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Showing papers in "Advances in Control and Optimization of Dynamical Systems in 2022"


Journal ArticleDOI
TL;DR: In this article , the authors used YOLO V5 to confirm the position relationship between tomatoes and peduncles, and then they used the boundary boxes center of the peduncle as the picking points, the corresponding depth information was obtained and the robot was controlled to complete the picking task.
Abstract: Tomato picking robots can save labor and improve production efficiency, which is of great significance for facility tomato planting. The picking mode of the Tomato Picking Robot has an important impact on fruit picking quality and efficiency. At present, in the process of fruit picking, the rough recognition of fruit positioning needs compensation accuracy. The picking mode is usually to capture the fruit in a large range and then separate the fruit peduncles in a specific position. In the process of grasping and pulling the fruit, it may cause damage to the fruit and plant, which will reduce the fruit quality. Moreover, The retention length of peduncles is also difficult to control, resulting in difficulties in transportation and storage. Therefore, the prediction, location and segmentation of separation points on tomato images are an important guarantee for efficient and lossless harvest. In this study considering the changeable conditions such as light change and branches and leaves interference, YOLO V5 is used to confirm the position relationship between tomatoes and peduncles. The region of interest for peduncles picking is reduced according to the growth characteristics of the fruit. Then, taking the boundary boxes center of the peduncles as the picking points, the corresponding depth information is obtained and the robot is controlled to complete the picking task. The experimental results show that this method can recognize and locate tomato picking points under complex near-color backgrounds. The average recognition time of a single frame image is 104 ms, which meets the real-time requirements of automatic picking. Compared with the SSD algorithm, it has obvious advantages.

14 citations


Journal ArticleDOI
TL;DR: In this paper , a novel PD with filter coefficient (PDN) controller cascade with fractional-order PID with filter coefficients (FOPIDN) is proposed as a secondary controller for combined ALFC-AVR loop.
Abstract: This paper discusses the significance of various energy storage devices like redox flow battery (RFB), capacitive energy storage (CES), superconducting magnetic energy storage (SMES), and flywheel energy storage system (FESS) impact on the combined control of automatic load frequency control (ALFC) and automatic voltage regulator (AVR) of three areas interconnected power systems having thermal, hydro, gas, and geothermal plants in presence of HVDC link. A novel PD with filter coefficient (PDN) controller cascade with fractional-order PID with filter coefficient (FOPIDN), CPDN-FOPIDN is proposed as a secondary controller for combined ALFC-AVR loop. An artificial flora algorithm is utilized to obtain the various controller parameters under numerous system conditions. The proposed CPDN-FOPIDN controller provides less settling time, overshoots, undershoots, and reduces oscillation compare to the FOPIDN controller. The study also reveals that the RFB provides better system performance than SMES, CES, and FESS. Integration of HVDC link improves the system dynamic response. Furthermore, the sturdiness of the proposed CPDN-FOPIDN controller is tested against the changes in system loading conditions via sensitivity analysis.

8 citations


Journal ArticleDOI
TL;DR: In this article , the authors reviewed and evaluated various RUL predictive models for aircraft engines and compared their performance with a proposed Long Short Term Memory (LSTM) method based on a data-driven machine learning approach.
Abstract: In a critical business sector such as the aviation industry, remaining useful life (RUL) prediction helps engineers schedule maintenance to avoid the risk of catastrophic failure in both the manufacturing and the servicing sectors. This paper attempts to review and evaluate various RUL predictive models for aircraft engines and compare their performance with a proposed Long-Short Term Memory (LSTM) method based on a data-driven machine learning approach. This study uses the C-MAPSS datasets in order to evaluate the performance and the results of each approach. The obtained outcomes show that the modified LSTM method with Attention mechanism improves the RUL prediction for aircraft engines and provides better performance.

8 citations


Journal ArticleDOI
TL;DR: A survey of reinforcement learning can be found in this article , where three major groups of approaches are overviewed: supervisor-based, Lyapunov reinforcement learning and fusion with model-predictive control.
Abstract: Reinforcement learning is concerned with a generic concept of an agent acting in an environment. From the control theory standpoint, reinforcement learning may be considered as an adaptive optimal control scheme. Despite accumulating evidence of effectiveness of reinforcement learning in various applications, which range from video games to robotics, this control scheme in its bare-bones version provides no guarantees on the performance of the agent-environment closed loop. Measures have to be taken to provide the said guarantees. This survey gives a brief picture of the current progress in this direction. Three major groups of approaches are overviewed: supervisor-based, Lyapunov reinforcement learning and fusion with model-predictive control. The central message of this survey is that a synergy with classical model-based control seems the most promising direction of research in reinforcement learning, as long as it is to become an industry standard.

