Command governor-based adaptive control for dynamical systems with matched and unmatched uncertainties

Date

2018-08-01

Author

Yayla, Metehan
Kutay, Ali Türker

Metadata

Show full item record

This work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.

Item Usage Stats

221
views

0
downloads

In this paper, we propose a command governor-based adaptive control architecture for stabilizing uncertain dynamical systems with not only matched but also unmatched uncertainties and achieving the desired command following performance of a user-defined subset of the accessible states. In our proposed solution, online least-squares solutions for the matched and unmatched parameters are obtained through integration method and they are employed in the adaptive control framework. Specifically, the matched uncertainty is identified and its effect upon the system behavior is entirely attenuated. Moreover, using the unmatched uncertainty approximation obtained through radial basis function neural networks, the command governor signal is designed to achieve the desired command following performance of the user-defined subset of the accessible states. With this command governor-based model reference adaptive control architecture, the tracking error of the selected states can be made arbitrarily small by judiciously tuning the design parameters. In addition to the analysis of the closed-loop system stability using methods from the Lyapunov theory, our findings are also illustrated through numerical examples.

Subject Keywords

Adaptive control, Command governor, Matched and unmatched uncertainties, Neural networks, Stability and command following

URI

https://hdl.handle.net/11511/39933

Journal

INTERNATIONAL JOURNAL OF ADAPTIVE CONTROL AND SIGNAL PROCESSING

DOI

https://doi.org/10.1002/acs.2891

Collections

Department of Aerospace Engineering, Article

Suggestions

OpenMETU
Core

Information Recovery-based Model Reference Adaptive Control for Fast Adaptation and Improved Transients with Aerospace Applications Yayla, Metehan; Kutay, Ali Türker; Department of Aerospace Engineering (2023-2-13) This thesis proposes improvements to Filter-based Model Reference Adaptive Control (MRAC) architectures for uncertain dynamical systems. Standard MRAC cannot guarantee closed-loop stability in the presence of bounded perturbations without restrictive persistent excitation of system signals. Robust modifications have been introduced to increase the robustness of standard MRAC and/or guarantee stability without persistent excitation, but little improvement has been achieved in guaranteed transient response. R...
Output-feedback control of linear time-varying and nonlinear systems using the forward propagating Riccati equation Prach, Anna; Tekinalp, Ozan; Bernstein, Dennis S. (2018-04-01) For output-feedback control of linear time-varying (LTV) and nonlinear systems, this paper focuses on control based on the forward propagating Riccati equation (FPRE). FPRE control uses dual difference (or differential) Riccati equations that are solved forward in time. Unlike the standard regulator Riccati equation, which propagates backward in time, forward propagation facilitates output-feedback control of both LTV and nonlinear systems expressed in terms of a state-dependent coefficient (SDC). To invest...
Camera controlled pick and placeapplication with Puma 760 arm Durusu, Deniz; Ersak, Aydın; Department of Electrical and Electronics Engineering (2005) This thesis analyzes the kinematical structure of Puma 760 arm and introduces the implementation of image based pick and place application by taking care of the obstacles in the environment. Forward and inverse kinematical solutions of PUMA 760 are carried out. A control software has been developed to calculate both the forward and inverse kinematics solution of this manipulator. The control program enables user to perform both offline programming and real time realization by transmitting the VAL commands (...
State-dependent impulsive Cohen-Grossberg neural networks with time-varying delays Sayli, Mustafa; YILMAZ, ENES (2016-01-01) In this paper, a more general class of state-dependent impulsive Cohen-Grossberg neural networks having variable coefficients with time-varying delays is addressed. By means of B-equivalence method, we reduce this state-dependent impulsive neural networks system to a fix time impulsive neural networks system. Sufficient conditions for existence and global exponential stability of the equilibrium point as well as periodic solution are obtained by employing a suitable Lyapunov function, the Banach fixed point...
On optimal resource allocation in phased array radar systems Ircı, Ayhan; Saranlı, Afşar; Department of Electrical and Electronics Engineering (2006) In this thesis, the problem of optimal resource allocation in real-time systems is studied. A recently proposed resource allocation approach called Q-RAM (Quality of Service based Resource Allocation Model) is investigated in detail. The goal of the Q-RAM based approaches is to minimize the execution speed in real-time systems while meeting resource constraints and maximizing total utility. Phased array radar system is an example of a system in which multiple tasks contend for multiple resources in order to...

Citation Formats

M. Yayla and A. T. Kutay, “Command governor-based adaptive control for dynamical systems with matched and unmatched uncertainties,” INTERNATIONAL JOURNAL OF ADAPTIVE CONTROL AND SIGNAL PROCESSING, pp. 1124–1144, 2018, Accessed: 00, 2020. [Online]. Available: https://hdl.handle.net/11511/39933.