Proportional-Integral-Observer With Adaptive High-Gain Design Using Funnel Adjustment Concept

2017 ◽  
Author(s):  
Fateme Bakhshande ◽  
Dirk Söffker
Keyword(s):  
Feedback Linearization ◽  
Dynamical Behavior ◽  
High Gain ◽  
Present Contribution ◽  
Input Estimation ◽  
Proportional Integral ◽  
Spring System ◽  
Unknown Input Estimation ◽  
Mass Spring ◽  
Funnel Control

This paper focuses on a novel gain design approach of Proportional-Integral-Observer (known as PI-Observer) for unknown input estimation such as disturbances. Whereas estimation of the fast dynamical behavior requires large observer gains, the effect of measurement noise is not negligible. To adjust the PIO gain adaptively, in this contribution the idea of funnel control is taken into consideration. The advantage of the proposed approach compared to previously published PIO gain design is the self adjustment of the observer gains according to the actual estimation situation. To improve the control performance and robustness, in the present contribution the proposed approach is combined with exact feedback linearization (EFL) method. The effectiveness of the proposed approach is verified by simulation results of a MIMO mass-spring system.

Sensor Fault and Unknown Input Estimation Based on Proportional Integral Observer Applied to LPV Descriptor Systems.

2012 ◽  
Vol 45 (20) ◽  
pp. 1059-1064 ◽  
Author(s):  
A. Aguilera-González ◽  
D. Theilliol ◽  
M. Adam-Medina ◽  
C.M. Astorga-Zaragoza ◽  
M. Rodrigues
Keyword(s):  
Descriptor Systems ◽  
Unknown Input ◽  
Sensor Fault ◽  
Input Estimation ◽  
Proportional Integral ◽  
Unknown Input Estimation

Contact Force Estimation for an Elastic Beam Using Optimal High-Gain Disturbance Observer

2010 ◽  
Author(s):  
Yan Liu ◽  
Dirk So¨ffker
Keyword(s):  
Contact Force ◽  
Disturbance Observer ◽  
Elastic Beam ◽  
High Gain ◽  
Contact Forces ◽  
Force Estimation ◽  
Input Estimation ◽  
System States ◽  
Unknown Input Estimation ◽  
Noisy Measurements

This contribution presents a contact force estimation approach based on an optimal high-gain disturbance observer for an elastic beam using noisy measurements. The reconstruction of contact forces as an example for unknown input estimation represents a class of typical mechanical engineering problems related to the estimation of unknown effects for disturbance rejection or accommodation or fault diagnosis and isolation. The high-gain disturbance observers applied here is able to estimate estimate unknown external inputs together with system states. But choosing observer gains is a difficult task because of the influence of measurement noise. The important advantage of the proposed approach in comparison with classical high-gain disturbance observer is the self adjustment of the observer gains according to the actual estimation situation. Estimation results based on real measurements from known high-gain disturbance observer and the proposed optimal one are compared. It can be shown that the proposed algorithm allows optimized disturbance observer gains calculation, being able to be situatively adapted.

A Robust Control Design Approach Combining Exact Linearization and High-Gain PI-Observer

2007 ◽  
Author(s):  
Yan Liu ◽  
Dirk So¨ffker
Keyword(s):  
Feedback Linearization ◽  
Control Method ◽  
High Gain ◽  
Observer Design ◽  
Input State ◽  
Exact Linearization ◽  
Practical Applications ◽  
Robust Control Design ◽  
Nonlinear Control Method ◽  
Feedback Linearization Approach

This paper introduces a robust nonlinear control method combining classical feedback linearization and a high-gain PI-Observer (Proportional-Integral Observer) approach that can be applied to control a nonlinear single-input system with uncertainties or unknown effects. It is known that the lack of robustness of the feedback linearization approach limits its practical applications. The presented approach improves the robustness properties and extends the application area of the feedback linearization control. The approach is developed analytically and fully illustrated. An example which uses input-state linearization and PI-Observer design is given to illustrate the idea and to demonstrate the advantages.

