DocumentCode :
2584980
Title :
Low-complexity model predictive control of ElectroMagnetic actuators
Author :
Hermans, R.M. ; Lazar, M. ; Cairano, S. Di ; Kolmanovsky, I.
Author_Institution :
Dept. of Electr. Eng., Eindhoven Univ. of Technol., Eindhoven, Netherlands
fYear :
2009
fDate :
18-23 May 2009
Firstpage :
1972
Lastpage :
1977
Abstract :
Electromagnetically driven mechanical systems are characterized by fast non-linear dynamics that are subject to physical and control constraints. This paper describes a Model Predictive Controller (MPC) for a general ElectroMagnetic (EM) actuator that satisfies both the performance constraints and the strict requirements on the computation time. Novel aspects of the MPC design are a one-step-ahead prediction horizon and an infinity-norm artificial Lyapunov function that is employed to drive the system to a desired reference. An additional optimization variable is introduced to relax the conditions on the Lyapunov function, which is not forced to decrease monotonically. This feature improves feasibility considerably. The resulting MPC problem is transformed into a low-complexity linear program that can be solved by modern microprocessors within tenths of milliseconds. An even simpler piecewise affine explicit controller is obtained via multiparametric programming. Simulation results are reported and compared with the results achieved by existing state-of-the-art explicit MPC.
Keywords :
Lyapunov methods; computational complexity; control system synthesis; electromagnetic actuators; linear programming; nonlinear control systems; predictive control; MPC design; electromagnetic actuator; infinity-norm artificial Lyapunov function; linear program; low-complexity model predictive control; mechanical system; microprocessor; multiparametric programming; nonlinear dynamics; optimization variable; physical constraint; piecewise affine explicit controller; prediction horizon; Actuators; Control systems; Electromagnetic modeling; H infinity control; Lyapunov method; Mechanical systems; Microprocessors; Nonlinear control systems; Predictive control; Predictive models; Mechatronics; predictive control for nonlinear systems; stability of nonlinear systems;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
EUROCON 2009, EUROCON '09. IEEE
Conference_Location :
St.-Petersburg
Print_ISBN :
978-1-4244-3860-0
Electronic_ISBN :
978-1-4244-3861-7
Type :
conf
DOI :
10.1109/EURCON.2009.5167917
Filename :
5167917
Link To Document :
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