Okyay Kaynak

• PH.D.
• Professor (Full) at Boğaziçi University

The intelligent manufacturing system is a complex, large-scale, interconnected system composed of many intelligent agents, and there may be physical or information space couplings between the agents. A distributed monitoring system and optimization control method are proposed to ensure the system completes its tasks safely and efficiently. The dist...

Due to limitations in large-area communication and computation, it can be challenging to apply centralized diagnosis and optimization control design approaches to cascaded systems. This work proposes a distributed diagnosis and optimization control approach, which is realized using data-driven techniques. Specifically, an adaptive observer-based su...

This article proposes a distributed performance recovery method for multiagent systems with actuator faults in noncooperative games. The local agent (player) can only obtain the policy information of neighboring agents through the communication network. The strategies of nonneighbors in the cost function are unknown, and a leader–follower consensus...

This study provides a view of how industrial metaverses shape a higher-dimensional world on top of the physical world humans live in and expands the discussion along the dimensions of “support technologies” and “scenarios of potential industrial applications”. Careful observations of research communities and markets have provided insight into some...

As industrial cyber-physical systems (ICPS) play an increasingly pivotal role in the new industrial paradigm, their sustainability has become the current research focus. Remaining useful life (RUL) prediction, also known as prognostics, is critically significant for the sustainability of ICPS. The prognostics involve utilizing process monitoring de...

In this paper, a novel Z-number based Fuzzy Neural Network (Z-FNN) based on the integration of Z-valued fuzzy logic and neural networks is proposed. Z-valued fuzzy rule base is presented and its inference process is described using interpolative approximate reasoning. Accordingly, the structure of the Z-FNN is proposed using a distance measure and...

Over the last decade, transfer learning has attracted a great deal of attention as a new learning paradigm, based on which fault diagnosis (FD) approaches have been intensively developed to improve the safety and reliability of modern automation systems. Because of inevitable factors such as the varying work environment, performance degradation of...

In the new industrial environment, the safe and reliable operation of Industrial Cyber-Physical Systems (ICPSs) is being threatened by new types of attacks: Attackers carefully tamper with the measurement and control data transmitted over the network, causing the controlled systems to behave abnormally. The essence of such threats is operational sa...

The study of artificial intelligence (AI) has been a continuous endeavor of scientists and engineers for over 65 years. The simple contention is that human-created machines can do more than just labor-intensive work; they can develop human-like intelligence. Being aware or not, AI has penetrated into our daily lives, playing novel roles in industry...

p>Industrial Metaverse is a novel ecological system for modern industry. One of the most inspiring parts of Industrial Metaverse lies in the potential to restructure the industrial chain and to provide added value to all the stakeholders therein. It is being enabled by the deep intertwining of SOTA ICT (information & communication technology) and t...

p>Industrial Metaverse is a novel ecological system for modern industry. One of the most inspiring parts of Industrial Metaverse lies in the potential to restructure the industrial chain and to provide added value to all the stakeholders therein. It is being enabled by the deep intertwining of SOTA ICT (information & communication technology) and t...

p>Over the last decade, transfer learning has attracted a great deal of attention as a new learning paradigm, based on which fault diagnosis (FD) approaches have been intensively developed to improve the safety and reliability of modern automation systems. Because of inevitable factors such as the varying work environment, performance degradation o...

p>Over the last decade, transfer learning has attracted a great deal of attention as a new learning paradigm, based on which fault diagnosis (FD) approaches have been intensively developed to improve the safety and reliability of modern automation systems. Because of inevitable factors such as the varying work environment, performance degradation o...

Inaccurate model, uncertainties and valve bias are the main challenges for the controller design of high precision electro-hydraulic servo systems. To achieve a satisfactory tracking control performance under such difficulties, a fractional order integral sliding mode controller based on a radial basis function neural network(RBFNN) is proposed and...

Abstract—Threats of cyber attacks have penetrated from disclosing critical user information to destroying/manipulating industrial control systems. Study on data security during network transmission has raised increasing attention in the systems and control community, which is found very necessary and timely in the context of Industry 4.0. In most e...

This paper investigates a novel model-free optimal controller for nonlinear autonomous underwater vehicles (AUVs). It is considered that the AUV considered as the case study is subject to multi-asymmetric constrained inputs. To achieve the optimal controller, a performance index function with exponential discounted value term and input hyperbolic f...