8 citations


Journal ArticleDOI
TL;DR: In this article , a generic deployment methodology for the Digital Twin (DT) is proposed based on the 5C decomposition of Cyber-Physical Systems (CPS), where the first level "Configuration" implies the setting up of a generic architecture, hence the DT typology presented in this paper.
Abstract: The Digital Twin, being a new transversal technology, has spread very quickly in several fields (industry, transportation, building, healthcare, etc.) and often in an anarchic way. As a result, several attempts to standardize and propose generic models for the Digital Twin (DT) have been made, in order to counterbalance the large heterogeneity that characterized the development of this technology as a consequence of a certain hype around this theme. This paper presents work that is part of our endeavors to develop a generic deployment methodology for DT, focusing on its interactional and systemic aspects. The deployment methodology is based on the 5C decomposition of Cyber-Physical Systems (CPS), where the first level "Configuration" implies the setting up of a generic architecture, hence the DT typology presented in this paper. Based on this, we presented a new vision of the 5D model of the DT, and then highlighted the interaction and evolution mechanisms that can characterize this latter during its life cycle. Finally, we discussed the concept of a hierarchical network of interconnected and evolving DTs. This will pave the way to further research that will address more specific architectures and technology dependent, dealing with the last level of the 5C pyramid.

7 citations


Journal ArticleDOI
TL;DR: In this paper , the stabilizing P, PD, or PDA controllers for time-delayed first-order systems extended by automatic reset (disturbance reconstruction and compensation) established by evaluating the steady state output values of the controller, yield series PI, PID or PIDA controllers.
Abstract: The article shows that the stabilizing P, PD, or PDA controllers for time-delayed first-order systems extended by automatic reset (disturbance reconstruction and compensation) established by evaluating the steady state output values of the controller, yield series PI, PID or PIDA controllers. By comparing the parameters of the given controllers tuned by the method of multiple real dominant pole, it can be shown that the obtained values of the integration time constant are many times larger than the time constants of the transients of the equivalent circuits with the stabilizing controller. The proposed interpretation of the functionality of disturbance observer included in controllers with disturbance compensation significantly helps in understanding principles of their optimal tuning, can also be used for further modifications of their operation taking into account various other limitations and establishes a unique educational framework covering most of the existing traditional, modern and postmodern controllers.

7 citations


Journal ArticleDOI
TL;DR: In this article , the longitudinal behavior of the drive wheel is modeled using the Pacejka model or magic formula, which describes the interaction between the tire and the road surface, which reflects road condition effect.
Abstract: Vehicles using internal combustion engine (ICE) adversely affect the environment. Therefore, all vehicle makers have started their mutation toward electric vehicles. In this paper, a quarter vehicle model is developed considering brushless DC (BLDC) motor actuation. The longitudinal behavior of the drive wheel is modeled using the Pacejka model or magic formula. This model describes the interaction between the tire and the road surface, which reflects road condition effect. The purpose of the control is to provide smooth speed control in both acceleration and deceleration modes, regardless of changes in road conditions. Due to the high complexity of the control model, a hybrid fuzzy-PID controller is designed to serve as a speed controller for the system motor-tire-road-surface. It is checked by numerous simulations that the proposed controller performs well, ensuring comfortable steering operation despite road characteristic changes.

7 citations


Journal ArticleDOI
TL;DR: In this article , the authors proposed a method based on artificial neural networks (ANN) using synchronized data provided by Phasor Measurement Units (PMU) to monitor the load margin of systems meeting voltage stability and small-signal stability requirements.
Abstract: The power system load margin is an index that provides information on how far the system is from a case of instability. Usually, this load margin is calculated considering voltage stability requirements but low frequency oscillation modes with low damping rates, a field of study in small-signal stability, can also compromise the proper operation of power systems and so should be considered in calculating the load margin. This paper proposes a method based on artificial neural networks (ANN) using synchronized data provided by Phasor Measurement Units to monitor the load margin of systems meeting voltage stability and small-signal stability requirements. Furthermore, a Genetic Algorithm-based approach is used to select a reduced number of buses for the ANN input layer. Results of applications of the proposed method show the applicability for real-time monitoring of the load margin.

