Browsing by Subject "Uncertain systems"
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Item Open Access Adaptive control allocation for constrained systems(Elsevier, 2020-06) Tohidi, Seyed Shahabaldin; Yıldız, Yıldıray; Kolmanovsky, I.This paper proposes an adaptive control allocation approach for uncertain over-actuated systems with actuator saturation. The proposed control allocation method does not require uncertainty estimation or persistency of excitation. Actuator constraints are respected by employing the projection algorithm. The stability analysis is provided for two different cases: when ideal adaptive parameters are inside and when they are outside of the projection boundary which is chosen consistently with the actuator saturation limits. Simulation results for the Aerodata Model in Research Environment (ADMIRE), which is used as an example of an over-actuated aircraft system with actuator saturation, demonstrate the effectiveness of the proposed method.Item Open Access Adaptive human pilot model for uncertain systems(IEEE, 2019-06) Tohidi, Shahab; Yıldız, YıldırayInspired by humans' ability to adapt to changing environments, this paper proposes an adaptive human model that mimics the crossover model despite input bandwidth deviations and plant uncertainties. The proposed human pilot model structure is based on the model reference adaptive control, and the adaptive laws are obtained using the Lyapunov-Krasovskii stability criteria applied to the overall closed loop system including the human pilot and the plant. The proposed model can be employed for human-in-the-Ioop stability and performance analyses with different controllers and plant types. A numerical example is used to demonstrate the effectiveness of the presented method.Item Open Access Attention-enabled memory for concurrent learning adaptive control(Institute of Electrical and Electronics Engineers, 2022-12-16) Habboush, Abdullah; Yıldız, YıldırayTransient tracking error dynamics are inevitable in any practical closed-loop control system. While numerous works are devoted to improving these dynamics, in this letter, we focus on taking advantage of it first, in the context of adaptive control. We propose a memory architecture that can make use of stored significant data about the transients of previously experienced anomalies to aid in obtaining a resilient system against uncertainties. The proposed architecture consists of 1) a memory containing data about a variety of uncertainties, 2) a short-term memory that aids in handling new uncertainties, and 3) an attention-based reading mechanism that enables the controller to retrieve only relevant data from the memory. The effectiveness of the architecture is validated through numerical simulations, and a rigorous Lyapunov stability analysis is provided.Item Open Access Control of uncertain sampled-data systems: An Adaptive posicast control approach(Institute of Electrical and Electronics Engineers Inc., 2017) Abidi K.; Yildiz, Y.; Annaswamy A.This technical note proposes a discrete-time adaptive controller for the control of sampled-data systems. The design is inspired from the Adaptive Posicast Controller (APC) which was designed for time-delay systems in continuous time. Due to the performance degradation caused by digital approximation of continuous laws, together with the problem of assuming time-delays as integer multiples of sampling intervals, the benefits of APC could not be fully realized. In this technical note, these approximations/assumptions are eliminated. In addition, a disturbance observer is incorporated into the controller design which minimizes the effect of disturbances on the system. Extension to the case of uncertain input time-delay is also presented. The proposed approach is verified in simulation studies. © 1963-2012 IEEE.Item Open Access A control theoretical adaptive human pilot model: theory and experimental validation(Institute of Electrical and Electronics Engineers Inc., 2022-04-19) Yildiz, Yildiray; Tohidi, S.SThis article proposes an adaptive human pilot model that is able to mimic the crossover model in the presence of uncertainties. The proposed structure is based on the model reference adaptive control, and the adaptive laws are obtained using the Lyapunov–Krasovskii stability criteria. The model can be employed for human-in-the-loop stability and performance analyses incorporating different types of controllers and plant types. For validation purposes, an experimental setup is employed to collect data and a statistical analysis is conducted to measure the predictive power of the pilot model.Item Open Access Design of a switched robust control scheme for drug delivery in blood pressure regulation(Elsevier B.V., 2016) Ahmed, S.; Özbay, HitayA control algorithm based on switching robust controllers is presented for a Linear Parameter Varying (LPV) time-delay system modeling automatic infusion of vasodilator drug to regulate postsurgical hypertension. The system is scheduled along a measurable signal trajectory. The prospective controllers are robustly designed at various operating points forming a finite set of robust controllers and then a hysteresis switching is performed between neighboring robust controllers for a larger operating range of the LPV system. The stability of the switching LPV system for the entire operating range is ensured by providing a sufficient condition in terms of bound on the scheduling signal variation using the concept of dwell time. Simulation results are provided to verify the performance of the designed control scheme. © 2016Item Open Access Enhancing human operator performance with long short-term memory networks in adaptively