Multi-step time-series prediction is an essential supportive step for decision-makers in several industrial areas. Artificial intelligence techniques, which use a neural network component in various forms, have recently frequently been used to accomplish this step. However, the complexity of the neural network structure still stands up as a critica...

As a result of informatization and wider use of connected intelligence, modern industry has evolved into being large-scale. To overcome the inevitable shortcomings of centralized design in such cases, this paper proposes a subspace-aided distributed closed-loop monitoring approach for interconnected systems. It only uses measurement information fro...

As an indispensable energy device, 18650 lithium-ion battery has widespread applications in electric vehicles. Remaining useful life (RUL) prediction of lithium-ion battery is critical for the normal operation of electric vehicles. In conventional approaches, the adaptive estimation of model parameters and the detection of capacity regeneration awa...

Sensors are ubiquitous in automatized industrial systems. To ensure the safety of the process control, the fault diagnosis and fault-tolerant control of sensors is necessary. This article proposes subspace-aided sensor fault diagnosis and compensation control approaches based on the data-driven stable kernel representation (SKR) and stable image re...

With the frequent occurrence of safety incidents in cyber–physical systems (CPSs), great significance has been attached to the study of defense schemes against cyber–physical attacks. In this paper, an integrated data-driven defense scheme is proposed, which can sensitively detect data integrity attacks such as false data injection (FDI) attacks, d...

During the last two decades, profound technological changes have taken place around us, supported by disruptive advances, both on the software and hardware sides. An amalgamation of information, communication, and artificial intelligence is taking place, as well as the cross-fertilization of a wide range of concepts, referred to as the digital tran...

Digitization and digitalization have already changed our world significantly. Further disruptions are imminent with the ongoing digital transformation, a major component of which is digital twins. As the big data techniques, Internet of Things, cloud computing, and artificial intelligence algorithms advance, the digital twin technology has entered...

Deep learning techniques have promoted the rise of artificial intelligence (AI) and performed well in computer vision. Medical image analysis is an important application of deep learning, which is expected to greatly reduce the workload of doctors, contributing to more sustainable health systems. However, most current AI methods for medical image a...

This brief proposes a subspace-aided fault detection approach for the drive systems of strip rolling mills. Considering the impact of the unknown periodic load generated by the strip rolling process, the primary contributions are concluded as follows. First, this brief presents an approach to describe the subspace of the unknown/unmeasurable period...

The fourteen papers in this special section focus on data-drive management of complex systems via plant-wide performance supervision. Currently, massive amounts of data are continuously being produced by social and industrial activities. Consequently, data-driven techniques have received considerable attention both in industry and academia in recen...

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...

A digital twin (DT) is classically defined as the virtual replica of a real-world product, system, being, communities, even cities that are continuously updated with data from its physical counterpart, as well as its environment. It bridges the virtual cyberspace with the physical entities and, as such, is considered to be the pillar of Industry 4....

Starting in the second half of the last century, the widespread use of computers has significantly changed the lifestyles of humankind. Since then, with the explosive and perhaps disruptive developments in digital technology, the internet and Internet of Things and artificial intelligence have promoted a growing interaction among humans and machine...

Gradient descentGradient Descent (GD) is a computational optimization method which is based on the first-order Taylor expansion of nonlinear functions. In order to find a local minimum for a nonlinear function, this algorithm uses the initial parameters of the nonlinear function and updates these parameters in the negative direction of the gradient...

The feedback linearization method can be used to control nonlinear systems without linearizing them around a specific equilibrium point. This controller includes a nonlinear feedback controller to eliminate the nonlinear terms. The mathematical preliminaries to design a feedback linearization controller is established in this chapter. The following...

Fuzzy logicFuzzy logic has proved itself as an advanced model-free approach with tremendous impact on control community. Fuzzy logicFuzzy logic has the ability to handle uncertainties, lack of modeling, and operational disturbances in a control system using expert knowledge. In this chapter, rule-based sliding mode fuzzy logic controllers are desig...

