Okyay Kaynak - Academia.edu (original) (raw)
Papers by Okyay Kaynak
Time delays in sensor data is one of the main issues in controlling the attitude of a satellite. ... more Time delays in sensor data is one of the main issues in controlling the attitude of a satellite. Although, there exists methods to alleviate the problem, it is preferable to have a robust controller which can handle delays in sensor data well. In this study, a new method is proposed in the literature which uses an enhanced fuzzy variable structure controller that can handle delays in sensor data well. However it displays a steady state error. The novelty in this study is that the steady state error is handled using an integral term so that an acceptable performance is obtained.
Symbiotic Autonomous Systems (SAS) are advanced intelligent and cognitive systems exhibiting auto... more Symbiotic Autonomous Systems (SAS) are advanced intelligent and cognitive systems exhibiting autonomous collective intelligence enabled by coherent symbiosis of human-machine interactions in hybrid societies. Basic research in the emerging field of SAS has triggered advanced general AI technologies functioning without human intervention or hybrid symbiotic systems synergizing humans and intelligent machines into coherent cognitive systems. This work presents a theoretical framework of SAS underpinned by the latest advances in intelligence, cognition, computer, and system sciences. SAS are characterized by the composition of autonomous and symbiotic systems that adopt bio-brain-social-inspired and heterogeneously synergized structures and autonomous behaviors. This paper explores their cognitive and mathematical foundations. The challenge to seamless human-machine interactions in a hybrid environment is addressed. SAS-based collective intelligence is explored in order to augment huma...
Philosophical Transactions of the Royal Society A: Mathematical, Physical and Engineering Sciences, 2021
Traffic flow characteristics are one of the most critical decision-making and traffic policing fa... more Traffic flow characteristics are one of the most critical decision-making and traffic policing factors in a region. Awareness of the predicted status of the traffic flow has prime importance in traffic management and traffic information divisions. The purpose of this research is to suggest a forecasting model for traffic flow by using deep learning techniques based on historical data in the Intelligent Transportation Systems area. The historical data collected from the Caltrans Performance Measurement Systems (PeMS) for six months in 2019. The proposed prediction model is a Variational Long Short-Term Memory Encoder in brief VLSTM-E try to estimate the flow accurately in contrast to other conventional methods. VLSTM-E can provide more reliable short-term traffic flow by considering the distribution and missing values.
Philosophical Transactions of the Royal Society A: Mathematical, Physical and Engineering Sciences, 2021
Symbiotic autonomous systems (SAS) are advanced intelligent and cognitive systems that exhibit au... more Symbiotic autonomous systems (SAS) are advanced intelligent and cognitive systems that exhibit autonomous collective intelligence enabled by coherent symbiosis of human–machine interactions in hybrid societies. Basic research in the emerging field of SAS has triggered advanced general-AI technologies that either function without human intervention or synergize humans and intelligent machines in coherent cognitive systems. This work presents a theoretical framework of SAS underpinned by the latest advances in intelligence, cognition, computer, and system sciences. SAS are characterized by the composition of autonomous and symbiotic systems that adopt bio-brain-social-inspired and heterogeneously synergized structures and autonomous behaviours. This paper explores the cognitive and mathematical foundations of SAS. The challenges to seamless human–machine interactions in a hybrid environment are addressed. SAS-based collective intelligence is explored in order to augment human capabili...
2014 International Conference on Mechatronics and Control (ICMC), 2014
European Psychiatry, 1991
A novel approach for the minimum effort control of a servo system is proposed. It is based on the... more A novel approach for the minimum effort control of a servo system is proposed. It is based on the prediction of the outputs of the plant over the next N sampling intervals. The scheme adopted for the prediction purposes is simple and has a physical meaning. The loss function, minimized, is composed of the squares of the control efforts and
ARCHIVE: Proceedings of the Institution of Mechanical Engineers, Part I: Journal of Systems and Control Engineering 1991-1996 (vols 205-210), 1993
In long-range predictive control schemes, multi-step ahead predicted values can be arrived at by ... more In long-range predictive control schemes, multi-step ahead predicted values can be arrived at by concatenating the unit step predictions. In doing this, the missing outputs are replaced by their previously predicted values. This approach is much simpler than the approach commonly adopted in the literature which is based on the solution of an identity. The paper concludes with the formulation of the scheme for the trajectory control of a servo-system.
Journal of Intelligent & Robotic Systems, 2010
International Journal of Automation and Control, 2011
This paper proposes to generate potential fields for navigation task of unmanned aerial vehicles ... more This paper proposes to generate potential fields for navigation task of unmanned aerial vehicles (UAVs) which have fuzzy logic-(FL-) based autonomous flight controls. Three FL modules are developed under the navigation system for the control of the altitude, the speed and the heading, through which the global position of vehicle is controlled. A potential field block designed by using sigmoid and normal functions. Limiting functions are defined to provide the circling pattern and to limit the elliptical shape. The output of block produces a ...
