Uncertainty model identification for H/sub ∞/ robust control

2002 ◽  
Author(s):  
M. Taragna
Keyword(s):  
Robust Control ◽  
Model Identification ◽  
Uncertainty Model

Robust control from data via uncertainty model sets identification

2004 ◽  
Vol 14 (11) ◽  
pp. 945-957 ◽  
Author(s):  
S. Malan ◽  
M. Milanese ◽  
D. Regruto ◽  
M. Taragna
Keyword(s):  
Robust Control ◽  
Model Sets ◽  
Uncertainty Model

SISO Model Identification of a Micro Air Vehicle for Robust Control Design

2015 ◽  
Vol 220-221 ◽  
pp. 470-478
Author(s):  
Arkadiusz Mystkowski
Keyword(s):  
Robust Control ◽  
Delta Wing ◽  
Angular Rate ◽  
Model Identification ◽  
Control Design ◽  
Real Data ◽  
Micro Air Vehicle ◽  
Lateral Direction ◽  
Air Vehicle ◽  
Robust Control Design

This paper describes a model identification method of a Micro Air Vehicle (MAV) for a further purpose of the robust control design. The identification procedure is based on logged real data collected from flight tests. For the identification purpose, both frequency and time-domain techniques are used. Identification results are presented for the lateral direction dynamics using the elevon (aileron deflection) as input and the roll angular rate as output. The MAV is a single-delta wing of the 0.84 m wingspan and 1.2 kg of total mass (ready to flight). The main goal of the system identification process is to achieve the best possible fit between the raw data and a dynamic model which is called a nominal model.

scholarly journals Experimental Robust Control of Structural Acoustic Radiation

1999 ◽  
Vol 121 (4) ◽  
pp. 433-439 ◽  
Author(s):  
D. E. Cox ◽  
G. P. Gibbs ◽  
R. L. Clark ◽  
J. S. Vipperman
Keyword(s):  
Robust Control ◽  
Ad Hoc ◽  
Acoustic Radiation ◽  
Experimental Results ◽  
Model Errors ◽  
Control Effort ◽  
Acoustic Control ◽  
Uncertainty Model ◽  
Bounding Model ◽  
Control Designs

This work addresses the design and application of robust controllers for structural acoustic control. Both simulation and experimental results are presented. H∞ and μ-synthesis design methods were used to design feedback controllers which minimize power radiated from a panel while avoiding instability due to unmodeled dynamics. Specifically, high-order structural modes which couple strongly to the actuator-sensor path were poorly modeled. This model error was analytically bounded with an uncertainty model which allowed controllers to be designed without artificial limits on control effort. It is found that robust control methods provide the control designer with physically meaningful parameters with which to tune control designs and can be very useful in determining limits of performance. However, experimental results also showed poor robustness properties for control designs with ad-hoc uncertainty models. The importance of quantifying and bounding model errors is discussed.

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