Optimization is the selectionSelection process of the best elements with respect to some criterion from a feasible set of variables. There may be single or multiple objectives to be considered during optimization. The optimization process generally involves the minimization of a cost or maximization of a profit. Sliding mode controller design probl...

Lack of imprecise nonlinear model of real-time systems is inevitable due to several simplifications made, neglected frictions, dead-zones, and saturation. One of the most well-known nonlinear control design tools to deal with uncertainties is sliding-mode control approach. In this method the desired behavior is defined in terms of a sliding manifol...

Control of a system—for example, operation of a robot—through a communication link from a distant location is called teleoperationTeleoperation. Remote operations in hazardous and unreachable areas are crucial and inevitable; examples of such areas are complex and challenging tasks in disaster areas, space robotic applications, remotely operated ve...

This chapter deals with adaptive design of fuzzy controllers based on sliding-modeSliding mode control law. As it was mentioned earlier, a challenge to design a sliding- modeSliding mode controller is necessity to have the nominal dynamics of the system. This requires a series of modeling prior to the control of the system. Fuzzy logic systems as g...

Centralized direct digital control systemsDirect digital control systems have several drawbacks, for example, massive wiring requirements, difficult diagnosis, and difficult fault detection procedures. Most of these drawbacks may impose heavy costs on the maintenance of the control system. These disadvantages have given rise to the development of N...

The word “fuzzy” means imprecisely defined, confused, and vague. However, fuzzy systems benefit from mathematical formulation to determine their output. This chapter deals with type-1 fuzzy systems as well as interval type-2 fuzzy systems in which different parts of these fuzzy systems are explained.

In this paper, a novel time-domain frequency estimation approach is proposed based on the well-known Subspace Identification Method (SIM). Differing from the Fast Fourier Transformation (FFT) method, the nonlinear identification for frequency estimation is reformulated into the eigenvalue identification problem, which avoids the spectrum peak searc...

Provision of some autonomous functions to an agricultural vehicle would lighten the job of the operator but in doing so, the accuracy should not be lost to still obtain an optimal yield. Autonomous navigation of an agricultural vehicle involves the control of different dynamic subsystems, such as the yaw angle dynamics and the longitudinal speed dy...

Free link to the article https://authors.elsevier.com/a/1cKoc4ZQE1aqw

The papers in this special section focus on the use of mechatronics in unmanned systems. During the past few decades, unmanned systems have widely been applied in the environs of aerospace, ground, surface, and underwater. It is expected that unmanned systems will have more pervasive applications in industry, military, agriculture, logistics, etc.,...

Short-term water demand forecasting (StWDF) is the foundation stone in the derivation of an optimal plan for controlling water supply systems. Deep learning (DL) approaches provide the most accurate solutions for this purpose. However, they suffer from complexity problem due to the massive number of parameters, in addition to the high forecasting e...

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 s...

This paper considers the problem of distributed adaptive fuzzy event-based finite-time prescribed performance leader-following tracking control for heterogeneous nonlinear multi-agent systems (NMASs) over a directed topology. Each agent is considered in a non-affine nonstrict-feedback form under input saturation and output constraint which contains...

The Industrial Revolution, which originally involved the change from an agrarian and handicraft economy to a market dominated by factory mechanization during the early 18th century, has profoundly shaped the world. It has progressed through four disruptive phases: Industry 1.0 through Industry 4.0. Industry 1.0 encompassed early automation, while I...

This book addresses some of the challenges suffered by the well-known and robust sliding-mode control paradigm. The authors show how the fusion of fuzzy systems with sliding-mode controllers can alleviate some of these problems and promote applicability. Fuzzy systems used as soft switches eliminate high-frequency signal oscillations and can subst...

The intensive research and development efforts directed towards large-scale complex industrial systems in the context of Industry 4.0 indicate that safety and reliability issues pose significant challenges. During online operation, system performance degradation will lead, not only to economic losses, but also potential safety hazards. In the exist...

In recent years, with the rapid growth of rooftop photovoltaic (PV) generation in distribution networks, power system operators call for accurate forecasts of the behind-the-meter (BTM) load and PV generation. However, the existing forecasting methodologies are incapable of quantifying such BTM measurements as the smart meters can merely measure th...

