In this paper, the output synchronization in large-scale discrete-time networks is examined by utilizing the novel phase tool, where the agent dynamics are allowed to be significantly heterogeneous. The synchronizatio...
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ISBN:
(数字)9783907144107
ISBN:
(纸本)9798331540920
In this paper, the output synchronization in large-scale discrete-time networks is examined by utilizing the novel phase tool, where the agent dynamics are allowed to be significantly heterogeneous. The synchronization synthesis problem is formulated and thoroughly investigated, with the goal of characterizing the allowable heterogeneity among the agents to ensure synchronization under a uniform controller. The solvability condition is provided in terms of the phases of the residue matrices of the agents at the persistent modes. When the condition is satisfied, a design procedure is given, producing a low-gain synchronizing controller. Numerical examples are given to illustrate the results.
Plants sequester carbon through photosynthesis and provide primary productivity for the ecosystem. However, they also simultaneously consume water through transpiration, leading to a carbon-water balance relationship....
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Plants sequester carbon through photosynthesis and provide primary productivity for the ecosystem. However, they also simultaneously consume water through transpiration, leading to a carbon-water balance relationship. Agricultural production can be regarded as a form of carbon sequestration *** the perspective of the natural-social-economic complex ecosystem, excessive water usage in food production will aggravate regional water pressure for both domestic and industrial purposes. Hence, achieving a harmonious equilibrium between carbon and water resources during the food production process is a key scientific challenge for ensuring food security and sustainability. Digital intelligence(DI) and cyber-physical-social systems(CPSS) are emerging as the new research paradigms that are causing a substantial shift in the conventional thinking and methodologies across various scientific fields, including ecological science and sustainability studies. This paper outlines our recent efforts in using advanced technologies such as big data, artificial intelligence(AI), digital twins, metaverses, and parallel intelligence to model, analyze, and manage the intricate dynamics and equilibrium among plants, carbon, and water in arid and semiarid ecosystems. It introduces the concept of the carbon-water balance and explores its management at three levels: the individual plant level, the community level, and the natural-social-economic complex ecosystem level. Additionally, we elucidate the significance of agricultural foundation models as fundamental technologies within this context. A case analysis of water usage shows that, given the limited availability of water resources in the context of the carbon-water balance, regional collaboration and optimized allocation have the potential to enhance the utilization efficiency of water resources in the river basin. A suggested approach is to consider the river basin as a unified entity and coordinate the relationship between the
The article puts focus on the the problem of performance assessment for UAV formation with leader-following structure and switching communication topology in the presence of unknown exogenous perturbations. First, two...
The article puts focus on the the problem of performance assessment for UAV formation with leader-following structure and switching communication topology in the presence of unknown exogenous perturbations. First, two time-varying indicators are devised on the basis of the regulated outputs of the followers. Then, a trainable performance assessment model is constructed by means of belief rule base expert system (BRB) with the two time-varying indicators as the inputs and the assessment utility as the final output. At last, relevant simulation experiments are conducted to validate the practicability of the established performance assessment model for leader-following UAV formation subject to switching communication topology and unknown external perturbations.
As the largest class of small non-coding RNAs, piRNAs primarily present in the reproductive cells of mammals, which influence post-transcriptional processes of mRNAs in multiple ways. Effective methods for predicting ...
As the largest class of small non-coding RNAs, piRNAs primarily present in the reproductive cells of mammals, which influence post-transcriptional processes of mRNAs in multiple ways. Effective methods for predicting piRNA and mRNA target relationships can help identify piRNA functions, investigate the possibility of piRNAs as biomarkers and therapeutic targets. In this study, we propose a computational approach for classifying the relationships of piRNA-mRNA pairs based on an interactive inference network (IIN). First, we gather piRNA-mRNA target data, collect sequence data by position alignment, and construct a benchmark dataset. Furthermore, a reliable negative set is constructed by positive-unlabeled learning. Finally, we view a piRNA and a mRNA sequence as a premise and hypothesis sentence, respectively, and IIN model is used to predict the relationship between them. The experiments demonstrate that our method effectively characterizes piRNA-mRNA interaction and could be beneficial for researchers to investigate piRNA functions.
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.
For the containment control problem of autonomous surface vehicles with external disturbances, a novel non-singular fixed-time control scheme is developed, where the multi-ship system consists of real leaders and foll...
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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.
Global Navigation Satellite systems (GNSS) can provide real-time positioning information for outdoor users, but cannot for indoor scenarios or heavily occluded outdoor scenarios. Strap-down Inertial Navigation system ...
Global Navigation Satellite systems (GNSS) can provide real-time positioning information for outdoor users, but cannot for indoor scenarios or heavily occluded outdoor scenarios. Strap-down Inertial Navigation system (SINS) are widely used to locate people in complex interior or heavily occluded outdoor scenarios due to its light weight and low power consumption. However, IMU of SINS are noisy, and the sampling data error is large, which is a divergence of the error with time. Therefore, it will generate a positioning accumulation error, which affects the final positioning accuracy. The problem of cumulative IMU errors is usually dealt with by Zero-Velocity Update (ZUPT). The zero-velocity detection part of basic ZUPT method usually uses a single threshold to determine the gait of pedestrian, which often has the problem of gait misjudgment and omission. To address these problems, this paper proposes a composite conditional detection method to solve the problem of misjudgment in the zero-velocity interval. In addition, we redesign the zero-velocity update algorithm and uses the Cubature Kalman filter (CKF) for pedestrian positioning error correction. The experimental results demonstrate that the proposed ZUPT method based on dual-threshold detection can better detect the interval between pedestrian motion and stationery than ones with single threshold. The zero-velocity update algorithm based on CKF has higher performance than conventional EKF and UKF methods, which constrains the cumulative error of SINS to about 0.2% of the whole walking distance.
In this paper, the composition and operation mechanism of a multi-aircraft cooperative simulation system is analyzed, with its formal architecture identified as a discrete event system differential equation system spe...
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Dynamic optimization for hypersonic reentry vehicle(HRV) is a challenge for complex nonlinear constraints during a global strike *** to the strong nonlinearity of HRV,it is difficult to guarantee the precision of comp...
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Dynamic optimization for hypersonic reentry vehicle(HRV) is a challenge for complex nonlinear constraints during a global strike *** to the strong nonlinearity of HRV,it is difficult to guarantee the precision of complex constraints on non-collocation points with traditional Gauss pseudospectral method(GPM).A novel approach which provides an optimal control strategy considering the above challenges is then ***,an adaptive mesh refinement strategy based on curvature information is presented to improve the accuracy of GPM.A collocation point redistribution method based on error analysis is then proposed to further improve the accuracy of the ***,a detection mechanism is proposed to correct the results on-line when the path constraint is not *** proposed approaches are finally applied to a classic HRV problem and compared with other literature work in *** research results validate the effectiveness of the proposed methods.
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