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Toplam kayıt 52, listelenen: 41-50
Learning Feedback Linearization Based Stable Robust Adaptive NARMA Controller Design for Rotary Inverted Pendulum
(ELECO 2019 - 11th International Conference on Electrical and Electronics Engineering, 2019)
This paper presents a Learning Feedback Linearization (LFL) based Nonlinear Auto-Regressive Moving Average (NARMA) controller design for a ROTary inverted PENdulum (ROTPEN) plant. The proposed NARMA controller comprises ...
Development of a Multi-Sensor Fire Detector Based on Machine Learning Models [Makine Öǧrenmesi Modellerine Dayali Çok Sensörlö Bir Yangin Algilayicisi Geliştirilmesi]
(Proceedings - 2019 Innovations in Intelligent Systems and Applications Conference, ASYU 2019, 2019)
This paper proposes a method to reduce false positive fire alarms by fusing data from different sensors using a specific machine learning model. We design an electronic circuit with 6 sensors to detect 7 physical sensory ...
Stochastic Microgrid Control Problems: Effects of Load Distribution and Planning Horizon [Rassal Mikro Şebeke Kontrol Problemleri: Yök Daǧilimi ve Planlama Ufuk Uzunluǧunun Etkileri]
(Proceedings - 2019 Innovations in Intelligent Systems and Applications Conference, ASYU 2019, 2019)
Microgrids enable the integration of distributed energy resources with high renewable penetration into the main power grid. In this study, a microgrid problem that takes into account the stochastic nature of the net load, ...
Performance analysis of stable adaptive NARMA controller scheme for furuta pendulum
(2019 23rd International Conference on System Theory, Control and Computing, ICSTCC 2019 - Proceedings, 2019)
This paper presents a novel stable adaptive controller scheme for Furuta Pendulum via nonlinear auto-regressive moving-average based plant identification. During online learning for the developed controller, input-output ...
Comparative study of forecasting schemes for IoT device traffic in machine-to-machine communication
(ACM International Conference Proceeding Series, 2019)
We present a comparative study of Autoregressive Integrated Moving Average (ARIMA), Multi-Layer Perceptron (MLP), 1-Dimensional Convolutional Neural Network (1-D CNN), and Long-Short Term Memory (LSTM) models on the problem ...
An Implementation of Vision Based Deep Reinforcement Learning for Humanoid Robot Locomotion
(IEEE International Symposium on INnovations in Intelligent SysTems and Applications, INISTA 2019 - Proceedings, 2019)
Deep reinforcement learning (DRL) exhibits a promising approach for controlling humanoid robot locomotion. However, only values relating sensors such as IMU, gyroscope, and GPS are not sufficient robots to learn their ...
Data Dependent Stable Robust Adaptive Controller Design for Altitude Control of Quadrotor Model
(Proceedings of the 2018 18th International Conference on Mechatronics - Mechatronika, ME 2018, 2019)
This paper presents Nonlinear Auto Regressive Moving Average (NARMA) based stable robust adaptive controller design. Both the plant and the closed-loop controller systems are modelled by the proposed NARMA based input-output ...
Discriminant-Based Bistability Analysis Of A Tmg-Induced Lac Operon Model Supported With Boundedness And Local Stability Results
(2016)
This paper presents the results of a theoretical and numerical study on the analysis of bistable behavior of the most studied gene regulatory network, the lac operon, in terms of the model parameters. The boundedness of ...
Spatiotemporal chaotification of delta robot mixer for homogeneous graphene nanocomposite dispersing
(Robotics and Autonomous Systems, 2020)
This paper presents the design, implementation and polymer nanocomposite mixing application of a robust spatiotemporal chaotic delta robot. Blending fluids efficiently is a vital process for the preparation of graphene ...
Learning Stable Robust Adaptive NARMA Controller for UAV and Its Application to Twin Rotor MIMO Systems
(Neural Processing Letters, 2020)
This study presents a nonlinear auto-regressive moving average (NARMA) based online learning controller algorithm providing adaptability, robustness and the closed loop system stability. Both the controller and the plant ...