controlled systems(Institute of Electrical and Electronics Engineers, 2023-11-20) Uzun, M. Yusuf; İnanç, Emirhan; Yıldız, YıldırayThe focus of this letter is developing a Long Short-Term Memory (LSTM) network-based control framework that works in collaboration with the human operator to enhance the overall closed-loop system performance in adaptively controlled systems. The domain of investigation is chosen to be flight control, although the proposed approach can be generalized for other domains such as automotive control. In accordance with this choice, an adaptive human pilot model is used as the mathematical representation of the pilot during the technical development of the method. An LSTM network is designed in such a way that it predicts and compensates for the inadequacies of the human operator's decisions while they fly an aircraft that has an adaptive inner loop controller. The simulation results demonstrate that the tracking performance is improved, and the pilot workload is reduced.Item Open Access Inflation and inflation uncertainty in the G-7 countries(Elsevier BV, 2005) Berument, Hakan; Dincer, N. N.This study examines the relationship between inflation and inflation uncertainty in the G-7 countries for the period from 1957 to 2001. The causality between the inflation and inflation uncertainty is tested by using the Full Information Maximum Likelihood Method with extended lags. Our results suggest that inflation causes inflation uncertainty for all the G-7 countries, while inflation uncertainty causes inflation for Canada, France, Japan, the UK and the US. Furthermore, we find that in four countries (Canada, France, the UK and the US) increased uncertainty lowers inflation, and in only one country (Japan), increased uncertainty raises inflation. © 2004 Elsevier B.V. All rights reserved.Item Open Access A Note on Robust Stability Bounds(IEEE, 1989) Sezer, M. E.; Siuak, D. D.The purpose of this note is to comment on stability robustness bounds for linear systems with multiple uncertain parameters, which were obtained via Lyapunov functions. Simple examples are used to illustrate the effects of the choice of functions and corresponding majorizations. © 1989 IEEEItem Open Access On the design of AQM supporting TCP flows using robust control theory(IEEE, 2004) Quet, P-F.; Özbay, HitayRecently it has been shown that the active queue management schemes implemented in the routers of communication networks supporting transmission control protocol (TCP) flows can be modeled as a feedback control system. Based on a delay differential equations model of TCPs congestion-avoidance mode different control schemes have been proposed. Here a robust controller is designed based on the known techniques for H∞ control of systems with time delays.Item Open Access The robust spanning tree problem with interval data(Elsevier, 2001) Yaman, H.; Karaşan, O. E.; Pınar, M. Ç.Motivated by telecommunications applications we investigate the minimum spanning tree problem where edge costs are interval numbers. Since minimum spanning trees depend on the realization of the edge costs, we de5ne the robust spanning tree problem to hedge against the worst case contingency, and present a mixed integer programming formulation of the problem. We also de5ne some useful optimality concepts, and present characterizations for these entities leading to polynomial time recognition algorithms. These entities are then used to preprocess a given graph with interval data prior to the solution of the robust spanning tree problem. Computational results show that these preprocessing procedures are quite e9ective in reducing the time to compute a robust spanning tree.Item Open Access Towards improved adaptive control: human pilot models & memory-augmented architectures(Bilkent University, 2023-07) Habboush, AbdullahTo facilitate the implementation of adaptive control methods, this dissertation introduces novel solutions to key problems that hinder the employment of adaptive controllers in industrial applications. We present techniques that are inspired by humans’ versatility in the control loop, where we focus on understanding how humans adapt in the face of anomalies, and how they use their memory to better recover from them. Towards that end, we propose adaptive human pilot models suited for the prediction of human behavior in the loop with an adaptive controller. These models serve as valuable tools to test the interactions between human pilots and adaptive control systems in the simulation environment in order to ensure safe operation in the presence of an anomaly. Furthermore, the development of the models is carried out based on rigorous Lyapunov stability analyses, which can provide analytical insights into how to better design adaptive con-trollers for manned applications. Apart from their unfavorable interactions with human pilots, another issue that accounts for the scarce employment of adaptive controllers in piloted applications lies in their transient characteristics. While numerous works are devoted to improving the transients of adaptive control systems, in this dissertation, we focus on taking advantage of it first by providing adaptive controllers with human-like memory capabilities. We propose a memory architecture that can make use of stored data about the transients of previously experienced anomalies to aid in obtaining a resilient system against uncertainties. Thus, the proposed memory architecture enables adaptive controllers to rely on memory rather than exploration to better recover from familiar anomalies. The effectiveness of the architecture is validated through numerical simulations, and a rigorous Lyapunov stability analysis is provided.