IEEE Transactions on Industrial Informatics, 2014
IEEE Transactions on Industrial Electronics, 2001
IEEE 1981 IECI proceedings …, 1981
Proc. of the 1st International Conference on Information Technology in Mechatronics, ITM, 2001
The robotic soccer belongs to the class of multi-agent systems and involves many challenging sub-... more The robotic soccer belongs to the class of multi-agent systems and involves many challenging sub-problems. Teams of robotic players have to cooperate in order to put the ball in the opposing goal and at the same time defend their own goal. The paper is concerned with the problem of learning and implementation of reactive behaviors for robotic agents playing soccer. It briefly presents the whole control system designed for the Cerberus' 01 Sony legged robot team that participated in RoboCup 2001 competitions in ...
The problem of obtaining the error at the output of a neuro sliding mode controller is analyzed i... more The problem of obtaining the error at the output of a neuro sliding mode controller is analyzed in this paper. The controller operates in discrete time and the method presented describes an error measure that can be used if the task to be achieved is to drive the system under control to a predefined sliding regime. Once the task specific output error is calculated, the neurocontroller parameters can be tuned so that the task is achieved. The paper postulates the strategy for discrete time representation of uncertain nonlinear systems belonging to a particular class. The performance of the proposed technique has been clarified on a third order nonlinear system, and the parameters of the controller are adjusted by using error backpropagation algorithm. It is observed that the prescribed behavior can be achieved with a simple network configuration.
International Journal of Adaptive Control and Signal Processing, Oct 1, 2007
In this work, a new dynamical on-line learning algorithm for robust model-free neuro-adaptive con... more In this work, a new dynamical on-line learning algorithm for robust model-free neuro-adaptive control of a class of nonlinear systems with uncertain dynamics is proposed and experimentally tested in order to evaluate its performance and practical feasibility in industrial settings. The control application studied is the trajectory tracking control task for the first three joints of an open architecture articulated robot manipulator. The control scheme makes use of variable structure systems theory and the feedback-error-learning ...
Variable Structure Systems: Towards the 21 st Century, 2002
Intelligence in the form of well-organized solutions to the ill-posed problems has been the prima... more Intelligence in the form of well-organized solutions to the ill-posed problems has been the primary focus of many engineering applications. The ever-increasing developments in data fusion, sensor technology and high-speed microprocessors made the design in digital domain with high performance. A natural consequence of the progression during the last few decades is the emergence of computationally intelligent systems. Neural networks and fuzzy inference systems constitute the core approaches of computational intelligence, whose ...
Journal of Dynamic Systems, Measurement, …, 2000
Time delays in sensor data is one of the main issues in controlling the attitude of a satellite. ... more Time delays in sensor data is one of the main issues in controlling the attitude of a satellite. Although, there exists methods to alleviate the problem, it is preferable to have a robust controller which can handle delays in sensor data well. In this study, a new method is proposed in the literature which uses an enhanced fuzzy variable structure controller that can handle delays in sensor data well. However it displays a steady state error. The novelty in this study is that the steady state error is handled using an integral term so that an acceptable performance is obtained.
Symbiotic Autonomous Systems (SAS) are advanced intelligent and cognitive systems exhibiting auto... more Symbiotic Autonomous Systems (SAS) are advanced intelligent and cognitive systems exhibiting autonomous collective intelligence enabled by coherent symbiosis of human-machine interactions in hybrid societies. Basic research in the emerging field of SAS has triggered advanced general AI technologies functioning without human intervention or hybrid symbiotic systems synergizing humans and intelligent machines into coherent cognitive systems. This work presents a theoretical framework of SAS underpinned by the latest advances in intelligence, cognition, computer, and system sciences. SAS are characterized by the composition of autonomous and symbiotic systems that adopt bio-brain-social-inspired and heterogeneously synergized structures and autonomous behaviors. This paper explores their cognitive and mathematical foundations. The challenge to seamless human-machine interactions in a hybrid environment is addressed. SAS-based collective intelligence is explored in order to augment huma...
Philosophical Transactions of the Royal Society A: Mathematical, Physical and Engineering Sciences, 2021
Traffic flow characteristics are one of the most critical decision-making and traffic policing fa... more Traffic flow characteristics are one of the most critical decision-making and traffic policing factors in a region. Awareness of the predicted status of the traffic flow has prime importance in traffic management and traffic information divisions. The purpose of this research is to suggest a forecasting model for traffic flow by using deep learning techniques based on historical data in the Intelligent Transportation Systems area. The historical data collected from the Caltrans Performance Measurement Systems (PeMS) for six months in 2019. The proposed prediction model is a Variational Long Short-Term Memory Encoder in brief VLSTM-E try to estimate the flow accurately in contrast to other conventional methods. VLSTM-E can provide more reliable short-term traffic flow by considering the distribution and missing values.