7 citations


Journal ArticleDOI
TL;DR: In this paper , a data-driven method is proposed to design an input assignment and a stabilizing controller to avoid a critical transition from a healthy state to a disease state, which is caused by qualitative shifts in gene networks.
Abstract: During the progression of complex diseases caused by qualitative shifts in gene networks, the deteriorations may be abrupt and cause a critical transition from a healthy state to a disease state. We define a pre-disease state as a state just before the imminent critical transition. Medical treatment in the pre-disease state should be more efficient than in the disease state. This paper proposes a data-driven method to design an input assignment and a stabilizing controller to avoid this kind of qualitative shift. The proposed method only requires a small number of data samples on the steady pre-disease state. We show numerical examples to validate the effectiveness of the proposed method.

7 citations


Journal ArticleDOI
TL;DR: In this article , a synchronization-oriented MPC with four principles is proposed to address the increasing economic, social and environmental requirements in the context of Industry 4.0 and even Industry 5.0.
Abstract: Benefiting from the marriage of just-in-time (JIT) and computer integrated manufacturing (CIM), a series of manufacturing planning and control (MPC) systems has been introduced for contemporary production and operations management. However, the increasing requirements for customized and personalized products and services, together with the acceleration of the socio-economic environment in the age of Industry 4.0, forced manufacturers to re-evaluate their current MPC strategies that mainly emphasize time, cost and quality priorities. Industry 4.0 presents a solid ambition for transforming to a digital, data-driven and interconnected manufacturing industry centred around cyber-physical convergence. Although the relevance of Industry 4.0 technologies’ disruptions on operations management has been acknowledged, a significant gap in the evolution of the logic and design of MPC systems has been observed. The requirements of on-demand products and services with enhanced flexibility, resilience, sustainability and humanitarianism in this new industrial revolution call for innovations of MPC architectures and approaches. This paper first summarizes the evolution of MPC systems with enabling technologies and the changing business climate at that time. To explore innovative MPC that complies with the increasing economic, social and environmental requirements, the concept of synchronization-oriented MPC with four principles is proposed. Following the principles, a general framework for the synchronization-oriented MPC with enhanced economic, social and environmental benefits is developed. This work potentially provides insights into innovative MPC in the age of Industry 4.0 and even Industry 5.0.

7 citations


Journal ArticleDOI
TL;DR: In this article , a multi-criteria decision-making model for the digitalization of industrial plants is developed based on both Fuzzy Logic and AHP and combined with an existing hierarchical classification of digital technologies in an attempt to highlight the advantage of adopting similar and easily interconnectable technologies.
Abstract: The presence of Industry 4.0 national plans and the ever-increasing international competition are forcing companies to embark on digitalization projects of their industrial plants. Time and money, however, are a constraint and, in addition to that, there is a considerable lack of works in the academic literature with regards to specific models for the selection of digital technologies. Starting from our methodological framework, we developed a multi-criteria decision-making model for the digitalization of industrial plants. The model is based on both Fuzzy Logic and AHP and is combined with an existing hierarchical classification of digital technologies in an attempt to highlight the advantage of adopting similar and easily interconnectable technologies. Finally, the model is applied to a simple case study to test its validity.

Journal ArticleDOI
TL;DR: In this article , a modification of typical GNE-seeking problems with affine coupling constraints is considered, where each agent's objective additionally depends on the measurable output of a nonlinear input-output mapping.
Abstract: This paper examines the intersection between feedback-based optimization problems and distributed Nash equilibrium seeking algorithms. We consider a modification of typical GNE-seeking problems with affine coupling constraints, wherein each agent's objective additionally depends on the measurable output of a nonlinear input-output mapping. Operator-theoretic methods are leveraged to develop an online distributed algorithm for this class of problems, with convergence criteria provided. We illustrate the algorithm via an application to coordination of distributed energy resources in a power distribution feeder.

