The growing interest in arm robotics is driven by the need to facilitate complex and repetitive jobs for humans, as well as by the advancement of production. There is a need for optimal control techniques for better c...
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The aim of to minimize the time utilized for the developing the aircraft enables the collaborative foundation for the integrated design of aircraft. The work presented in this paper is a simulated work in Simulink whi...
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In industrial systems, automated electric drives are subjected to various internal disturbances as well as external disturbances. These disturbing influences do not allow to provide appropriate control accuracy and ne...
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Today, pulse radar has been widely used in society. Pulse radar transmitter is one of the important components of pulse radar. The normal or not of the transmitter directly affects the performance and safety of the pu...
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The integration of multi-agent deep reinforcement learning (MADRL) in adaptive and intelligent home energy management systems (AI-HEMS) enhances real-time energy management by enabling intelligent decision-making amon...
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ISBN:
(纸本)9798350361261;9798350361278
The integration of multi-agent deep reinforcement learning (MADRL) in adaptive and intelligent home energy management systems (AI-HEMS) enhances real-time energy management by enabling intelligent decision-making among multiple agents to optimize various problems. This approach allows smart homes to dynamically respond to changes in energy demand, pricing, and user preferences. The integration of Internet of Things (IoT) devices with AI-HEMS has been promoted to efficiently manage energy resources and maintain occupants' comfort, where IoT devices collect data on energy consumption, usage patterns, and environmental conditions. However, ensuring trade-offs between conflicting optimization objectives, such as reducing energy consumption and electricity prices, and maximizing users' comfort levels is challenging. In this paper, we propose a MADRL-based multi-objective demand response (MODR) optimization framework to efficiently manage and control the energy consumption of smart homes. The proposed approach aims to simultaneously reduce energy costs and maximize users' comfort, improving the overall reliability of energy systems. We first formulate the MODR optimization problem as MDP and then adopt the MADRL algorithm to solve it. The simulation results demonstrate that our proposed DR optimization approach can effectively balance the trade-off between energy cost and user comfort levels, resulting in improved energy efficiency compared to benchmark approaches.
This research paper proposes a curriculum for a five-year academic program with a bachelor's degree (honors) in intelligentsystems engineering and software engineering and a master's degree in intelligent sys...
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ISBN:
(纸本)9798350361513;9798350372304
This research paper proposes a curriculum for a five-year academic program with a bachelor's degree (honors) in intelligentsystems engineering and software engineering and a master's degree in intelligentsystems engineering and software engineering. This program includes courses in data structures, compiler design, operating system design, firmware design, database systems, computer graphics and virtual reality design, static and dynamic website design, development of chatbots and voice assistants, software engineering methodology, knowledge-based systems, fuzzy logic, neural networks, evolutionary computation, evolutionary multiojective optimization, machine learning, image processing, computer vision, pattern recognition, voice recognition, natural language processing, data science, controlsystems, intelligentcontrolsystems, robotics, digital signal processing, mathematics, engineering physics, biology, etc. These degrees will allow graduates to have a good understanding of all of the main branches of intelligentsystems engineering and software engineering as well as other relevant subjects in electrical and computer engineering.
In order to solve the problems of the low sense of participation in the project, inconvenient control of the equipment and complex control process, an intelligent interactive system is designed in this paper. The syst...
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The proceedings contain 99 papers. The topics discussed include: blind synchronization method of OFDM sampling clock timing based on phase difference;research on the configuration method of smart distribution grid tec...
ISBN:
(纸本)9781665428101
The proceedings contain 99 papers. The topics discussed include: blind synchronization method of OFDM sampling clock timing based on phase difference;research on the configuration method of smart distribution grid technology scheme based on target differentiation;research on high-latitude transfer alignment technology;prediction of ecotourism population based on exponential smoothing and ARIMA mixed model;task scheduling considering multiple constraints in mobile edge computing;polarimetric dehazing utilizing Vis-NIR spectral image fusion;an infrared and visible image fusion method based on adaptive weight learning;method for determining power system high fragile target sequence based on community structure;research on PMSM sensorless control based on improved synovial observer algorithm;and benign and malignant classification of pulmonary nodules based on multi-level feature fusion.
The future of productive indoor farming is approaching us, and this paper investigates the synergistic merging of Internet of Things (IoT) technologies with aquaponics and hydroponics. The water-based technologies and...
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This work proposes an optimal control scheme for a trajectory-tracking Automated Guided Vehicle considering motion and collision constraints in a warehouse environment. We outline how the simpler obstacle avoidance co...
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ISBN:
(纸本)9798350377712;9798350377705
This work proposes an optimal control scheme for a trajectory-tracking Automated Guided Vehicle considering motion and collision constraints in a warehouse environment. We outline how the simpler obstacle avoidance constraints in the Cartesian Coordinate Frame (CCF) can be retained, while projecting the tricycle kinematics to the Frenet Coordinate Frame (FCF) for track progress. The Nonlinear Model Predictive control (NMPC) scheme is subsequently implemented using acados and its real-time feasibility is demonstrated in simulation and aboard a test vehicle at a warehouse.
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