Gain scheduling using time-varying Kalman filter for a class of LPV systems
Date
2008
Authors
Cha, Sung-Han
Rotkowitz, Michael
Anderson, Brian
Journal Title
Journal ISSN
Volume Title
Publisher
Elsevier
Abstract
Current gain-scheduling approaches only assure stability when the underlying parameter varies sufficiently slowly, and hence stable closed-loop is not guaranteed for more general (i.e. faster) parameter variations. Shamma and Athans (1992) provides a solution to overcome this by computing Riccati Differential Equation (RDE) online for the current parameter value with the offline Algebraic Riccati Equation (ARE) solutions for every parameter value, which is computationally demanding. This paper achieves a very significant simplification, by showing how only a finite number of AREs need be used and the online RDE solutions can be computed by table look-up and matrix inversion. In simulations the method yields results indistinguishable from those achieved in Shamma and Athans (1992).
Description
Keywords
Keywords: Adaptive control; Algebraic Riccati equations; Closed-loop; Current gains; Current parameters; Finite number; Gain Scheduling; Linear parameter-varying systems; LPV systems; Matrix inversions; Nonlinear system control; Offline; Parameter values; Parameter Adaptive control; Linear parameter-varying systems; Nonlinear system control
Citation
Collections
Source
Proceedings of International Federation of Automatic Control World Congress (SYSID 2008)
Type
Conference paper