The problem of finite-time path following control for a typical 6-DOF (degree of freedom) autonomous underwater vehicle (AUV) subjected to parametric and modeling uncertainties, disturbances and unknown saturation nonlinearities is studied and discussed in this paper. For the mentioned AUV, finite-time control inputs are designed based on innovativ...

This article investigates the design of an optimal tracking controller for a class of nonlinear continuous-time systems with time-delay, mismatched external disturbances and input constraints. The technique of integral reinforcement learning (IRL) is utilized for determining the control input that optimizes an objective function. To enable the usag...

Over the past twenty years, numerous research outcomes have been published, related to the design and implementation of soft sensors. In modern industrial processes, various types of soft sensors are used, which play essential roles in process monitoring, control and optimization. Emerging new theories, advanced techniques and the information infra...

In this paper, a real-time three-tank system setup is used for practical investigations. Differing with the virtual simulator of three-tank system, the setup can enable the setting of different types of faults through manual manipulation, users can choose the combinations of different valves and knobs in the setup which is helpful to evaluate and c...

Due to the recent rapid developments in communication and networking technologies as well as computer science, the complexity of automatic control systems has increased significantly. To ensure the safety and the reliability of such systems under continuous operation, real-time supervision and control systems have now to run in parallel. These deve...

This paper considers chaos in a PI control system for the first time and presents an equivalent-input-disturbance (EID)-based control method to suppress a chaotic phenomenon. Since the chaos is caused by two nonlinear terms, two EID estimators are used to separately compensate for them, and thus to suppress any possible chaos. This paper devises a...

A finite-time control method is presented for $n$ -link robots with actuator saturation under time-varying constraints of work space. Barrier Lyapunov functions (BLFs) are designed for ensuring that the robot remains under time-varying constraints of the work space. In order to deal with asymmetric saturation nonlinearity, we transform asymmetric...

The fault-tolerant control (FTC) issue is considered in this article for Markovian jump systems (MJSs) in which both nonlinearity and actuator faults exist simultaneously. The existed nonlinearity in the considered MJSs means that there exist limitations to employ the renown sliding mode control (SMC) method directly. In this work, the radial basis...

This paper selected nine novel feature quantities that can reflect control performance in the closed-loop. Combined with support vector machine (SVM) and k-nearest neighbor (KNN), they are used to perform accurate fault diagnosis. Stability margin describes the degree of stability of the transfer function matrix of system, and thus can be used as a...

In this paper, a data-driven predictive control strategy for nonlinear system is proposed and testified on a continuous stirred tank heater (CSTH) benchmark. A recursive modified partial least square (RMPLS) algorithm is employed to regress the local linear model. The algorithm of locally weighted projection regression (LWPR) is then leveraged to b...

This paper is concerned with a novel data-driven bias-eliminated subspace identification approach for closed-loop systems. Compared with the existing methods, the proposed method firstly proposes to utilize the coprime factorization of the controller to construct an instrumental variable uncorrelated with noise under closed-loop conditions. Further...

In the conventional approaches to the design of fault diagnosis systems, little effort is usually paid to the selection of the parity vectors. As a result, the systems' performance can be significantly affected. In this work, novel approaches are proposed to derive the parity vectors that construct optimized residual generators for linear and nonli...

p>During the last two decades, profound technological changes have taken place around us, supported by disruptive advances, both on software and hardware sides. An amalgamation of information, communication and AI is taking place, as well as the cross-fertilization of a wide range of concepts, referred to as the digital transformation. As a re...

p>During the last two decades, profound technological changes have taken place around us, supported by disruptive advances, both on software and hardware sides. An amalgamation of information, communication and AI is taking place, as well as the cross-fertilization of a wide range of concepts, referred to as the digital transformation. As a re...

This paper describes a novel approach for the control of underwater robots that can handle uncertainties and disturbance problems, which are commonly met in underwater environments. The considered system is an underwater manipulator with n-degrees of freedom. The approximation capability of an adaptive neural network is exploited to estimate uncert...

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...

Filters are the fastest among the different types of feature selection methods. They employ metrics from information theory, such as mutual information (MI), Joint-MI (JMI), and minimal redundancy and maximal relevance (mRMR). The determination of the optimal feature selection set is an NP-hard problem. This work proposes the engineering of the Gen...

