Information Recovery-based Model Reference Adaptive Control for Fast Adaptation and Improved Transients with Aerospace Applications

Yayla, Metehan
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. Recently, filter-based solutions have been introduced, among which CMRAC has gained a significant reputation due to its simplicity in application, superior adaptation performance to external disturbances, and improvements on transient performance. However, filter-based methods suffer from losing information during filtering, which can degrade adaptation performance, and assume the uncertainty lies in the span of the control input, which may not hold for many practical systems. This thesis proposes a method to recover information lost during filtering in filter-based adaptive controllers, extending it to cover systems with unknown control effectiveness, and introducing a command governor-based adaptive controller architecture to guarantee strict tracking performance in the presence of unmatched uncertainty. The proposed information recovery-based model reference adaptive controller (IR-MRAC) is illustrated with an energy-based longitudinal flight controller architecture, which successfully decouples velocity and altitude responses while benefiting from all the advantages of an energy-based controller. The proposed command governor-based adaptive controller is extended to the lateral flight control problem to achieve the desired tracking performance in the presence of both matched and unmatched uncertainties. Closed-loop stability analyses of all proposed methods are illustrated through rigorous Lyapunov's stability analysis, with numerical examples and software-in-the-loop simulations used to validate the proposed methods in a more realistic environment.


Command governor-based adaptive control for dynamical systems with matched and unmatched uncertainties
Yayla, Metehan; Kutay, Ali Türker (2018-08-01)
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 unce...
Applied supervisory control for a flexible manufacturing system
Moor, Thomas; Schmidt, Klaus Verner; Perk, Sebastian (2010-12-01)
This paper presents a case study in the design and implementation of a discrete event system (DES) of real-world complexity. Our DES plant is a flexible manufacturing system (FMS) laboratory model that consists of 29 interacting components and is controlled via 107 digital signals. Regarding controller design, we apply a hierarchical and decentralised synthesis method from earlier work in order to achieve nonblocking and safe closed-loop behaviour. Regarding implementation, we discuss how digital signals tr...
Representing temporal knowledge in connectionist expert systems
Alpaslan, Ferda Nur (1996-09-27)
This paper introduces a new temporal neural networks model which can be used in connectionist expert systems. Also, a Variation of backpropagation algorithm, called the temporal feedforward backpropagation algorithm is introduced as a method for training the neural network. The algorithm was tested using training examples extracted from a medical expert system. A series of experiments were carried out using the temporal model and the temporal backpropagation algorithm. The experiments indicated that the alg...
Electromagnetic modeling of split-ring resonators
Gurel, Levent; Unal, Alper; Ergül, Özgür Salih (2006-09-15)
In this paper, we report our efforts to model split-ring resonators (SRRs) and their large arrays accurately and efficiently in a sophisticated simulation environment based on recent advances in the computational electromagnetics. The resulting linear system obtained from the simultaneous discretization of the geometry and Maxwell's equations is solved iteratively with the multilevel fast multipole algorithm. As an example, we present an array of 125 SRRs showing a negative effective permeability about 92 GHz.
Adaptive decentralized control of interconnected systems
Sezer, ME; Altunel, H (2004-08-01)
This paper presents a decentralized adaptive stabilization scheme for a class of interconnected systems using high-gain adaptive controllers. The nominal subsystems are assumed to satisfy some mild conditions required by standard adaptive control schemes, and the interconnections certain structural conditions. The decentralized controllers are high-gain dynamic systems operating on local outputs to generate local control inputs. Both continuous-time and sampled-data controllers are considered. The idea behi...
Citation Formats
M. Yayla, “Information Recovery-based Model Reference Adaptive Control for Fast Adaptation and Improved Transients with Aerospace Applications,” Ph.D. - Doctoral Program, Middle East Technical University, 2023.