Journal ArticleDOI
TL;DR: In this article , a nonlinear controller for an autonomous UAV to follow a predefined trajectory is proposed, where the UAV is made to follow the desired path by driving the relative distance to the path, and its look angle to zero.
Abstract: In this work, we design a nonlinear controller for an autonomous unmanned aerial vehicle (UAV) to follow a predefined trajectory. The UAV is made to follow the desired path by driving the UAV’s relative distance to the path, and its look angle to zero. The proposed design is easy to implement as it does not need path curvature information and uses the philosophy of target pursuit to follow the predefined path. We further demonstrate the merits of the proposed method through simulations for various cases in accurately tracking straight line and curvilinear paths.

Journal ArticleDOI
TL;DR: In this paper , a fuzzy-based harmonic search (HS) metaheuristic technique for optimizing type-1 fuzzy controller for Fault-Tolerant Control (FTC) for nonlinear level control application subject to two uncertainties (i.e. actuator fault and external process disturbances), using type- 1 and interval type- 2 fuzzy based HS algorithms.
Abstract: This research offers a fuzzy-based harmonic search (HS) metaheuristic technique for optimizing type-1 fuzzy controller for Fault-Tolerant Control (FTC) for nonlinear level control application subject to two uncertainties (i.e. actuator fault and external process disturbances), using type-1 and interval type-2 fuzzy-based HS algorithms. The effectiveness of a fuzzy logic-based adaptive HS algorithm in a nonlinear two-tank level control process with the primary actuator has dwindled (LOE). The work key contribution is the discovery of the best technique for constructing an optimal vector of values for the fuzzy controller’s membership functions (MFs) optimization. This is made to improve dynamic response by bringing the process value of the two-tank level control process close to the target process value (set-point). It’s worth noting that the type-1 fuzzy controller’s optimized MFs use an interval type-2 fuzzy system for parameter adaptation of the HS algorithm, which can handle greater uncertainty than a type-1 fuzzy system. In this case, the limiting MFs of interval type-2 fuzzy sets are type-1 fuzzy sets, which defne the footprint of uncertainty (FOU). Simulation results show that FHSO using an interval type-2 fuzzy system outperforms FHSO using a type-1 fuzzy system in the optimal design of a type-1 fuzzy controller.

Journal ArticleDOI
TL;DR: In this article , an Extended Kalman Filter is used to estimate the state of health and the dynamics of the degradation, and the remaining useful life is predicted with respect to failure thresholds pre-set by the user.
Abstract: Reduction of spaceflight costs calls for development of new technologies that render rockets reusable. This new requirement and the continuous improvement of rocket engines require pro-active approach towards the possibility of integrating health monitoring systems on-board. These health monitoring strategies should also take into consideration the state of degradation and the remaining useful life prediction. In this paper, an Extended Kalman Filter is used to estimate the state of health and the dynamics of the degradation, and the remaining useful life is predicted with respect to failure thresholds pre-set by the user. The first-order inverse reliability method is employed to assess the quality of the remaining useful life prediction by quantifying the associated uncertainty. The overall method is validated using simulation study involving degradation data provided by Centre National d'Etudes Spatiales (CNES) applied to liquid propulsion rocket engine (LPRE) combustion chamber.

Journal ArticleDOI
TL;DR: In this article , an agent-based approach for enhancing the digitization process of assets, considering agents to embed distributed intelligence and collaborative functions, service orientation to support interoperability, and holonic principles to provide the system organization, is presented.
Abstract: Modern manufacturing systems are facing new challenges related to the fast-changing market conditions, increased global competition and rapid technological developments, imposing strong requirements in terms of flexibility, robustness and reconfigurability. In this context, the Industry 4.0 (I4.0) paradigm relies on digitizing industrial assets to fulfil these requirements. The implementation of this digitization process is being promoted by the so-called Asset Administration Shell (AAS), a digital representation of an asset that complies with standardization and interoperability strategies. At this moment, a significant part of the AAS developments is more focused on the information management of the asset along its lifecycle and not concerned with aspects of intelligence and collaboration, which are fundamental aspects to develop I4.0 compliant solutions. In this sense, this paper presents an agent-based AAS approach for enhancing the digitization process of assets, considering agents to embed distributed intelligence and collaborative functions, service orientation to support interoperability, and holonic principles to provide the system organization. The proposed agent-based AAS was implemented in an industrial automation system aiming to analyze its applicability.

