In this paper,the formation control problem is investigated for a team of uncertain underactuated surface vessels(USVs)based on a directed *** the risk of collision and the limited communication range of USVs,the pres...
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In this paper,the formation control problem is investigated for a team of uncertain underactuated surface vessels(USVs)based on a directed *** the risk of collision and the limited communication range of USVs,the prescribed performance control(PPC)methodology is employed to ensure collision avoidance and connectivity *** event-triggered mechanism is designed to reasonably use the limited communication ***,neural networks(NNs)and an auxiliary variable are constructed to deal with the problems of uncertain nonlinearities and underactuation,***,an event-triggered formation control scheme is proposed to ensure that all signals of the closed-loop system are uniformly ultimately bounded(UUB).Finally,simulation results are presented to demonstrate the effectiveness of the proposed control scheme.
This paper focuses on the leader-following consensus control problem for nonlinear multiagent systems subject to deferred asymmetric time-varying state constraints.A distributed eventtriggered adaptive neural control ...
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This paper focuses on the leader-following consensus control problem for nonlinear multiagent systems subject to deferred asymmetric time-varying state constraints.A distributed eventtriggered adaptive neural control approach is *** virtue of a distributed sliding-mode estimator,the leader-following consensus control problem is converted into multiple simplified tracking control ***,a shifting function is utilized to transform the error variables such that the initial tracking condition can be totally unknown and the state constraints can be imposed at a specified time ***,the deferred asymmetric time-varying full state constraints are addressed by a class of asymmetric barrier Lyapunov *** order to reduce the burden of communication,a relative threshold event-triggered mechanism is incorporated into controller and Zeno behavior is *** on Lyapunov stability theorem,all closed-loop signals are proved to be semi-globally uniformly ultimately ***,a practical simulation example is given to verify the presented control scheme.
Workpiece grinding is a crucial process in the smart manufacturing chain. In order to meet the requirements of industrial precision and relieve heavy work, researchers have developed a vision-based grinding robot. How...
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The adaptive fixed-time consensus problem for a class of nonlinear multi-agent systems(MASs)with actuator faults is considered in this *** approximate the unknown nonlinear functions in MASs,radial basis function neur...
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The adaptive fixed-time consensus problem for a class of nonlinear multi-agent systems(MASs)with actuator faults is considered in this *** approximate the unknown nonlinear functions in MASs,radial basis function neural networks are *** addition,the first order sliding mode differentiator is utilized to solve the“explosion of complexity”problem,and a filter error compensation method is proposed to ensure the convergence of filter error in fixed *** the help of the Nussbaum function,the actuator failure compensation mechanism is *** designing the adaptive fixed-time controller,all signals in MASs are bounded,and the consensus errors between the leader and all followers converge to a small area of ***,the effectiveness of the proposed control method is verified by simulation examples.
This paper considers the human-in-the-loop leader-following consensus control problem of multi-agent systems(MASs)with unknown matched nonlinear functions and actuator *** is assumed that a human operator controls the...
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This paper considers the human-in-the-loop leader-following consensus control problem of multi-agent systems(MASs)with unknown matched nonlinear functions and actuator *** is assumed that a human operator controls the MASs via sending the command signal to a non-autonomous leader which generates the desired ***,the leader’s input is nonzero and not available to all *** using neural networks and fault estimators to approximate unknown nonlinear dynamics and identify the actuator faults,respectively,the neighborhood observer-based neural fault-tolerant controller with dynamic coupling gains is *** is proved that the state of each follower can synchronize with the leader’s state under a directed graph and all signals in the closed-loop system are guaranteed to be cooperatively uniformly ultimately ***,simulation results are presented for verifying the effectiveness of the proposed control method.
In sequential recommender systems, the main problems are the long-tailed distribution of data and noise interference. A Contrastive Framework for Sequential Recommendation (CFSeRec) is proposed to solve these two prob...
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This paper proposes an estimator-based distributed model predictive control (DMPC) approach for vehicle platoons in the presence of external disturbance and uncertain cornering stiffness. A lateral dynamics model of v...
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The problem of solving discrete-Time Lyapunov equations (DTLEs) is investigated over multiagent network systems, where each agent has access to its local information and communicates with its neighbors. To obtain a so...
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This paper proposes a sampled-data multi-objective path-following control method for autonomous vehicles based on the polytopic linear parameter varying (LPV) approach. Combining the active front-wheel steering (AFS) ...
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In recent years,the introduction of Siamese network has brought new vitality to the object tracking ***,high-performance Siamese trackers cannot run at a real-time speed on mobile devices due to their complex and huge...
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ISBN:
(数字)9789887581536
ISBN:
(纸本)9781665482561
In recent years,the introduction of Siamese network has brought new vitality to the object tracking ***,high-performance Siamese trackers cannot run at a real-time speed on mobile devices due to their complex and huge *** distillation is a common and effective model compression method,but it is difficult to be applied to the challenging task like object *** find out the fundamental cause is that the imbalance between the foreground and background in the object tracking task,which aggravates the problem of insufficient feature extraction ability of small ***,we propose the attention mask distillation(AMD) to help the student tracker focus on the foreground area faster and more *** attention mask can be easily obtained from the feature maps and brings fine-granularity to the traditional binary *** experimental results on OTB100 and VOT2018 show that our method enables the student tracker perform as well as the teacher *** the same time,it's able to run on the CPU at a hyper-real-time of 66 fps and achieves nearly 9 times model compression *** low computational and storage costs make it possible to deploy high-performance trackers on resource-constrained platforms.
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