Philosophical Transactions of the Royal Society A: Mathematical, Physical and Engineering Sciences, 2021
Symbiotic autonomous systems (SAS) are advanced intelligent and cognitive systems that exhibit au... more Symbiotic autonomous systems (SAS) are advanced intelligent and cognitive systems that exhibit autonomous collective intelligence enabled by coherent symbiosis of human–machine interactions in hybrid societies. Basic research in the emerging field of SAS has triggered advanced general-AI technologies that either function without human intervention or synergize humans and intelligent machines in coherent cognitive systems. This work presents a theoretical framework of SAS underpinned by the latest advances in intelligence, cognition, computer, and system sciences. SAS are characterized by the composition of autonomous and symbiotic systems that adopt bio-brain-social-inspired and heterogeneously synergized structures and autonomous behaviours. This paper explores the cognitive and mathematical foundations of SAS. The challenges to seamless human–machine interactions in a hybrid environment are addressed. SAS-based collective intelligence is explored in order to augment human capabili...
2014 International Conference on Mechatronics and Control (ICMC), 2014
European Psychiatry, 1991
A novel approach for the minimum effort control of a servo system is proposed. It is based on the... more A novel approach for the minimum effort control of a servo system is proposed. It is based on the prediction of the outputs of the plant over the next N sampling intervals. The scheme adopted for the prediction purposes is simple and has a physical meaning. The loss function, minimized, is composed of the squares of the control efforts and
ARCHIVE: Proceedings of the Institution of Mechanical Engineers, Part I: Journal of Systems and Control Engineering 1991-1996 (vols 205-210), 1993
In long-range predictive control schemes, multi-step ahead predicted values can be arrived at by ... more In long-range predictive control schemes, multi-step ahead predicted values can be arrived at by concatenating the unit step predictions. In doing this, the missing outputs are replaced by their previously predicted values. This approach is much simpler than the approach commonly adopted in the literature which is based on the solution of an identity. The paper concludes with the formulation of the scheme for the trajectory control of a servo-system.
Journal of Intelligent & Robotic Systems, 2010
International Journal of Automation and Control, 2011
This paper proposes to generate potential fields for navigation task of unmanned aerial vehicles ... more This paper proposes to generate potential fields for navigation task of unmanned aerial vehicles (UAVs) which have fuzzy logic-(FL-) based autonomous flight controls. Three FL modules are developed under the navigation system for the control of the altitude, the speed and the heading, through which the global position of vehicle is controlled. A potential field block designed by using sigmoid and normal functions. Limiting functions are defined to provide the circling pattern and to limit the elliptical shape. The output of block produces a ...
IEEE Transactions on Industrial Informatics, 2014
IEEE Transactions on Industrial Electronics, 2001
IEEE 1981 IECI proceedings …, 1981
Proc. of the 1st International Conference on Information Technology in Mechatronics, ITM, 2001
The robotic soccer belongs to the class of multi-agent systems and involves many challenging sub-... more The robotic soccer belongs to the class of multi-agent systems and involves many challenging sub-problems. Teams of robotic players have to cooperate in order to put the ball in the opposing goal and at the same time defend their own goal. The paper is concerned with the problem of learning and implementation of reactive behaviors for robotic agents playing soccer. It briefly presents the whole control system designed for the Cerberus' 01 Sony legged robot team that participated in RoboCup 2001 competitions in ...
The problem of obtaining the error at the output of a neuro sliding mode controller is analyzed i... more The problem of obtaining the error at the output of a neuro sliding mode controller is analyzed in this paper. The controller operates in discrete time and the method presented describes an error measure that can be used if the task to be achieved is to drive the system under control to a predefined sliding regime. Once the task specific output error is calculated, the neurocontroller parameters can be tuned so that the task is achieved. The paper postulates the strategy for discrete time representation of uncertain nonlinear systems belonging to a particular class. The performance of the proposed technique has been clarified on a third order nonlinear system, and the parameters of the controller are adjusted by using error backpropagation algorithm. It is observed that the prescribed behavior can be achieved with a simple network configuration.
International Journal of Adaptive Control and Signal Processing, Oct 1, 2007
In this work, a new dynamical on-line learning algorithm for robust model-free neuro-adaptive con... more In this work, a new dynamical on-line learning algorithm for robust model-free neuro-adaptive control of a class of nonlinear systems with uncertain dynamics is proposed and experimentally tested in order to evaluate its performance and practical feasibility in industrial settings. The control application studied is the trajectory tracking control task for the first three joints of an open architecture articulated robot manipulator. The control scheme makes use of variable structure systems theory and the feedback-error-learning ...
Variable Structure Systems: Towards the 21 st Century, 2002
Intelligence in the form of well-organized solutions to the ill-posed problems has been the prima... more Intelligence in the form of well-organized solutions to the ill-posed problems has been the primary focus of many engineering applications. The ever-increasing developments in data fusion, sensor technology and high-speed microprocessors made the design in digital domain with high performance. A natural consequence of the progression during the last few decades is the emergence of computationally intelligent systems. Neural networks and fuzzy inference systems constitute the core approaches of computational intelligence, whose ...
Journal of Dynamic Systems, Measurement, …, 2000