Journal ArticleDOI
TL;DR: In this paper , the authors proposed a wide area damping controller (WADC) design method based on an optimization problem to ensure the resilience of WADC to permanent loss of communication channels.
Abstract: The use of real-time data from Phasor Measurement Units (PMUs) to compose a Wide-Area Damping Controller (WADC) proved to be effective in damping inter-area power system oscillation modes. However, PMU data is vulnerable to cyber-attacks that can compromise the functioning of the WADC communication channels and the small-signal stability of the closed-loop control system. This article proposes a WADC design method based on an optimization problem to ensure the resilience of WADC to permanent loss of communication channels. The optimization problem is solved using the Crow Search Algorithm. Case studies were done for the IEEE 68-bus system. The results of modal analysis and non-linear simulations in the time domain show the effectiveness of the proposed method.

Journal ArticleDOI
TL;DR: In this paper , the authors address the problem of maximizing the fidelity in a quantum state transformation process satisfying the Liouville-von Neumann equation by introducing fidelity as the performance index, aiming at maximizing the similarity of the final state density operator with the one of the desired target state.
Abstract: High fidelity quantum state transfer is an essential part of quantum information processing. In this regard, we address the problem of maximizing the fidelity in a quantum state transformation process satisfying the Liouville-von Neumann equation. By introducing fidelity as the performance index, we aim at maximizing the similarity of the final state density operator with the one of the desired target state. Optimality conditions in the form of a Maximum Principle of Pontryagin are given for the matrix-valued dynamic control systems propagating the probability density function. These provide a complete set of relations enabling the computation of the optimal control strategy.

Journal ArticleDOI
TL;DR: In this article , the authors explored the use of Machine Learning to extract, through the important features selection, information on which sensors/data - used in a steel industry production line - can be considered principal through data obtained from the integration of real-time monitoring and Digital Twin elaboration.
Abstract: Predictive Maintenance is gathering a lot of interest both from research and industries. The combination of Digital Twin models and Machine Learning provides the mixture of past and featured values for application in the prediction of failures in correlation with production plans. In this work, we explored the use of Machine Learning to extract, through the important features selection, information on which sensors/data - used in a steel industry production line - can be considered “principal” through data obtained from the integration of real-time monitoring and Digital Twin elaboration. The analysis of the data, collected from a period of six months, provided information on anomalies and main signal correlation. The data from Digital Twin and Machine Learning predicted normal and in need of observation states along with the anomalies. Further investigation using Machine Learning, provided the sensors that reported the anomalies and gathered principal components. The sensors’ signal data are currently used for real-time monitoring and Predictive Maintenance plans and integrated in a cloud based platform.

Journal ArticleDOI
TL;DR: In this article , an adaptive controller is designed to meet two controller objectives: (i) regulating the continuous voltage at the end of the HVDC cable; and (ii) ensuring a perfect power quality and system stability, which can be achieved by continuously adjusting the active and reactive powers independently.
Abstract: This paper studies the problem of controlling a long distance transmission system for huge amounts of electrical energy (Generator-Load VSC-HVDC). An adaptive controller is designed to meet two controller objectives: (i) regulating the continuous voltage at the end of the HVDC cable; and (ii) ensuring a perfect power quality and system stability, which can be achieved by continuously adjusting the active and reactive powers independently. The controller's robustness is addressed by considering various parameter uncertainties, such as DC cable parameter variations. Furthermore, since the DC load is usually located at great distances from the control unit, a high gain observer is designed to estimate the DC cable states, as well the current in the load. Thus, the output voltage and current of the VSC are the only accessible measurements. The theoretical analysis results are approved by numerical simulation within MATLAB/SIMULINK environment.

Journal ArticleDOI
TL;DR: In this paper , the authors consider the problem of minimizing the entropy, energy, or exergy production for state transitions of irreversible port-Hamiltonian systems subject to control constraints and show that optimal solutions exhibit the manifold turnpike phenomenon with respect to the manifold of thermodynamic equilibria.
Abstract: We consider the problem of minimizing the entropy, energy, or exergy production for state transitions of irreversible port-Hamiltonian systems subject to control constraints. Via a dissipativity-based analysis we show that optimal solutions exhibit the manifold turnpike phenomenon with respect to the manifold of thermodynamic equilibria. We illustrate our analytical findings via numerical results for a heat exchanger.

