Subsystem identification of reduced-order model for an aeroservo-elastic closed-loop system

2016 ◽  
Author(s):  
Kai-Yew Lum ◽  
Kwok-Leung Lai
Keyword(s):  
Closed Loop ◽  
Loop System ◽  
Reduced Order Model ◽  
Closed Loop System ◽  
Order Model ◽  
Reduced Order

scholarly journals Boundary Conditions for Transient and Robust Performance of a Reduced-Order Model-Based State Feedback Controller with PI Observer

Energies ◽  
2021 ◽  
Vol 14 (10) ◽  
pp. 2881
Author(s):  
Nebiyeleul Daniel Amare ◽  
Doe Hun Kim ◽  
Sun Jick Yang ◽  
Young Ik Son
Keyword(s):  
State Feedback ◽  
Closed Loop ◽  
Loop System ◽  
Reduced Order Model ◽  
System Stability ◽  
Order System ◽  
Closed Loop System ◽  
Order Model ◽  
Reduced Order ◽  
Model Based

One common technique employed in control system design to minimize system model complexity is model order reduction. However, controllers designed by using a reduced-order model have the potential to cause the closed-loop system to become unstable when applied to the original full-order system. Additionally, system performance improvement techniques such as disturbance observers produce unpredictable outcomes when augmented with reduced-order model-based controllers. In particular, the closed-loop system stability is compromised when a large value of observer gain is employed. In this paper, a boundary condition for the controller and observer design parameters in which the closed-loop system stability is maintained is proposed for a reduced-order proportional-integral observer compensated reduced-order model-based controller. The boundary condition was obtained by performing the stability analysis of the closed-loop system using the root locus method and the Routh-Hurwitz criterion. Both the observer and the state feedback controller were designed using a reduced-order system model based on the singular perturbation theory. The result of the theoretical analysis is validated through computer simulations using a DC (direct current) motor position control problem.

Model Simplification and Stability Robustness With Elastic Flight Vehicles

1995 ◽  
Vol 117 (3) ◽  
pp. 336-342
Author(s):  
Brett Newman ◽  
David K. Schmidt
Keyword(s):  
Closed Loop ◽  
Order Reduction ◽  
Higher Order ◽  
Reduced Order Model ◽  
Control Law ◽  
Model Simplification ◽  
Closed Loop System ◽  
Order Model ◽  
Reduced Order ◽  
Stability Robustness

Quantitative criteria are presented for model simplification, or order reduction, such that the reduced order model may be used to synthesize and evaluate a control law, and the stability and stability robustness obtained using the reduced order model will be preserved when controlling the higher order system. The error introduced due to model simplification is treated as modeling uncertainty, and some of the results from multivariable robustness theory are brought to bear on the model simplification problem. Also, the importance of the control law itself, in meeting the modeling criteria, is underscored. A weighted balanced order reduction technique is shown to lead to results that meet the necessary criteria. The procedure is applied to an aeroelastic vehicle model, and the results are used for control law development. Critical robustness properties designed into the lower order closed-loop system are shown to be present in the higher order closed-loop system.

A Stabilization of Fixed Gain Controlled Infinite Dimensional Systems by Augmentation With Direct Adaptive Control

2017 ◽  
Author(s):  
Mark J. Balas ◽  
Susan A. Frost
Keyword(s):  
Closed Loop ◽  
Adaptive Controller ◽  
Open Loop ◽  
Reduced Order Model ◽  
Order Model ◽  
Reduced Order ◽  
Infinite Dimensional ◽  
Infinite Dimensional Systems ◽  
Transmission Zeros ◽  
Exponentially Stable

Linear infinite dimensional systems are described by a closed, densely defined linear operator that generates a continuous semigroup of bounded operators on a general Hilbert space of states and are controlled via a finite number of actuators and sensors. Many distributed applications are included in this formulation, such as large flexible aerospace structures, adaptive optics, diffusion reactions, smart electric power grids, and quantum information systems. We have developed the following stability result: an infinite dimensional linear system is Almost Strictly Dissipative (ASD) if and only if its high frequency gain CB is symmetric and positive definite and the open loop system is minimum phase, i.e. its transmission zeros are all exponentially stable. In this paper, we focus on infinite dimensional linear systems for which a fixed gain linear infinite or finite dimensional controller is already in place. It is usually true that fixed gain controllers are designed for particular applications but these controllers may not be able to stabilize the plant under all variations in the operating domain. Therefore we propose to augment this fixed gain controller with a relatively simple direct adaptive controller that will maintain stability of the full closed loop system over a much larger domain of operation. This can ensure that a flexible structure controller based on a reduced order model will still maintain closed-loop stability in the presence of unmodeled system dynamics. The augmentation approach is also valuable to reduce risk in loss of control situations. First we show that the transmission zeros of the augmented infinite dimensional system are the open loop plant transmission zeros and the eigenvalues (or poles) of the fixed gain controller. So when the open-loop plant transmission zeros are exponentially stable, the addition of any stable fixed gain controller does not alter the stability of the transmission zeros. Therefore the combined plant plus controller is ASD and the closed loop stability when the direct adaptive controller augments this combined system is retained. Consequently direct adaptive augmentation of controlled linear infinite dimensional systems can produce robust stabilization even when the fixed gain controller is based on approximation of the original system. These results are illustrated by application to a general infinite dimensional model described by nuclear operators with compact resolvent which are representative of distributed parameter models of mechanically flexible structures. with a reduced order model based controller and adaptive augmentation.

