approaches to ease weighting factor design. We do not give full answers but discuss first ideas which are admissible within the theoretical framework of standard MPC of LTI SISO systems.
AB - We consider multiple-objective model-predictive control (MPC) of a linear time-invariant (LTI) single-input single-output (SISO) system (for simplicity without input constraints and/or disturbances). The performance index is the sum of weighted convex functionals J = Σi=1nw iJi (with wi ≥ 0). Although, by theory, the overall model-predictive control problem has a unique, globally optimal solution, this does not imply optimality of each sub-performance index Ji. To achieve 'desirable' control performance, one has to find 'decent' weighting factors wi; often done by 'trial-and-error' which should be avoided, since weighting factor design might be not intuitive (even for LTI SISO systems without constraints; as we will show). The inherent difficulty lies in the mismatch between the 'human performance index' (the optimality measure in the mind of the control engineer) and the implemented performance index J. In this paper, we illustrate these difficulties for a simple, linear third-order system and present some (old and new) approaches to ease weighting factor design. We do not give full answers but discuss first ideas which are admissible within the theoretical framework of standard MPC of LTI SISO systems.
UR - http://www.scopus.com/inward/record.url?scp=84894446365&partnerID=8YFLogxK
U2 - 10.1109/SLED-PRECEDE.2013.6684475
DO - 10.1109/SLED-PRECEDE.2013.6684475
M3 - Conference contribution
AN - SCOPUS:84894446365
SN - 9781479906819
T3 - SLED/PRECEDE 2013 - 2013 IEEE International Symposium on Sensorless Control for Electrical Drives and Predictive Control of Electrical Drives and Power Electronics
BT - SLED/PRECEDE 2013 - 2013 IEEE International Symposium on Sensorless Control for Electrical Drives and Predictive Control of Electrical Drives and Power Electronics
PB - IEEE Computer Society
T2 - 2013 IEEE International Symposium on Sensorless Control for Electrical Drives and Predictive Control of Electrical Drives and Power Electronics, SLED/PRECEDE 2013
Y2 - 17 October 2013 through 19 October 2013
ER -