Marine sciences require the use of Autonomous Underwater Vehicles (AUV) for their missions in order to perform unmanned duties like deep-sea explorations. AUV require to reject turbulence disturbances while regulating...
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ISBN:
(纸本)9781728173818;9781728173801
Marine sciences require the use of Autonomous Underwater Vehicles (AUV) for their missions in order to perform unmanned duties like deep-sea explorations. AUV require to reject turbulence disturbances while regulating their trajectory. In this paper, a position controller applying the Generalized Proportional Integral (GPI) observer to an Autonomous Underwater Vehicle (AUV) in order to maintain the desired trajectory and reject the environment perturbations is given. the mathematical model and the performance of the GPI shows a precise and fast tracking control through simulations.
the problems of water quality sensors and actuators placement in drinking water distribution systems (DWDSs) are addressed as separate, primarily. However, against the background of control systems theory, the nature ...
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ISBN:
(纸本)9781728173818;9781728173801
the problems of water quality sensors and actuators placement in drinking water distribution systems (DWDSs) are addressed as separate, primarily. However, against the background of control systems theory, the nature of DWDSs dynamics indicates that these both problems are interdependent and impact the design of related water quality monitoring and control structures and algorithms. the research work presented in this paper is to investigate the state-of-the-art in this field and discuss the problems of water quality sensors and actuators placement within DWDS and to highlight the potential benefits of considering the joint task of their allocation.
Efficient maintenance of industrial equipment requires degradation monitoring and prediction. Currently used prediction models are mostly deterministic and cannot consider uncertainty inherent to degradation measureme...
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ISBN:
(纸本)9781728173818;9781728173801
Efficient maintenance of industrial equipment requires degradation monitoring and prediction. Currently used prediction models are mostly deterministic and cannot consider uncertainty inherent to degradation measurements. In this paper we propose using time series models obtained using Facebook Prophet algorithm to predict the evolution of degradation of turbomachinery. We Illustrate our considerations with data from large scale industrial centrifugal compressors. Our predictions are promising and confidence intervals cover the predictions well.
the paper describes an aggregate cloud-based digital twin (DT) that models an industrial robot by virtualizing its physical structure, motion and action control, operating modes, parameters and interactions with shop ...
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In collaboration with our industrial partners at Autocam [1], we developed this Deep Learning (DL) based assistance system for robotic welding. the system is tailored to address the challenges encountered in real-worl...
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ISBN:
(纸本)9798350372694;9798350372700
In collaboration with our industrial partners at Autocam [1], we developed this Deep Learning (DL) based assistance system for robotic welding. the system is tailored to address the challenges encountered in real-world industrial settings, where conventional programming methods face limitations, particularly in constrained spaces. Autocam provided us with authentic industrial datasets and 3D models. Our approach focuses on automating the identification of collision-free torch poses, crucial for navigating intricate environments commonly encountered in industrial robotic operations. To capture the intricacies of these environments, we utilize four virtual cameras, each strategically positioned to provide a unique perspective. this multi-perspective observation facilitates the development of a robust relationship between 3D space and collision dynamics. the DL model is trained using a combination of Imitation Learning and Deep Reinforcement Learning (DRL). this training process not only empowers the agent to autonomously learn collision-free poses but also allows for the assimilation of existing solutions derived from real-world industrial scenarios. By leveraging computer vision and combining the strengths of both imitation learning and DRL, our model aspires to offer a more adaptive and efficient solution for automation in challenging spatial configurations within industrial robotic operations.
Industrial anomaly detection plays a crucial role in modern manufacturing and production processes. In order to help researchers and professionals in the manufacturing industry understand the developing research resul...
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the problem of PID type controller tuning has been addressed in this paper. In particular, a method of selection of PD settings based on the solution of linear-quadratic optimisation problem using the energy criterion...
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ISBN:
(纸本)9781728173818;9781728173801
the problem of PID type controller tuning has been addressed in this paper. In particular, a method of selection of PD settings based on the solution of linear-quadratic optimisation problem using the energy criterion has been investigated. thus, the possibility of transforming optimal settings of the linear-quadratic regulator into the settings of the controller in the classical control system has been given. the presented methodology has been used during synthesis of control system for a two-wheeled balancing robot. Finally, the performance of the proposed control system has been validated by simulation in Matlab/Simulink environment withthe use of a two-wheeled balancing robot model.
Model Predictive Control (MPC) is an advanced method of process control. Despite its usefulness, it is applied mostly for large industrial processes. In the paper, a model predictive algorithm for a glass forehearth i...
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ISBN:
(纸本)9781728173818;9781728173801
Model Predictive Control (MPC) is an advanced method of process control. Despite its usefulness, it is applied mostly for large industrial processes. In the paper, a model predictive algorithm for a glass forehearth is presented. the problem of molten glass temperature stabilisation under external disturbances is especially important during the glass conditioning, so the use of an adaptive predictive controller seems to be reasonable. the controller tuning utilizes linear models of the process, that can be obtained on-line. Modifications of the known continuous-time MPC approach are described. the most important difference is the original method of measurable disturbances compensation and its implementation in the algorithm. the developed controller was tested using the process model with distributed parameters (Partial Differential Equation). the experimental results are presented in the paper.
automation in Electric Vehicle (EV) Li-Ion Battery (LIB) pack disassembly is getting a lot of attraction with increased number of EVs being manufactured. Highly cluttered components placed in complex configurations pr...
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ISBN:
(纸本)9798350315684
automation in Electric Vehicle (EV) Li-Ion Battery (LIB) pack disassembly is getting a lot of attraction with increased number of EVs being manufactured. Highly cluttered components placed in complex configurations present a unique challenge for object detection models. To get maximum coverage of the components in the EV battery pack, images from multiple viewpoints are considered and merged using Multiple-View Super Resolution (MVSR). the proposed method provides 7% higher accuracy in the screw detection task than the statistical methods previously derived [1].
Waste disposal into water bodies is a serious concern for environmental engineers, often resulting in urban flooding, soil degradation in agricultural areas, and freshwater pollution. Additionally, trash accumulation ...
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