The Internet of Things (IoT) is the cutting edge of computing technology that connects things and integrate them into large ecosystem. Recently, the Edge computing architecture is driving the rapid development of the ...
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The use of impedance control has become widespread in applications requiring simultaneous position tracking and compliance in contact. However, disturbances such as friction and model uncertainties can adversely affec...
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ISBN:
(纸本)9781665491907
The use of impedance control has become widespread in applications requiring simultaneous position tracking and compliance in contact. However, disturbances such as friction and model uncertainties can adversely affect the performance of impedance-based motion control. The disturbance observer (DOB) has been proposed to address this issue, which is a widely-utilized robust controller that eliminates observed disturbances with the nominal model. However, current DOB applications fail to consider the aspect of interactive force control properly. This study proposes a novel Workspace Force/Acceleration Disturbance Observer (WFADOB) controller, which utilizes both interaction force and acceleration to design a disturbance observer loop, enabling precise motion tracking even with low-impedance gain settings. Additionally, the proposed controller offers fine impedance rendering performance, offering safe contact while maintaining low impedance. This paper discusses the problem of motion tracking performance due to friction and the interaction force that arises during contact. The proposed controller is theoretically analyzed and experimentally verified, demonstrating its performance compared to conventional methods.
The world is currently experiencing an unseen increase in the number of vehicles on the road, and our traffic controlsystems have been struggling to keep up with this rapid growth. This research paper is dedicated to...
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As the adoption of Unmanned Aerial Vehicles (UAVs) increases in the industrial sector, the limitations of traditional multirotors have become more noticeable. Though widely employed, conventional multirotors are under...
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ISBN:
(纸本)9798350355376;9798350355369
As the adoption of Unmanned Aerial Vehicles (UAVs) increases in the industrial sector, the limitations of traditional multirotors have become more noticeable. Though widely employed, conventional multirotors are under-actuated, which restricts the types and quality of manipulation task they can perform. Fully-actuated systems on the other hand, offer an interesting alternative solution with their decoupled forces. However, their widespread use is hindered by complexities in their control and design. Our proposed approach addresses this challenge by introducing multirotors equipped with horizontal thrusters, aiming to find a balance between simplicity and advanced control. These vehicles strategically incorporate additional thrust components tailored to specific tasks, thereby extending the capabilities of traditional under-actuated multirotors. We developed a control algorithm using the PX4 Autopilot to accommodate various flight modes, encompassing directional thrust flight and planar flight. To evaluate our system, we conducted simulations and tested vehicles with different actuator configurations. These simulations were then validated through real-world experiments using a UAV equipped with thrusters and a flight controller running a modified firmware with our control framework. This comprehensive approach allowed us to assess the system's performance in both simulated and practical scenarios.
This paper proposes a reinforcement learning-based collaborative multi-agent actor and critic scheme (RL-CMAS) under edge computing architecture for emergency vehicle preemption. The RL-CMAS deployed a parallel traini...
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This paper proposes a reinforcement learning-based collaborative multi-agent actor and critic scheme (RL-CMAS) under edge computing architecture for emergency vehicle preemption. The RL-CMAS deployed a parallel training process at the cloud side for building knowledge and well accelerating learning. Priority of message and model of message offloading strategy have been developed. The simulation results show that the proposed RL-CMAS is efficient in detecting even complex data. Finally, a comparison was made with other benchmark methods, namely, Regular scheduling algorithm, Alameddine's DTOS algorithm, and independent multi-agent actor-critic. The result showed the proposed method outperforming the other three bench marking methods. The proposed RL-CMAS provides reduction in message processing delay, total delay, and an increase of message delivery success ratio of 14.22%, 18.21%, and 8.86% respectively.
The proceedings contain 298 papers. The topics discussed include: design and implementation of artificial intelligence-driven network intrusion detection system;comparative study of intelligent algorithms in fault dia...
ISBN:
(纸本)9798331529246
The proceedings contain 298 papers. The topics discussed include: design and implementation of artificial intelligence-driven network intrusion detection system;comparative study of intelligent algorithms in fault diagnosis of aviation mechanical systems;design and implementation of network intrusion detection system based on machine learning;evaluation of teaching quality in higher mathematics courses based on artificial neural networks;research on mechanical automation control based on bidirectional long short-term memory;intelligent mapping technology for single line diagram and layered diagram of intelligent distribution network;a comprehensive analysis of knowledge graph-based social recommendation system;and networks assessment of regional economic development level prediction with deep graph convolutional network.
The automation of key processes in metal cutting would substantially benefit many industries such as manufacturing and metal recycling. We present a vision-based control scheme for automated metal cutting with oxy-fue...
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ISBN:
(纸本)9781665491907
The automation of key processes in metal cutting would substantially benefit many industries such as manufacturing and metal recycling. We present a vision-based control scheme for automated metal cutting with oxy-fuel torches, an established cutting medium in industry. The system consists of a robot equipped with a cutting torch and an eye-in-hand camera observing the scene behind a tinted visor. We develop a vision-based control algorithm to servo the torch's motion by visually observing its effects on the metal surface. As such, the vision system processes the metal surface's heat pool and computes its associated features, specifically pool convexity and intensity, which are then used for control. The operating conditions of the control problem are defined within which the stability is proven. In addition, metal cutting experiments are performed using a physical 1-DOF robot and oxy-fuel cutting equipment. Our results demonstrate the successful cutting of metal plates across three different plate thicknesses, relying purely on visual information without a priori knowledge of the thicknesses.
In recent years, cloud computing has become the buzzword in a lot of industries including healthcare. Cloud computing can be simplified as a computation infrastructure that can be accessed on-demand with high availabi...
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The proceedings contain 56 papers. The topics discussed include: contrastive learning regularization method for information extraction of floating raft aquaculture;fractional-order adaptive sliding mode projective syn...
ISBN:
(纸本)9798331516147
The proceedings contain 56 papers. The topics discussed include: contrastive learning regularization method for information extraction of floating raft aquaculture;fractional-order adaptive sliding mode projective synchronization of different hyperjerk systems;intelligent supplier evaluation and selection module for fast-moving consumer goods;filtered sliding mode tracking controller for robot joint using linear matrix inequalities design;optimization algorithm for global k-means algorithm;enhancing product bundling with large language models;hyperspectral image analysis using maximum abundance classification;invariant set analysis and control synthesis of multi-equilibrium switched systems under control constraints;and a framework for solving quadratic knapsack problem based on deep reinforcement learning.
In order to further strengthen the power supply guarantee ability of cogeneration units, this paper designs energy storage power generation-heat supply system. The thermodynamic system, the storage device for steam he...
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