Low order sampled data H∞ control using the delta operator and LMIs
2004 (English)In: Decision and Control, 2004. CDC. 43rd IEEE Conference on, 2004, Vol. 4, p. 4479-4484Conference paper, Published paper (Refereed)
Abstract [en]
A procedure for H∞ optimization of low order controllers for discrete-time and sampled-data systems is presented in this paper. Generally, low order H∞ controllers may be achieved by solving bilinear matrix inequalities (BMIs). In this paper an iterative alternation between two LMIs gives a suboptimal solution. To avoid local minima in this search the initial controller is obtained by a frequency weighted controller reduction scheme, where the closed loop properties of a full order controller is taken into account. A minimal number of parameters in the state space realization of the controller also reduces the complexity and improves numerical robustness. The complete presentation is based on delta operator models, which shows a close relationship between the continuous- and discrete-time solutions. The sensitivity of the ordinary discrete-time shift operator LMI formulation to small sampling periods is also analyzed.
Place, publisher, year, edition, pages
2004. Vol. 4, p. 4479-4484
Keywords [en]
H∞control, H∞ optimisation, closed loop systems, discrete time systems, iterative methods, linear matrix inequalities, sampled data systems, H∞ optimization, closed loop properties, complexity, delta operator, discrete time shift operator, discrete-time systems, frequency weighted controller reduction scheme, full order controller, iterative alternation, low order controllers, low order sampled data H H∞ control, numerical robustness, state space, Automatic control, Control systems, Frequency, Robust control, Robustness, Sampling methods, Signal processing, State-space methods, Weight control
National Category
Control Engineering
Research subject
ENGINEERING, Manufacturing and materials engineering
Identifiers
URN: urn:nbn:se:hv:diva-7905DOI: 10.1109/CDC.2004.1429456OAI: oai:DiVA.org:hv-7905DiVA, id: diva2:845949
Conference
Decision and Control, 2004. CDC. 43rd IEEE Conference on
2015-08-132015-08-132015-08-13Bibliographically approved