It is well known that cyber-physical systems (CPSs) commonly exist in both industrial manufacturing and people’s daily lives. As a hot topic within Industry 4.0, CPSs have attracted interest from both academia and industry. Typical examples of CPSs include autonomous vehicles, smart grid, process control systems, and industrial robotics systems. Th...

In most of industrial applications, the dynamics of the system in hand are perturbed by a number of operational conditions. Also the outputs of the sensors always include noise. To alleviate these common problems, this paper presents a novel fuzzy control approach based on the immersion and invariance (I&I) approach under the conditions of unknown...

In this paper, a fractional order model of pneumatic servo system is introduced by replacing the integer order dynamic equation with the corresponding fractional order one. Then, a Fractional order Proportional-Integer-Differential (FPID) controller is optimized for the servo system using an online multi-variable multi-objective genetic algorithm (...

In this paper, the complex problems of internal forces and position control are studied simultaneously and a disturbance observer-based radial basis function neural network (RBFNN) control scheme is proposed to: 1) estimate the unknown parameters accurately; 2) approximate the disturbance experienced by the system due to input saturation; and 3) si...

In this paper, a novel robust predictive control strategy is proposed for the synchronization of fractional-order time-delay chaotic systems. A recurrent non-singleton type-2 fuzzy neural network (RNT2FNN) is used for the estimation of the unknown functions. Additionally, another RNT2FNN is used for the modeling of the tracking error. A nonlinear m...

Robust and accurate control of a flapping-wing aerial vehicle (FWAV) system is a challenging problem due to the existence of backlash-like hysteresis nonlinearity. This paper proposes uncertainty and disturbance estimator (UDE)-based control with output feedback for FWAV systems. The approach enables the acquisition of the approximate plant model w...

Gas flow has fractional order dynamics; therefore, it is reasonable to assume that the pneumatic systems with a proportional valve to regulate gas flow have fractional order dynamics as well. There is a hypothesis that the fractional order control has better control performance for this inherent fractional order system, although the model used for...

The performance of the pneumatic elements and the micro-controller steadily increases as the price of them decreases. This trend promotes the high performance tracking control research on pneumatic servo systems. However, it is very difficult to obtain exact model parameters, which is one of main obstacles to design a high performance controller. M...

In this paper, a robust adaptive control scheme is proposed for the leader following control of a class of fractional-order multi-agent systems (FMAS). The asymptotic stability is shown by a linear matrix inequality (LMI) approach. The nonlinear dynamics of the agents are assumed to be unknown. Moreover, the communication topology among the agents...

Industrial cyber-physical systems (ICPSs) are the backbones of Industry 4.0 and as such, have become a core transdisciplinary area of research, both in industry and academia. New challenges brought about by the growing scale and complexity of systems, insufficient information exchange and the exploitation of knowledge available have started threate...

An intelligent data-driven predictive control strategy is proposed in this paper. The predictive controller is designed by combining predictive control and local weighted projection regression. The presented control strategy needs less prior knowledge and has fewer parameters that are hard to determine compared to other data-driven predictive contr...

The eleven papers included in this special section focus on sliding mode control and observation for complex industrial systems. Addresses such topics as control design of power electronics, control design of vehicl e systems, and control/switching techniques.

The papers in this special section focus on sliding mode control and observations for complex industrial systems. With the recent rapid developments in industrial technology, the modern industrial systems have become more and more complex requiring a greater attention to be paid on the stabilizability, the robustness, the reliability, and the optim...

A data-driven model predictive control (MPC) that combines modified partial least squares (PLSs) and MPC is proposed in this paper. A theoretical comparison among traditional MPC, MPC in PLS framework and in modified PLS framework is presented, which demonstrates that the proposed MPC approach has high prediction precision and the ability in coping...

Accurate wind speed forecasting is a fundamental requirement for large-scale integration of wind power generation. However, the intermittent and stochastic nature of wind speed makes this task challenging. Artificial neural networks (ANNs) are widely used in this area; however, they may fail to provide the accuracy that may be required. This is due...

The robust parameter and output estimation for linear parameter varying (LPV) time-delay system with output data contaminated with outliers and subjected to randomly missing measurements are considered in this paper. The outliers, missing data, and the time-delay are widely existed in practical industry and have imposed extra difficulties on comple...