Graphene-Based Resonant Sensors for Detection of Ultra-Fine Nanoparticles: Molecular Dynamics and Nonlocal Elasticity Investigations

NANO ◽  
2015 ◽  
Vol 10 (02) ◽  
pp. 1550024 ◽  
Author(s):  
S. Kamal Jalali ◽  
M. Hassan Naei ◽  
Nicola Maria Pugno
Keyword(s):  
Molecular Dynamics ◽  
Nonlocal Elasticity ◽  
Md Simulations ◽  
Small Scale ◽  
Frequency Shifts ◽  
Resonant Sensors ◽  
Embedded Atom ◽  
Metal Metal ◽  
Spring System ◽  
Mass Spring

Application of single layered graphene sheets (SLGSs) as resonant sensors in detection of ultra-fine nanoparticles (NPs) is investigated via molecular dynamics (MD) and nonlocal elasticity approaches. To take into consideration the effect of geometric nonlinearity, nonlocality and atomic interactions between SLGSs and NPs, a nonlinear nonlocal plate model carrying an attached mass-spring system is introduced and a combination of pseudo-spectral (PS) and integral quadrature (IQ) methods is proposed to numerically determine the frequency shifts caused by the attached metal NPs. In MD simulations, interactions between carbon–carbon, metal–metal and metal–carbon atoms are described by adaptive intermolecular reactive empirical bond order (AIREBO) potential, embedded atom method (EAM), and Lennard–Jones (L–J) potential, respectively. Nonlocal small-scale parameter is calibrated by matching frequency shifts obtained by nonlocal and MD simulation approaches with same vibration amplitude. The influence of nonlinearity, nonlocality and distribution of attached NPs on frequency shifts and sensitivity of the SLGS sensors are discussed in detail.

scholarly journals Reduced Mass-Weighted Proper Decomposition for Modal Analysis

2011 ◽  
Vol 133 (2) ◽  
Author(s):  
Venkata K. Yadalam ◽  
B. F. Feeny
Keyword(s):  
Modal Analysis ◽  
Mass Distribution ◽  
Mass Matrix ◽  
Linear Interpolation ◽  
Modal Identification ◽  
Distributed Parameter ◽  
Arbitrary Mass ◽  
Spring System ◽  
Mass Spring ◽  
Proper Orthogonal

A method of modal analysis by a mass-weighted proper orthogonal decomposition for multi-degree-of-freedom and distributed-parameter systems of arbitrary mass distribution is outlined. The method involves reduced-order modeling of the system mass distribution so that the discretized mass matrix dimension matches the number of sensed quantities, and hence the dimension of the response ensemble and correlation matrix. In this case, the linear interpolation of unsensed displacements is used to reduce the size of the mass matrix. The idea is applied to the modal identification of a mass-spring system and an exponential rod.

scholarly journals Numerical Method of Fabric Dynamics Using Front Tracking and Spring Model

2013 ◽  
Vol 14 (5) ◽  
pp. 1228-1251 ◽  
Author(s):  
Yan Li ◽  
I-Liang Chern ◽  
Joung-Dong Kim ◽  
Xiaolin Li
Keyword(s):  
Upper Bound ◽  
Mesh Size ◽  
Front Tracking ◽  
Time Step ◽  
Mass System ◽  
Ode System ◽  
Spring System ◽  
Fabric Surface ◽  
Mass Spring ◽  
Eigen Frequency

AbstractWe use front tracking data structures and functions to model the dynamic evolution of fabric surface. We represent the fabric surface by a triangulated mesh with preset equilibrium side length. The stretching and wrinkling of the surface are modeled by the mass-spring system. The external driving force is added to the fabric motion through the “Impulse method” which computes the velocity of the point mass by superposition of momentum. The mass-spring system is a nonlinear ODE system. Added by the numerical and computational analysis, we show that the spring system has an upper bound of the eigen frequency. We analyzed the system by considering two spring models and we proved in one case that all eigenvalues are imaginary and there exists an upper bound for the eigen-frequency This upper bound plays an important role in determining the numerical stability and accuracy of the ODE system. Based on this analysis, we analyzed the numerical accuracy and stability of the nonlinear spring mass system for fabric surface and its tangential and normal motion. We used the fourth order Runge-Kutta method to solve the ODE system and showed that the time step is linearly dependent on the mesh size for the system.

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