Journal ArticleDOI
TL;DR: In this article , the FMEA-linked-to-PPR asset issue analysis (FPI) model is introduced to guide quality issue analyses. But the model is not suitable for the analysis of large-scale data sets.
Abstract: The diffusion of the Industry 4.0 paradigm has led to a proliferation of data that is generated by production assets on the shop floor. This data opens up new opportunities for the analysis of quality issues, but it also makes identifying, selecting, and correctly interpreting data all the more critical. This involves a multitude of domain experts that design, operate and maintain production equipment. Major challenges they face in this context are (i) to map and integrate their domain knowledge on potential failure modes and effects, products, processes and production assets; and (ii) to coordinate their actions to systematically investigate and address the most important issues first. To address these challenges, this paper introduces the FMEA-linked-to-PPR Asset Issue Analysis (FPI) Model, a multi-view coordination asset, to guide quality issue analyses. The model integrates cross-domain knowledge and facilitates tracking the investigation state of quality analyses in teams of domain experts. A preliminary evaluation on a real-world use case indicates the FPI model to facilitate effective cross-domain analytic processes and the efficient identification of potential causes for quality issues.

Journal ArticleDOI
TL;DR: In this article , the authors investigated the current state of the art in DT and its application as a tool to evaluate and integrate ergonomic aspects, or additional human factors, in M&L systems.
Abstract: Today, Digital Twin (DT) represents an emerging topic in Manufacturing and Logistics (M&L) systems due to its role as an enabler of digital transformation in the so-called Smart Factories. It has been widely integrated into maintenance, production planning, and control or layout planning decisions. Several frameworks and surveys have been proposed to provide guidelines, managerial insights, limitations, and future research perspectives on this emerging topic. However, just a few works focus the attention on DT and its role in quantifying, evaluating, and providing ergonomics, mental or physical workload, posture feedback, or warnings to workers, aiming to improve their safety conditions. For this reason, this study investigates the current state of the art in DT and its application as a tool to evaluate and integrate ergonomic aspects, or additional human factors, in M&L systems. Furthermore, future research directions are provided.

Journal ArticleDOI
TL;DR: In this paper , the authors discuss the importance of using appropriate stopping criteria and analyse the behaviour of a novel criterion based on the evolution of optimality criteria in active graph-SLAM.
Abstract: Autonomous robotic exploration has long attracted the attention of the robotics community and is a topic of high relevance. Deploying such systems in the real world, however, is still far from being a reality. In part, it can be attributed to the fact that most research is directed towards improving existing algorithms and testing novel formulations in simulation environments rather than addressing practical issues of real-world scenarios. This is the case of the fundamental problem of autonomously deciding when exploration has to be terminated or changed (stopping criteria), which has not received any attention recently. In this paper, we discuss the importance of using appropriate stopping criteria and analyse the behaviour of a novel criterion based on the evolution of optimality criteria in active graph-SLAM.

Journal ArticleDOI
TL;DR: In this article , the authors proposed a predictive control framework that employs a recursive least squares algorithm to approximate in real time the driving behavior of the preceding human-driven vehicles and then uses this approximation to derive safety-aware trajectory in a finite horizon.
Abstract: A typical urban signalized intersection poses significant modeling and control challenges in a mixed traffic environment consisting of connected automated vehicles (CAVs) and human-driven vehicles (HDVs). In this paper, we address the problem of deriving safe trajectories for CAVs in a mixed traffic environment that prioritizes rear-end collision avoidance when the preceding HDVs approach the yellow and red signal phases of the intersection. We present a predictive control framework that employs a recursive least squares algorithm to approximate in real time the driving behavior of the preceding HDVs and then uses this approximation to derive safety-aware trajectory in a finite horizon. We validate the effectiveness of our proposed framework through numerical simulation and analyze the robustness of the control framework.

Journal ArticleDOI
TL;DR: In this paper , the authors identify the barriers of I4.0 technologies implementation in maintenance and classify them into five main groups such as strategy and organization, resources, technology and infrastructure, and security and confidentiality.
Abstract: The purpose of this paper is to identify the barriers of I4.0 technologies implementation in maintenance. Based on literature analysis twenty two barriers of I4.0 technologies implementation are determined and classified into five main groups such as “Strategy and Organization”; “Maintenance staff knowledge and training”; “Resources”; “Technology and infrastructure” and “Security and confidentiality”. Experts’ opinions were taken to finalize the identified barriers. The data for the study were collected from academia experts and have been further analyzed. The results show that from twenty two identified I4.0 technologies implementation barriers only nine are the most representative ones.

