This paper is concerned with bearing-based cooperative target entrapping control of multiple uncertain agents with arbitrary maneuvers including shape deformation, rotations, scalings, etc. A leader-follower structure...
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This paper is concerned with bearing-based cooperative target entrapping control of multiple uncertain agents with arbitrary maneuvers including shape deformation, rotations, scalings, etc. A leader-follower structure is used, where the leaders move with the predesigned trajectories, and the followers are steered by an estimation-based control method, integrating a distance estimator using bearing measurements and a stress matrix-based formation controller. The signum functions are used to compensate for the uncertainties so that the agents’ accelerations can be piecewise continuous and bounded to track the desired dynamics. With proper design of the leaders’ trajectories and a geometric configuration, an affine matrix is determined so that the inter-agent relative bearings can be persistently exciting since the bearing rates are related to different weighted combinations of the affine matrix vectors. The asymptotic convergence of the estimation and control error is proved using Filipov properties and cascaded system theories. A sufficient condition for inter-agent collision avoidance is also proposed. Finally, simulation results are given to validate the effectiveness of the method.
A substantial amount of research has shown that most attacks on cyber-physical systems rely on knowledge of system models, where the models can be obtained using identification methods. Hence, achieving unidentifiabil...
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A substantial amount of research has shown that most attacks on cyber-physical systems rely on knowledge of system models, where the models can be obtained using identification methods. Hence, achieving unidentifiability is an attractive way for the security of systems. This paper focuses on the unidentifiability of systems and designs a controller against the attacks relying on identification. The key insight is that we propose a quantitative evaluation to measure the unidentifiability of the system. This evaluation can be taken as a criterion for evaluating the security of the system. Different from the existing research, the evaluation gives the exact number of unidentifiable parameters in the system. Moreover, we give the necessary and sufficient condition for each parameter to be unidentifiable. Finally, we design a controller based on this evaluation to maximize the number of unidentifiable parameters. Simulation demonstrates the effectiveness of our algorithm.
This paper investigates the fault estimation problem for singular fractional-order systems. An H∞ unknown input observer is designed to meet both admissibility and performance conditions. By using the bounded real le...
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We investigate the problem of synthesizing distributionally robust control policies for stochastic systems under safety and reach-avoid specifications. Using a game-theoretical framework, we consider the setting where...
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作者：
Xiang GuDewei LiAoyun MaYaru YuDepartment of Automation
Shanghai Jiao Tong University Key Laboratory of System Control and Information Processing Ministry of Education of China Shanghai Engineering Research Center of Intelligent Control and Management
In the practical application of model predictive control in power electronics, both online computational burden and model accuracy are crucial. This paper presents an explicit model predictive control method based on ...
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ISBN:
(数字)9789887581581
ISBN:
(纸本)9798350366907
In the practical application of model predictive control in power electronics, both online computational burden and model accuracy are crucial. This paper presents an explicit model predictive control method based on input-mapping *** address the issue of parameter drift in the forward DC-DC converter system, the input-mapping method is introduced to compensate for model deviations using historical data. Firstly, the average model of the forward DC-DC converter system is introduced. For the control objective of voltage tracking, an explicit predictive control using the incremental model is ***, input-mapping method is integrated with explicit predictive control. During offline computation, analytical forms of the input-mapping combination coefficients and the optimal solution function of explicit model predictive control are *** computation of combination coefficients is conducted to obtain the optimal solution rapidly. The effectiveness of the proposed method is verified through simulations in MATLAB.
As for urban water dispatch, multiple steps of water pressure prediction are necessary. Due to the strong irregularity of water pressure, both machine learning and original deep learning methods can't accurately p...
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As for urban water dispatch, multiple steps of water pressure prediction are necessary. Due to the strong irregularity of water pressure, both machine learning and original deep learning methods can't accurately predict water pressure. In order to predict the water pressure with significant irregularity, this paper has developed a prediction model. The CEEMDAN approach seeks to reduce the noise of the raw water pressure data, which is directly recorded by sensors. The extraction of pump state signals has the ability to introduce extra useful information to the training model. Gradient Correction Methodology is a new strategy for increasing the precision of water pressure prediction in multi-step models. It could alleviate the gradient disappearing issue for long horizon prediction. In general, the designed prediction model on water pressure performs better than other models with long step sizes.
Developing an efficient automatic navigation system for mobile robots is challenging in the strange scenarios where robots can only observe the environment of the surrounding limited *** other distributed automatic na...
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ISBN:
(数字)9789887581536
ISBN:
(纸本)9781665482561
Developing an efficient automatic navigation system for mobile robots is challenging in the strange scenarios where robots can only observe the environment of the surrounding limited *** other distributed automatic navigation systems exist,they often require extracting semantic information to calculate navigation action,which requires extra modules to provide perceptual information and is not *** propose an end-to-end automatic navigation system based on the reinforcement learning *** particular,the raw 3 D LiDAR data is used to directly map an efficient navigation *** design a novel dense reward function to handle the reward sparsity issue and provide a graphical representation method to enable the efficient feature learning from the raw 3 D LiDAR data in our navigation *** addition,an imitation learning based policy initialization is introduced before the subsequent reinforcement learning,which increases the learning efficiency and,in the meantime,still encouraging the robot to explore all the potential states to achieve advanced performance than the imitated *** navigation model is trained in the Webots environment and the experimental results show that our model has efficient and flexible navigation performance in complex *** importantly,trained model can be easily extended to unfamiliar environments.
Close and efficient cooperation between devices in the Industrial Internet of Things (IIoT) requires precise clock synchronization as a prerequisite. The uncertainty of IIoT networks and the complexity of industrial e...
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Wood broken defects, such as cracks, penetrating dead knots and wanes, will seriously weaken the strength of the wood and destroy the structral integrity of the wood. Therefore, these defects should be inspected and t...
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Pickup vehicle scheduling in the steel logistics park is a critical issue in determining the outbound effciency of steel products. Steel products are distributed in the yards of the steel logistics park with mixed sto...
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