scholarly journals Interpolation-Based Modeling Methodology for Efficient Aeroelastic Control of a Folding Wing

2021 ◽  
Vol 2021 ◽  
pp. 1-20
Author(s):  
Chengyu Yue ◽  
Yonghui Zhao
Keyword(s):  
Linear Time ◽  
Rational Functions ◽  
Control Synthesis ◽  
Special Treatment ◽  
Aeroelastic System ◽  
Modeling And Control ◽  
Linear Time Invariant ◽  
Modeling Methodology ◽  
Folding Wing ◽  
Parameter Varying

The aeroelastic model of a folding wing varies with different configurations, so it actually represents a parameter-varying system. Firstly, a new approach based on interpolation of local models is proposed to generate the linear parameter-varying model of a folding wing. This model is capable of predicting the aeroelastic responses during the slow morphing process and is suitable for subsequent control synthesis. The underlying inconsistencies among local linear time-invariant (LTI) models are solved through the modal matching of structural modes and the special treatment of the rational functions in aerodynamic models. Once the local LTI models are represented in a coherent state-space form, the aeroservoelastic (ASE) model at any operating point can be immediately generated by the matrix interpolation technique. Next, based on the present ASE model, the design of a parameterized controller for suppressing the gust-induced vibration is studied. The receptance method is applied to derive fixed point controllers, and the effective independence method is adopted and modified for optimal sensor placement in variable configurations, which can avoid solving ill-conditioned feedback gains. Numerical simulation demonstrates the effectiveness of the proposed interpolation-based modeling approach, and the parameterized controller exhibits a good gust mitigation effect within a wide parameter-varying range. This paper provides an effective and practical solution for modeling and control of the parameterized aeroelastic system.

New Results on Linear Time Invariant and Parameter Varying Static Output Feedback

2008 ◽  
Vol 31 (5) ◽  
pp. 1230-1238 ◽  
Author(s):  
Ricardo S. Sanchez-Pena ◽  
Phalguna Kumar Rachinayani ◽  
Dario H. Baldelli
Keyword(s):  
Output Feedback ◽  
Linear Time ◽  
Static Output Feedback ◽  
Linear Time Invariant ◽  
Parameter Varying ◽  
Time Invariant ◽  
Static Output

Design of a Compliant Based Biomimetic Planar Locomotive Mechanism

2020 ◽  
Author(s):  
Dillon Loupe ◽  
Hanseul Kim ◽  
Ayse Tekes ◽  
Coskun Tekes ◽  
Amir Ali Amiri Moghadam
Keyword(s):  
Nonlinear Dynamics ◽  
Linear Time ◽  
High Mobility ◽  
Performance Bounds ◽  
Design Development ◽  
Modeling And Control ◽  
Linear Time Invariant ◽  
Time Domains ◽  
Linear Time Invariant Systems ◽  
And Control

Abstract This paper presents the design, development, modeling and control of a biomimetic multi degree of freedom compliant locomotive mechanism that can follow a prescribed trajectory. The research objective of this study is the design of a high mobility and flexible planar locomotive mechanism incorporating large deflecting compliant hinges. The actuation is realized using servo motors. Mechanism is consisted of five sliding carts, rail, 3D-printed supplementary pieces to house motors and pins. Carts are connected by monolithically designed two arm links joined by a large deflecting flexure. Four servo motors are mounted on the driven carts. Since sliding carts are identical, forward motion is achieved by changing the friction of carts through the connecting pins. Dynamical model is created in Matlab Simulink using Euler’s laws of motion principle, pseudo rigid body modeling (PRBM), vector closure-loop equations and kinematic constraints. To robustly control the position of the mechanism, first its nonlinear dynamics replaced with a family of linear time invariant systems which have parameter uncertainty. Then a robust controller is designed based on the Quantitative Feedback Theory (QFT) for the desired robust tracking and stability bounds. QFT is one of the most powerful robust control techniques which can take into account both phase and magnitude information of the system and enables the designer to minimize the cost of feedback by clearly observing the design constraints through robust performance bounds. Finally, the performance of the designed controller is validated though nonlinear simulations using the nonlinear dynamics of the mechanism. It has been shown that the mechanism can consistently track the desired inputs both in frequency and time domains.

scholarly journals Extending the Root-Locus Method to Fractional-Order Systems

2008 ◽  
Vol 2008 ◽  
pp. 1-13 ◽  
Author(s):  
Farshad Merrikh-Bayat ◽  
Mahdi Afshar
Keyword(s):  
Fractional Order ◽  
Transfer Functions ◽  
Linear Time ◽  
Rational Functions ◽  
Fractional Order Systems ◽  
Root Locus ◽  
Linear Time Invariant ◽  
Locus Method ◽  
Linear Time Invariant Systems ◽  
Time Invariant

The well-known root-locus method is developed for special subset of linear time-invariant systems known as fractional-order systems. Transfer functions of these systems are rational functions with polynomials of rational powers of the Laplace variables. Such systems are defined on a Riemann surface because of their multivalued nature. A set of rules for plotting the root loci on the first Riemann sheet is presented. The important features of the classical root-locus method such as asymptotes, roots condition on the real axis, and breakaway points are extended to fractional case. It is also shown that the proposed method can assess the closed-loop stability of fractional-order systems in the presence of a varying gain in the loop. Three illustrative examples are presented to confirm the effectiveness of the proposed algorithm.

Determination of Different Polytopic Models of the Prototypical Aeroelastic Wing Section by TP Model Transformation

2006 ◽  
Vol 10 (4) ◽  
pp. 486-493 ◽  
Author(s):  
Péter Baranyi ◽  
◽  
Zoltán Petres ◽  
Péter L. Várkonyi ◽  
Péter Korondi ◽  
...  
Keyword(s):  
Model Transformation ◽  
Linear Time ◽  
Convex Combination ◽  
Linear Matrix ◽  
Linear Parameter Varying ◽  
Linear Time Invariant ◽  
Wing Section ◽  
Parameter Varying ◽  
Time Invariant

The Tensor Product (TP) model transformation is a recently proposed technique for transforming given Linear Parameter Varying (LPV) models into polytopic model form, namely, to parameter varying convex combination of Linear Time Invariant (LTI) models. The main advantage of the TP model transformation is that the Linear Matrix Inequality (LMI) based control design frameworks can immediately be applied to the resulting polytopic models to yield controllers with tractable and guaranteed performance. The effectiveness of the LMI design depends on the type of the convex combination in the polytopic model. Therefore, the main objective of this paper is to study how the TP model transformation is capable of determining different types of convex hulls of the LTI models. The study is conducted trough the example of the prototypical aeroelastic wing section.

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