Robust control design with real-parameter uncertainty and unmodeled dynamics

1990 ◽  
Vol 13 (6) ◽  
pp. 1117-1125 ◽  
Author(s):  
Hsi-Han Yeh ◽  
Siva S. Banda ◽  
Sharon A. Heise ◽  
Andrew C. Bartlett
Keyword(s):  
Robust Control ◽  
Parameter Uncertainty ◽  
Control Design ◽  
Real Parameter ◽  
Unmodeled Dynamics ◽  
Robust Control Design ◽  
Real Parameter Uncertainty

A New Robust Control Design for Linear Systems With Norm Bounded Time Varying Real Parameter Uncertainty

2010 ◽  
Author(s):  
Nagini Devarakonda ◽  
Rama K. Yedavalli
Keyword(s):  
Robust Control ◽  
Linear Systems ◽  
Parameter Uncertainty ◽  
Design Method ◽  
Control Design ◽  
Design Methods ◽  
Real Parameter ◽  
Time Varying ◽  
Robust Control Design ◽  
Real Parameter Uncertainty

In this paper, a new methodology for robust control design of linear systems with time varying real parameter uncertainty is presented. The distinctive feature of this method is that it specifically offers robustness guarantees to real parameter uncertainty thereby providing a much needed alternative design method compared to existing design methods such as H∞ and μ-synthesis methods which tend to be conservative when specialized to real parameter uncertainty. The proposed robust control design method is inspired by sign (qualitative) stability idea from ecology, leading to a specific structure in the desired closed loop system matrix involving pseudosymmetry. The design procedure is simple and straightforward without requiring intensive computation. The proposed design algorithm is illustrated with aerospace applications. This algorithm is quite promising with considerable scope for extensions and improvements, finally adding to the bank of available control design methods for linear state space systems.

Uncertainty Quantification for Robust Control Design of Smart Material Systems

2013 ◽  
Author(s):  
Jerry A. McMahan ◽  
Ralph C. Smith
Keyword(s):  
Robust Control ◽  
Uncertainty Quantification ◽  
Control Design ◽  
Smart Material ◽  
Unmodeled Dynamics ◽  
Worst Case ◽  
Control Authority ◽  
Robust Control Design ◽  
Smart Material Systems ◽  
Control Designs

The objective in robust control design is to provide mechanisms to achieve tracking or stabilization objectives in the presence of unmodeled dynamics. This is usually achieved by assuming worst case model discrepancies which can significantly degrade control authority if the uncertainty bounds are overly conservative. In this paper, we use uncertainty quantification techniques to construct densities for control outputs that can be used to derive optimal robust control designs. We illustrate the performance of these techniques in the context of systems with smart material actuators and sensors.

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