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.

scholarly journals Suboptimal Control Using Model Order Reduction

2014 ◽  
Vol 2014 ◽  
pp. 1-5 ◽  
Author(s):  
Avadh Pati ◽  
Awadhesh Kumar ◽  
Dinesh Chandra
Keyword(s):  
Model Order Reduction ◽  
Order Reduction ◽  
Higher Order ◽  
Reduced Order Model ◽  
Suboptimal Control ◽  
Order Model ◽  
Model Order ◽  
Markov Parameters ◽  
Reduced Order ◽  
Partial Feedback

A Padé approximation based technique for designing a suboptimal controller is presented. The technique uses matching of both time moments and Markov parameters for model order reduction. In this method, the suboptimal controller is first derived for reduced order model and then implemented for higher order plant by partial feedback of measurable states.

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.

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.

scholarly journals Order Reduction based on Coulomb’s and Franklin’s laws Algorithm

2021 ◽  
Author(s):  
Ram Kumar ◽  
Afzal Sikander
Keyword(s):  
Large Scale ◽  
Linear Time ◽  
Order Reduction ◽  
Absolute Error ◽  
Search Space ◽  
Engineering Problem ◽  
Reduced Order Model ◽  
Order Model ◽  
Reduced Order ◽  
Linear Time Invariant

Abstract The Coulomb and Franklin laws (CFL) algorithm is used to construct a lower order model of higher-order continuous time linear time-invariant (LTI) systems in this study. CFL is quite easy to implement in obtaining reduced order model of large scale system in control engineering problem as it employs the combined effect of Coulomb’s and Franklin’s laws to find the best values in search space. The unknown coefficients are obtained using the CFLA methodology, which minimises the integral square error (ISE) between the original and proposed ROMs. To achieve the reduced order model, five practical systems of different orders are considered. Finally, multiple performance indicators such as the ISE, integral of absolute error (IAE), and integral of time multiplied by absolute error were calculated to determine the efficacy of the proposed methodology. The simulation results were compared to previously published well-known research.

Order Reduction of Parametrically Excited Nonlinear Systems Subjected to External Periodic Excitations

2009 ◽  
Author(s):  
Sangram Redkar ◽  
S. C. Sinha
Keyword(s):  
Nonlinear Systems ◽  
Fundamental Solution ◽  
Invariant Manifold ◽  
Large Scale ◽  
Order Reduction ◽  
Reduced Order Model ◽  
Reduced Order Models ◽  
Order Model ◽  
Reduced Order ◽  
And Control

In this work, some techniques for order reduction of nonlinear systems with periodic coefficients subjected to external periodic excitations are presented. The periodicity of the linear terms is assumed to be non-commensurate with the periodicity of forcing vector. The dynamical equations of motion are transformed using the Lyapunov-Floquet (L-F) transformation such that the linear parts of the resulting equations become time-invariant while the forcing and/or nonlinearity takes the form of quasiperiodic functions. The techniques proposed here; construct a reduced order equivalent system by expressing the non-dominant states as time-varying functions of the dominant (master) states. This reduced order model preserves stability properties and is easier to analyze, simulate and control since it consists of relatively small number of states in comparison with the large scale system. Specifically, two methods are outlined to obtain the reduced order model. First approach is a straightforward application of linear method similar to the ‘Guyan reduction’, the second novel technique proposed here, utilizes the concept of ‘invariant manifolds’ for the forced problem to construct the fundamental solution. Order reduction approach based on invariant manifold technique yields unique ‘reducibility conditions’. If these ‘reducibility conditions’ are satisfied only then an accurate order reduction via ‘invariant manifold’ is possible. This approach not only yields accurate reduced order models using the fundamental solution but also explains the consequences of various ‘primary’ and ‘secondary resonances’ present in the system. One can also recover ‘resonance conditions’ associated with the fundamental solution which could be obtained via perturbation techniques by assuming weak parametric excitation. This technique is capable of handing systems with strong parametric excitations subjected to periodic and quasi-periodic forcing. These methodologies are applied to a typical problem and results for large-scale and reduced order models are compared. It is anticipated that these techniques will provide a useful tool in the analysis and control system design of large-scale parametrically excited nonlinear systems subjected to external periodic excitations.

Optimal Tracking Control of Multi-Zone Indoor Environmental Spaces

1995 ◽  
Vol 117 (3) ◽  
pp. 292-303 ◽  
Author(s):  
M. Zaheer-uddin ◽  
R. V. Patel
Keyword(s):  
Optimal Control ◽  
Tracking Control ◽  
Control Law ◽  
Closed Loop System ◽  
Order Model ◽  
Fast Subsystem ◽  
Reduced Order ◽  
Optimal Tracking ◽  
Optimal Tracking Control ◽  
Slow Subsystem

Optimal control of indoor environmental spaces is explored. A physical model of the system consisting of a heating system, a distribution system and an environmental zone is considered and a seventh order bilinear system model is developed. From the physical characteristics and open-loop response of the system, it is shown that the overall system consists of a fast subsystem and a slow subsystem. By including the effects of the slow subsystem in the fast subsystem, a reduced order model is developed. An optimal control law is designed based on the reduced order model and it is implemented on the full order nonlinear system. Both local and global linearization techniques are used to design optimal control laws. Results showing the disturbance rejection characteristics of the resulting closed-loop system are presented. The use of optimal tracking control to implement large changes in setpoints, in a prescribed manner, is also examined. A general model to describe environmental zones is proposed and its application to multi-zone spaces is illustrated. A multiple-input optimal tracking control law with output error integrators is designed. The resulting closed-loop system response to step-like disturbances is shown to be good.

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