Journal ArticleDOI
TL;DR: In this paper , a modular architecture approach for the design of cyber-physical steel production processes is presented, which is tested within a production facility for long products such as rails or tubes taking into account the main peculiarities of the sector.
Abstract: The new generation of steelworks shaped by Industry 4.0 are digitized, networked, flexible and adaptable. Production processes use distributed information and communication structures, are more autonomous and capable to react to dynamic evolutions of the environment. Cyber-physical systems are a fundamental component of Industry 4.0 and enable new generation of smart processes. This paper presents a modular architecture approach for the design of cyber-physical steel production processes. The approach is tested within a production facility for long products such as rails or tubes taking into account the main peculiarities of the sector. The use of an industrial-agent-based solution for enabling intelligent capabilities and interactions among cyber-physical modules is investigated and adopted. Experimental results highlight the industrial applicability of the adopted implementation scheme combining agent-based technology with the proper connection between models, communication and optimisation methods.

Journal ArticleDOI
TL;DR: In this article , an end-to-end conceptual framework for addressing the key barriers and opportunities for digitalisation in SME manufacturers is proposed. But this framework has not been used to guide the developments in the Digital Manufacturing on a Shoestring (DMOS) project.
Abstract: This paper is concerned with examining and prioritising the specific requirements SME manufacturers have for digital solutions and approaches for developing such solutions based on low-cost technologies and processes. In particular, this paper proposes an end-to-end conceptual framework for addressing the key barriers and opportunities for digitalisation in SME manufacturers. It then shows how this framework has been used to guide the developments in the Digital Manufacturing on a Shoestring programme - an ongoing UK-based research programme developing low-cost digital solutions for SMEs. The framework is intended to provide a reference point in the areas of low-cost digital and automated solutions - which has had surprisingly limited focus to date and also provide support for academic developments targeted at supporting the digital needs of manufacturing SMEs and suggests an application opportunity for modular and reconfigurable systems architectures. The so-called digital Shoestring approach exploits the fact that many low-cost digital devices and software being developed in the non-industrial domain (e.g. sensors, wifi cameras, game controllers) may well have direct industrial applicability. The novelty of this work lies in the recognition that a low-cost pathway to helping SME manufacturers address digitalisation may address an outstanding industrial need and that the use of non-industrial digital technologies and methods may provide advantages.

Journal ArticleDOI
TL;DR: In this paper , a robust quaternion constrained attitude control law for rigid bodies is presented, which is formulated using the backstepping philosophy, and Barrier Lyapunov Functions (BLFs) are used to prevent attitude constraint violation.
Abstract: A novel, robust quaternion constrained attitude control law for rigid bodies is presented in this paper. The controller is formulated using the backstepping philosophy, and Barrier Lyapunov Functions (BLFs) are used to prevent attitude constraint violation. This is done by ensuring the boundedness of BLFs in the closed-loop Lyapunov stability analysis. The analogy between a standard Quadratic Lyapunov Function based attitude control law and the BLF based control law is highlighted, and a systematic procedure to select control constants is detailed. Finally, the BLF based control law is verified by carrying out numerical simulations of the rigid body in the presence of initial attitude errors and bounded disturbance torques. In the first case, the attitude errors are asymptotically driven to zero while strictly satisfying the quaternion constraints. In the presence of bounded disturbance torques, the attitude errors remain bounded within the constraint boundary.

Journal ArticleDOI
TL;DR: In this paper , a distributed model predictive control (DMPC) is proposed to offload path planning computations to multiple ground-based computation units to save 60% of network traffic and required computational power.
Abstract: Distributed model predictive control (DMPC) is often used to tackle path planning for unmanned aerial vehicle (UAV) swarms. However, it requires considerable computations on-board the UAV, leading to increased weight and power consumption. In this work, we propose to offload path planning computations to multiple ground-based computation units. As simultaneously communicating and recomputing all trajectories is not feasible for a large swarm with tight timing requirements, we develop a novel event-triggered DMPC that selects a subset of most relevant UAV trajectories to be replanned. The resulting architecture reduces UAV weight and power consumption, while the active redundancy provides robustness against computation unit failures. Moreover, the DMPC guarantees feasible and collision-free trajectories for UAVs with linear dynamics. In simulations, we demonstrate that our method can reliably plan trajectories, while saving 60% of network traffic and required computational power. Hardware-in-the-loop experiments show that it is suitable to control real quadcopter swarms.