Show/Hide Menu
Hide/Show Apps
Logout
Türkçe
Türkçe
Search
Search
Login
Login
OpenMETU
OpenMETU
About
About
Open Science Policy
Open Science Policy
Open Access Guideline
Open Access Guideline
Postgraduate Thesis Guideline
Postgraduate Thesis Guideline
Communities & Collections
Communities & Collections
Help
Help
Frequently Asked Questions
Frequently Asked Questions
Guides
Guides
Thesis submission
Thesis submission
MS without thesis term project submission
MS without thesis term project submission
Publication submission with DOI
Publication submission with DOI
Publication submission
Publication submission
Supporting Information
Supporting Information
General Information
General Information
Copyright, Embargo and License
Copyright, Embargo and License
Contact us
Contact us
Constrained discrete-time optimal control of uncertain systems with adaptive Lyapunov redesign
Date
2021-01-01
Author
ALTINTAS, Oguz Han
Turgut, Ali Emre
Metadata
Show full item record
This work is licensed under a
Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License
.
Item Usage Stats
155
views
0
downloads
Cite This
All rights reserved.In this paper, the conventional estimation-based receding horizon control paradigm is enhanced by using functional approximation, the adaptive modifications on state estimation and convex projection notion from optimization theory. The mathematical formalism of parameter adaptation and uncertainty estimation procedure are based on the redesign of optimal state estimation in discrete-time. By using Lyapunov stability theory, it is shown that the online approximation of uncertainties acting on both physical system and state estimator can be obtained. Moreover, the convergence criteria for online parameter adaptation with fully matched and partially matched cases are presented and shown. In addition, it is shown that the uniform boundedness of tracking and adaptation errors can be maintained by projection-based parameter update laws in discrete-time with adequate sampling times. Finally, the proposed method is implemented to quadrotor case study and the gradual recovery of feasible sub-optimal solutions are presented despite actuation, modeling and measurement errors. By using the proposed method, the uncertainty estimates are successfully converged to their prescribed values and both state prediction and command tracking of model predictive controller are corrected within the convergence bounds.
URI
https://www.scopus.com/inward/record.uri?partnerID=HzOxMe3b&scp=85108365685&origin=inward
https://hdl.handle.net/11511/91278
Journal
Turkish Journal of Electrical Engineering and Computer Sciences
DOI
https://doi.org/10.3906/elk-2011-8
Collections
Department of Mechanical Engineering, Article
Suggestions
OpenMETU
Core
Global exponential stability of neural networks with non-smooth and impact activations
Akhmet, Marat (2012-10-01)
In this paper, we consider a model of impulsive recurrent neural networks with piecewise constant argument. The dynamics are presented by differential equations with discontinuities such as impulses at fixed moments and piecewise constant argument of generalized type. Sufficient conditions ensuring the existence, uniqueness and global exponential stability of the equilibrium point are obtained. By employing Green's function we derive new result of existence of the periodic solution. The global exponential s...
STABILITY OF CONTROL FORCES IN REDUNDANT MULTIBODY SYSTEMS
IDER, SK (1996-01-03)
In this paper inverse dynamics of redundant multibody systems using a minimum number of control forces is formulated. It is shown that the control forces and the task accelerations may become noncausal at certain configurations, yielding the dynamical equation set of the system to be singular. For a given set of tasks, each different set of actuators leads to a different system motion and also to different singular configurations. To avoid the singularities in the numerical solution, the dynamical equations...
Stability criteria for linear Hamiltonian systems under impulsive perturbations
Kayar, Z.; Zafer, Ağacık (2014-03-01)
Stability criteria are given for planar linear periodic Hamiltonian systems with impulse effect by making use of a Lyapunov type inequality. A disconjugacy criterion is also established. The results improve the related ones in the literature for such systems.
Continuous-time nonlinear estimation filters using UKF-aided gaussian sum representations
Gökçe, Murat; Kuzuoğlu, Mustafa; Department of Electrical and Electronics Engineering (2014)
A nonlinear filtering method is developed for continuous-time nonlinear systems with observations/measurements carried out in discrete-time by means of UKFaided Gaussian sum representations. The time evolution of the probability density function (pdf) of the state variables (or the a priori pdf) is approximated by solving the Fokker-Planck equation numerically using Euler’s method. At every Euler step, the values of the a priori pdf are evaluated at deterministic sample points. These values are used with Ga...
Automated inverse analysis of a deep excavation in Ankara clay using finite element analysis
Engin, Tugce Aktas; Çokça, Erdal (2021-10-01)
The objective of this study is to find out the constant that shows a linear relationship between the deformation modulus parameter of Ankara clay and SPT N-60 values by using Plaxis 2D software. During analyses, three constitutive models are used, those are Mohr-Coulomb (MC), hardening soil model (HS), and hardening soil model with small strain stiffness (HSsmall). For that purpose, reverse analysis of a 25.0-m deep excavation was done by comparing results with displacements taken from inclinometer measurem...
Citation Formats
IEEE
ACM
APA
CHICAGO
MLA
BibTeX
O. H. ALTINTAS and A. E. Turgut, “Constrained discrete-time optimal control of uncertain systems with adaptive Lyapunov redesign,”
Turkish Journal of Electrical Engineering and Computer Sciences
, pp. 1836–1851, 2021, Accessed: 00, 2021. [Online]. Available: https://www.scopus.com/inward/record.uri?partnerID=HzOxMe3b&scp=85108365685&origin=inward.