Leighton Chajnantor Telescope(LCT), i.e., the former Caltech Submillimeter Observatory telescope, will be refurbished at the new site in Chajnantor Plateau, Chile in 2023. The environment of LCT will change significan...
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Leighton Chajnantor Telescope(LCT), i.e., the former Caltech Submillimeter Observatory telescope, will be refurbished at the new site in Chajnantor Plateau, Chile in 2023. The environment of LCT will change significantly after its relocation, and the telescope will be exposed to large wind disturbances directly because its enclosure will be completely open during observation. The wind disturbance is expected to be a challenge for LCT's pointing control since the existing control method cannot reject this disturbance very well. Therefore, it is very necessary to develop a new pointing control method with good capability of disturbance rejection. In this research, a disturbance observer—based composite position controller(DOB-CPC) is designed, in which an H∞feedback controller is employed to compress the disturbance, and a feedforward linear quadratic regulator is employed to compensate the disturbance precisely based on the estimated disturbance signal. Moreover, a controller switching policy is adopted, which applies the proportional controller to the transient process to achieve a quick response and applies the DOB-CPC to the steady state to achieve a small position error. Numerical experiments are conducted to verify the good performance of the proposed pointing controller(i.e., DOB-CPC) for rejecting the disturbance acting on LCT.
In Off-Policy reinforcement learning (RL), the experience imbalance problem can affect learning performance. The experience imbalance problem refers to the phenomenon that the experiences obtained by the agent during ...
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In this paper, we study a distributed state estimation problem for Markov jump systems (MJS) over sensor networks, in which each sensor node connects with each other through wireless networks with communication delays...
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This paper investigates the problem of traffic signal control in large-scale road networks. A deep reinforcement learning model based on graph meta-learning using local subgraphs is proposed to control the traffic sig...
This paper investigates the problem of traffic signal control in large-scale road networks. A deep reinforcement learning model based on graph meta-learning using local subgraphs is proposed to control the traffic signal. The entire traffic network is represented as a graph by defining traffic lights as nodes and treating connections between intersections as edges. A graph neural network is used to enhance cooperation and communications between agents since information about neighbors is aggregated. To overcome the challenges in large-scale road networks, the proposed model employs a graph neural network on local subgraphs to reduce the difficulty of training in large-scale road networks. The model trained in small-scale traffic networks is transferred to a large-scale traffic network. Agent knowledge acquired from local subgraphs during the training of a small-scale road network confers advantages to the training of large-scale road networks under the resemblance between the structures of local subgraphs in small-and large-scale road networks. Furthermore, meta-learning is used to facilitate the model's rapid adaptability to unseen large-scale road networks. The advantage of the double Q-learning network is taken to reduce overestimation. In experiments, real-world road networks and synthetic road networks comprising more than 1000 intersections are given to evaluate the effectiveness of the proposed model.
The possibility of using artificial intelligence in the task of recognizing objects of interest in medical radiographic images has been studied. To implement computer vision, the YOLOv5 neural network and the use of i...
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Inverse modeling is extensively applied in the design and tuning of microwave filters (MFs). Inverse models (IMs) take the features extracted from the high-dimensional electromagnetic parameters as input. How to make ...
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This paper discusses the data-driven design of linear quadratic regulators,i.e.,to obtain the regulators directly from experimental data without using the models of *** particular,we aim to improve an existing design ...
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This paper discusses the data-driven design of linear quadratic regulators,i.e.,to obtain the regulators directly from experimental data without using the models of *** particular,we aim to improve an existing design method by reducing the amount of the required experimental *** the data amount leads to the cost reduction of experiments and computation for the data-driven *** present a simplified version of the existing method,where parameters yielding the gain of the regulator are estimated from only part of the data required in the existing *** then show that the data amount required in the presented method is less than half of that in the existing method under certain *** addition,assuming the presence of measurement noise,we analyze the relations between the expectations and variances of the estimated parameters and the *** a result,it is shown that using a larger amount of the experimental data might mitigate the effects of the noise on the estimated *** results are verified by numerical examples.
Electrical tree degradation is one of the main causes of insulation failure in high-frequency *** tree degradation is studied on pure epoxy resin(EP)and MgO/EP composites at frequencies ranging from 50 Hz to 130 *** r...
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Electrical tree degradation is one of the main causes of insulation failure in high-frequency *** tree degradation is studied on pure epoxy resin(EP)and MgO/EP composites at frequencies ranging from 50 Hz to 130 *** results show that the tree initiation voltage of EP decreases,while the growth rate and the expansion coefficient increase with ***,the bubble phenomenon at high frequencies in EP composites is *** with trap distribution character-istics within the material,the intrinsic mechanism of epoxy composites to inhibit the growth of the electrical tree at different frequencies is *** can be concluded that more deep traps and blocking effect are introduced by doping nano-MgO into EP bulks,which can improve the electrical tree resistance performance of EP composites in a wide frequency range.
This paper studies a geometric attitude tracking control problem of quadrotor unmanned aerial vehicles (UAVs) with adaptive extended state observers (AESOs). Through coordinate transformation, the error dynamic of AES...
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