To address the failure of precise overload tracking and anti-interference caused by the difficulty of accurate modeling of a complex aircraft, the controller designing method based on deep reinforcement learning is st...
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ISBN:
(数字)9781728159225
ISBN:
(纸本)9781728159232
To address the failure of precise overload tracking and anti-interference caused by the difficulty of accurate modeling of a complex aircraft, the controller designing method based on deep reinforcement learning is studied. This paper trained the control network based on the Proximal Policy Optimization (PPO), studied the tracking control problem of the aircraft, and accurately tracked the typical command signals. Fixed-point simulation of the aircraft is performed, with results showing that, in presence of aircraft model parameter variation and external disturbance, the controller based on deep reinforcement learning can achieve accurate tracking of overload commands.
Air combat decision-making is a critical issue in Unmanned Air Vehicle automatic combat. Precise and efficient maneuvering strategies are extremely important for the final victory. Quantitative research has been condu...
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ISBN:
(数字)9781728180250
ISBN:
(纸本)9781728180267
Air combat decision-making is a critical issue in Unmanned Air Vehicle automatic combat. Precise and efficient maneuvering strategies are extremely important for the final victory. Quantitative research has been conducted on the maneuver strategy. In this study, a knowledge-based maneuver action library for air combat was established by the Rough Set Theory, which can help quick response to the battlefield situation. Since not all influence factors of battlefield situation are that significant and the computing source is finite, the rough set model was simplified to increase reaction rate. This paper introduced an advanced genetic algorithm to reduce the attributes of rough sets, taking the purity of each attribute into account, so as to make the condition attribute as close to 1 or 0 as possible. As a result, the reducing accuracy of the whole decision-making system is improved. The simulation results show that the rough set model built in this paper is efficient, feasible and reasonable, and the algorithm can support the air combat maneuver strategy decision system.
In public roads, autonomous vehicles (AVs) face the challenge of frequent interactions with human-driven vehicles (HDVs), which render uncertain driving behavior due to varying social characteristics among humans. To ...
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Dear editor,Generally, one of the most prominent features of modern industrial systems is the massive amount of data collected from various sensors, which poses great challenges to traditional methods of captur-
Dear editor,Generally, one of the most prominent features of modern industrial systems is the massive amount of data collected from various sensors, which poses great challenges to traditional methods of captur-
A single unit (head) is the conventional input feature extractor in deep learning architectures trained on multivariate time series signals. The importance of the fixed-dimensional vector representation generated by t...
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Cyber-Physical-Social systems bridge the gap between social resource organization and distribution, and give birth to Society 5.0, which represents a transformative vision aimed at realizing the human-centric paradigm...
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Cyber-Physical-Social systems bridge the gap between social resource organization and distribution, and give birth to Society 5.0, which represents a transformative vision aimed at realizing the human-centric paradigm for more efficient and effective sustainable development. In this paper, we discuss the decentralized paradigm in fostering human needs-driven smart services, in line with Maslow’s hierarchy of needs theory. Societies 5.0 is committed to optimizing the use of natural, artificial, and social resources by enhancing democratic participation and ensuring that decision-making processes are more transparent, reliable, and aligned with the needs of the populace in sustainable ways. Moreover, our discussion extends to how Society 5.0’s principles correlate with the United Nations Sustainable Development Goals (SDGs), providing a framework that supports health, education, and poverty reduction, among other targets. This approach also aligns with the Human Development Index (HDI), reinforcing the notion that technological progress in Society 5.0 does not overshadow but rather complements and enhances human values, paving a synergistic path towards sustainable development that is both advanced and fundamentally human-centric.
The availability of network communication services is an important evaluation standard to measure the ability of the network to meet the user’s business *** current related research mostly focuses on the evaluation o...
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The availability of network communication services is an important evaluation standard to measure the ability of the network to meet the user’s business *** current related research mostly focuses on the evaluation of network reliability,which cannot reflect the logical relationship between failure/maintenance and network performance *** Ad Hoc Network is a multi-hop,centerless and energy-constrained distributed *** to the dynamic change of communication environment and the instability of wireless link,Ad Hoc Network is facing great challenges in service avail*** this thesis,a fault-based quantitative evaluation model of traffic availability in Ad Hoc networks is *** studying the multi-state Markov fault model of communication networks and the performance analysis of delay index based on CSMA\CA protocol,the quantitative evaluation of traffic availability in Ad Hoc networks is *** the availability of tactical unit network under different typical network configuration conditions is analyzed through experiments.
A simulation model of a simple supply chain consisting of a single distribution center and several points of sale was created. Initially, a new model was created with the name "Suplly Chain" and watches as u...
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A simulation model of a simple supply chain consisting of a single distribution center and several points of sale was created. Initially, a new model was created with the name "Suplly Chain" and watches as units of model time. Next, a GIS (geographic information system) map was added to the diagram of the main object using the standard display settings. The distributor properties were defined and it marked the distribution point on the map. Next, retailers were added to the map: using the OpenStreetMap online server, to which AnyLogic sends addresses and receives coordinates and automatically arranges retailers. Manually added the properties of retailers. The next step was to create a model of trucks and their movement logic is set. To do this, a state diagram was used, with the help of which a diagram of the state of the logic of trucks was obtained. Using the New Agent Wizard, add a new agent type – order. It also changed the status chart to display order information. The created model was supplemented, where time was added for unloading and loading trucks from retailers. A basic simulation model of supply chains was built, and ideas for improving this model were considered.
The fixed-wing UAV is a non-linear and strongly coupled system. controlling UAV attitude stability is the basis for ensuring flight safety and performing tasks successfully. The non-linear characteristic of the UAV is...
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ISBN:
(数字)9781728180250
ISBN:
(纸本)9781728180267
The fixed-wing UAV is a non-linear and strongly coupled system. controlling UAV attitude stability is the basis for ensuring flight safety and performing tasks successfully. The non-linear characteristic of the UAV is the main reason for the difficulty of attitude stabilization. Deep reinforcement learning for the UAV attitude control is a new method to design controller. The algorithm learns the nonlinear characteristics of the system from the training data. Due to the good performance, the PPO algorithm is the mainly algorithm of reinforcement learning. The PPO algorithm interacts with the reinforcement learning training environment by gazebo, and improve attitude controller, different from the traditional PID control method, the attitude controller based on deep reinforcement learning uses the neural network to generate control signals and controls the rotation of rudder directly.
From the perspective of military demand for swarm fight, it is point out that the cooperative guidance technology of multiple aerial vehicles based on spatiotemporal coordination is a key technology to effectively imp...
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ISBN:
(数字)9781728180250
ISBN:
(纸本)9781728180267
From the perspective of military demand for swarm fight, it is point out that the cooperative guidance technology of multiple aerial vehicles based on spatiotemporal coordination is a key technology to effectively improve penetration probability and combat effectiveness. Then, in view of the development status of cooperative guidance technology for multiple aerial vehicles, it introduces thoughts on technology development at home and abroad based on time coordination, space coordination and spatiotemporal coordination, perspectively. Finally, the cooperative guidance technology of multiple aerial vehicles is summarized, and the future development direction is prospected.
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