Browsing by Author "Cifdaloz, Oguzhan"

Now showing 1 - 5 of 5

Citation - WoS: 1
Citation - Scopus: 2
Dynamical system parameter identification using deep recurrent cell networks: Which gated recurrent unit and when?
(Springer London Ltd, 2021) Akagunduz, Erdem; Cifdaloz, Oguzhan; 279762
In this paper, we investigate the parameter identification problem in dynamical systems through a deep learning approach. Focusing mainly on second-order, linear time-invariant dynamical systems, the topic of damping factor identification is studied. By utilizing a six-layer deep neural network with different recurrent cells, namely GRUs, LSTMs or BiLSTMs; and by feeding input/output sequence pairs captured from a dynamical system simulator, we search for an effective deep recurrent architecture in order to resolve the damping factor identification problem. Our study's results show that, although previously not utilized for this task in the literature, bidirectional gated recurrent cells (BiLSTMs) provide better parameter identification results when compared to unidirectional gated recurrent memory cells such as GRUs and LSTM. Thus, indicating that an input/output sequence pair of finite length, collected from a dynamical system and when observed anachronistically, may carry information in both time directions to predict a dynamical systems parameter.
Citation - WoS: 0
Citation - Scopus: 0
Improving the Performance of a Mems-Imu System Based on a False State-Space Model by Using a Fading Factor Adaptive Kalman Filter
(Sage Publications Ltd, 2024) Akbas, Eren Mehmet; Cifdaloz, Oguzhan; Ucuncu, Murat
In this study, we introduce a novel algorithm, the low error rate adaptive fading Kalman filter (LERAFKF), designed to predict system states in the presence of uncertainty in both the system matrix and the model. The purpose of developing the LERAFKF is to address challenges arising from measurement difficulties, system parameter uncertainties, and state-space model inaccuracies. Several studies have utilized the Kalman filter (KF) and extended Kalman filter (EKF) algorithms to handle uncertainties in system parameters, corrupted measurements with unknown covariances, and incorrectly defined system modeling. Our work distinguishes itself by proposing a new approach that achieves lower error and deviation rates by combining the current Kalman estimation algorithm and the fading factor adaptive filter. To achieve this goal, we transformed the KF into an adaptive KF by introducing a forgetting factor, and the algorithm was subsequently reconfigured to calculate an optimized forgetting factor. In this study, we conducted simulations and measurements using both linear and nonlinear systems. The linear system represents the motion of an object, and the simulation involved measurements from the inertial navigation system (INS) sensor, specifically the Pololu IMU01b three-axis inertial measurement unit (IMU) sensor. We employed the SDI33 system with 9 degrees of freedom (DoF) mounted on a three-axis rotary table for the nonlinear system. This system simulates a missile as a 4th-order nonlinear system. Our findings demonstrate that the proposed LERAFKF filter outperforms KF and EKF in estimating system states, particularly in measurement-related error scenarios. Mean square error analysis further confirmed that LERAFKF exhibited the lowest error values, showcasing superior performance over KF and EKF in linear and nonlinear systems.
Citation - WoS: 0
Citation - Scopus: 0
Line-of-sight rate construction for a roll-pitch gimbal via a virtual pitch-yaw gimbal
(Tubitak Scientific & Technological Research Council Turkey, 2021) Cifdaloz, Oguzhan; 279762
In this paper, a method to construct the line of sight rate of a target with a roll-pitch gimbal and tracker is described. Construction of line-of-sight rate is performed via utilizing a virtual pitch-yaw gimbal. Kinematics of both the roll-pitch and pitch-yaw gimbals are described. A dynamical model for the roll-pitch gimbal is developed, and a nested control structure is designed to control the angular rates and line of sight angles. A kinematic model of the tracker is developed and a tracker controller is designed to keep the target in the field of view. Conversion equations between roll-pitch and pitch-yaw gimbal configurations are provided. Finally, constructed line of sight rates are compared to true line of sight rates via simulations. Obtained results indicate that the constructed line of sight rates pertaining to a target satisfactorily converge to the actual line of sight rates.
Citation - WoS: 0
Citation - Scopus: 0
Management of Open-Access Renewable Resources with Depensation Dynamics: Control Systems Perspective
(Ieee, 2021) Cifdaloz, Oguzhan; 279762
Renewable resources are being over exploited at an increasing rate. Institutions/governments are compelled to devise effective policies and strategies to sustainably manage renewable resources under social, ecological and environmental pressures that stem from increasing demand, model uncertainties, disturbances, and measurement errors. Open-access policies to harvest renewable resources are still widely used around the world. They are mildly regulated by implementing landing quotas, defining harvesting seasons, and/or constraining the technology used for harvesting. In many parts of the world, including the regions that are highly developed, open-access fisheries a refailing. In this paper, management of an open-access renewable resource (fishery) with depensation dynamics is formulated as a control systems problem and a strategy to sustainably manage the renewable resource is proposed. First, dynamics of an unregulated open-access fishery is described and its vulnerabilities are stated. Then, an easy-to-implement regulation strategy based on classical control systems ideas is proposed and its robustness characteristics are provided. The management policy (control law) is implemented via manipulating economic variables, i.e. by adjusting the (opportunity) cost of harvesting. An agent-based model is used to model the resource exploiters (i.e. fishermen). It is shown that a classical control law can be used to effectively manage an open access fishery subject to sampling effects.
Citation - WoS: 1
Citation - Scopus: 1
Sustainable Management of a Renewable Fishery Resource with Depensation Dynamics from a Control Systems Perspective
(Gazi Univ, 2022) Cifdaloz, Oguzhan
Human societies are exploiting natural renewable sources such as fisheries, forests, groundwater basins, rivers, and soil at an increasing intensity. Around the world, these resources are being managed by various institutions or governments. One of the challenges faced by institutions is to develop strategies and policies to effectively manage these renewable resources under social and ecological uncertainties, disturbances, policy implementation difficulties, and measurement errors. In this paper, a fishery is considered as an example and the problem of managing a fishery is approached from a control systems perspective. The justification behind this approach is due to the observation that the problem of managing a renewable resource can be posed as a control systems problem and that the discipline of control systems possesses tools and methods to deal with model uncertainties, external disturbances, measurement errors and implementation issues. For the fishery, a depensation type population dynamics model is considered. Depensatory models are used in social/ecological systems in order to model dynamics of certain species of fish populations. An optimal control strategy based on Pontryagin's Maximum Principle is derived and its sustainability and robustness properties with respect to parametric uncertainties, measurement errors and disturbances are examined. Finally, a sub-optimal but more robust control strategy is proposed and its robustness properties are provided. The main objective of the paper is to show that a control systems engineering approach can be applied to a social-ecological problem and it can provide easy to implement management strategies, insight, and guidance into the management of renewable resources.