APM – Simple and Fast MPC Algorithm for LTI SISO Systems
the author of the article can submit here a request for assignment of a DOI number to this resource!
Cost of the service: euros 10,00 (for a DOI)
In this paper a simple and fast APM (Asymptotic Predictive Method) algorithm for real time control of LTI SISO (Linear Time Invariant Single Input Single Output) systems has been presented. Optimal control signal on each sampling period is calculated using trivial counter control sequence instead of demanding QP (Quadratic Programming) numerical method. Using Matlab simulation, APM control has been compared with demanding standard MPC (Model Predictive Control) algorithm on some typical high order dynamic systems with or without output constraints. Simulation results confirm competitiveness of APM algorithm with minor software and hardware demands.
Copyright © 2014 Praise Worthy Prize - All rights reserved.
K. S. Holkar, L. M. Waghmare, An Overview of Model Predictive Control, International Journal of Control and Automation, vol. 3, no. 4, 47-63, 2010.
J. M. Macijeowski, Predictive Control with Constraints (Pearson Education Ltd, 2001).
B. Kouvaritakis, M. Cannon, J.A. Rossiter, Who needs QP for linear MPC anyway ?, Automatica, no. 38, 879 – 884, 2002.
Y. Wang, S. Boyd, Fast Model Predictive Control Using Online Optimization, IEEE Transactions on Control Systems Technology, vol.18, no. 2, 267-278, 2010.
M. Evans, M. Cannon, B. Kouvaritakis, Linear stochastic MPC under finitely supported Multiplicative uncertainty, American Control Conference Fairmont Queen Elizabeth, pp. 1-5, 2012.
Vozak, D., Veseli, V., Stable predictive control with input constraints based on variable gain approach, (2014) International Review of Automatic Control (IREACO), 7 (2), pp. 131-139.
M. A. Müller, and F. Allgöwer, Improving performance in model predictive control: Switching cost functionals under average dwell-time, Automatica, no. 48, 402-409, 2012.
Draghici, D., Ciresan, A., Gurbina, M., Lascu, D., Predictive trailing triangle modulation peak current control in DC-DC converters, (2014) International Review of Automatic Control (IREACO), 7 (1), pp. 74-81.
A. Bemporad, Explicit Model Predictive Control, Swiss Federal Institute of Technology (ETH) Zurich, 1-54, 2009.
E. Saletovic, T. Mateljan, Control of linear stationary stochastic systems with constraints - APM vs PID vs Matlab MPC, Iti 2012, pp. 467-472, Cavtat, June 2012.
E. Saletovic. APM (Simple MPC) vs. PID – Detailed Comparison, International Journal of Advanced Computer Research, vol. 4, no. 1, 26-31, March-2014.
I. Batina, Model predictive control for stochastic systems by randomized algorithms, Ph.D. dissertation, Tehnische Universiteit Eindhoven, 2004.
D. Q. Mayne, J. B. Rawlings, C. V. Rao, P. O. M. Scokaert, Constrained model predictive control: Stability and optimality, Automatica, no. 36, 789-814, 2000.
M. Rubagotti, P. Patrinos, and A. Bemporad, Stabilizing linear model predictive control under inexact numerical optimization, IEEE Trans. Automatic Control, vol. 59, no. 6, 1660–1666, 2014.
M. Zeilinger, M. Morari, C. N. Jones, Soft Constrained Model Predictive Control With Robust Stability Guarantees, IEEE Transactions On Automatic Control, vol. 59, no. 5, 1190-1202, 2014.
D. Mayne, M. Seron, S. Rakovic, Robust model predictive control of constrained linear systems with bounded disturbances, Automatica, no. 41, 219–234, 2005.
- There are currently no refbacks.
Please send any question about this web site to email@example.com
Copyright © 2005-2021 Praise Worthy Prize