Closed-loop control of unsteadiness over a rounded backward-facing step

2012 ◽  
Vol 703 ◽  
pp. 326-362 ◽  
Author(s):  
Alexandre Barbagallo ◽  
Gregory Dergham ◽  
Denis Sipp ◽  
Peter J. Schmid ◽  
Jean-Christophe Robinet
Keyword(s):  
Closed Loop ◽  
Random Noise ◽  
Reduced Order Model ◽  
Estimation Accuracy ◽  
Closed Loop Control ◽  
Backward Facing Step ◽  
Order Model ◽  
Loop Control ◽  
Reduced Order ◽  
And Performance

AbstractThe two-dimensional, incompressible flow over a rounded backward-facing step at Reynolds number $\mathit{Re}= 600$ is characterized by a detachment of the flow close to the step followed by a recirculation zone. Even though the flow is globally stable, perturbations are amplified as they are convected along the shear layer, and the presence of upstream random noise renders the flow unsteady, leading to a broadband spectrum of excited frequencies. This paper is aimed at suppressing this unsteadiness using a controller that converts a shear-stress measurement taken from a wall-mounted sensor into a control law that is supplied to an actuator. A comprehensive study of various components of closed-loop control design – covering sensor placement, choice and influence of the cost functional, accuracy of the reduced-order model, compensator stability and performance – shows that successful control of this flow requires a judicious balance between estimation speed and estimation accuracy, and between stability limits and performance requirements. The inherent amplification behaviour of the flow can be reduced by an order of magnitude if the above-mentioned constraints are observed. In particular, to achieve superior controller performance, the estimation sensor should be placed upstream near the actuator to ensure sufficient estimation speed. Also, if high-performance compensators are sought, a very accurate reduced-order model is required, especially for the dynamics between the actuator and the estimation sensor; otherwise, very minute errors even at low energies and high frequencies may render the large-scale compensated linearized simulation unstable. Finally, coupling the linear compensator to nonlinear simulations shows a gradual deterioration in control performance as the amplitude of the noise increases.

Closed Loop Transient Response from the Open Loop Frequency Response

1978 ◽  
Vol 11 (8) ◽  
pp. 302-308 ◽  
Author(s):  
E.C. Hind
Keyword(s):  
Frequency Response ◽  
Transient Response ◽  
Feedback Loop ◽  
Closed Loop ◽  
Full Range ◽  
Open Loop ◽  
Loop System ◽  
Closed Loop System ◽  
Order Model ◽  
First Order

A method is shown for relating the closed loop transient response to the open loop frequency response, which is based on the use of the contour of constant closed loop phase angle, α = −90°. The method primarily yields a second order model of the closed loop system which covers the full range of relative damping (0 < ζ < +∞). A first order model is recommended when prescribed conditions apply. The method is simpler and yields better results than currently used methods. In all cases it is assumed that the negative feedback loop has a transfer function of unity and that the closed loop system is stable.

Semi-Active Control of Civil Structures With a Simultaneous Reduced-Order Modeling and a Tuning of the Control Law

2011 ◽  
Author(s):  
Kazuhiko Hiramoto ◽  
Taichi Matsuoka ◽  
Katsuaki Sunakoda
Keyword(s):  
Control Systems ◽  
Active Control ◽  
Closed Loop ◽  
Reduced Order Model ◽  
Control Law ◽  
Structural Damping ◽  
Order Model ◽  
Civil Structures ◽  
Reduced Order ◽  
The Stability

Various semi-active control methods have been proposed for vibration control of civil structures. In contrast to active vibration control systems, all semi-active control systems are essentially asymptotically stable because of the stability of the structural systems themselves (with structural damping) and the energy dissipating nature of the semi-active control law. In this study, by utilizing the above property on the stability of semi-active control systems, a reduced-order structural model and a semi-active control law are simultaneously obtained so that the performance of the resulting semi-active control system becomes good. Based on the above fact any semi-active control laws derived from some models stabilize all real-existing structural systems that have structural damping. It means that the difference of dynamic behaviors between the real structural system and the reduced-order mathematical model in the sense of the open-loop response is no longer an important issue. In other words, we do not have to consider the closed-loop stability, which is one of the most important constraints in active control, in the process of the reduced-order structural modeling and the semi-active control design. We can only focus on the control performance of the closed-loop system with the real structure with the (model-based) semi-active control law in obtaining the reduced-order model. The semi-active control law in the present study is based on the one step ahead prediction of the structural response. The Genetic Algorithm (GA) is adopted to obtain the reduced-order model and the semi-active control law based on the reduced order model.

Sign in / Sign up

Export Citation Format

Share Document