This paper focuses on the design of an initialization-free distributed finite-time algorithm for the economic dispatch problem in smart grid, where the generation units only communicate with its neighbors to minimize ...
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This paper deals with the three-dimensional(3D) coordinated control of satellites formation motion along a set of given closed orbits, where each satellite has intrinsic second-order Lipchitz nonlinear dynamics and th...
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ISBN:
(纸本)9781467374439
This paper deals with the three-dimensional(3D) coordinated control of satellites formation motion along a set of given closed orbits, where each satellite has intrinsic second-order Lipchitz nonlinear dynamics and the commutation topology among satellites is directed. A projection-based orbit extension method is presented by extending our previous concentric compressing method. The control for the orbit-tracking subsystem and the formation motion subsystem are designed respectively at first, and then the overall closed-loop coordinated orbit-following system is regarded as a cascade system. By using tools from Input-toState stability(ISS) theory and the extension of Barbalat's lemma, it is shown the closed-loop coordinated orbit-tracking system is asymptotic stability if the directed communication topology contains a directed spanning tree. The effectiveness of the analytical results is verified by Satellite Tool Kit(STK).
Grasping is a significant yet challenging task for the robots. In this paper, the grasping problem for a class of dexterous robotic hands is investigated based on the novel concept of constrained region in environment...
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Grasping is a significant yet challenging task for the robots. In this paper, the grasping problem for a class of dexterous robotic hands is investigated based on the novel concept of constrained region in environment, which is inspired by the grasping operations of the human beings. More precisely, constrained region in environment is formed by the environment, which integrates a bio-inspired co-sensing framework. By utilizing the concept of constrained region in environment, the grasping by robots can be effectively accomplished with relatively low-precision sensors. For the grasping of dexterous robotic hands, the attractive region in environment is first established by model primitives in the configuration space to generate offline grasping planning. Then, online dynamic adjustment is implemented by integrating the visual sensory and force sensory information, such that the uncertainty can be further eliminated and certain compliance can be obtained. In the end, an experimental example of BarrettHand is provided to show the effectiveness of our proposed grasping strategy based on constrained region in environment.
Unmanned Aerial Vehicles (UAVs) are increasingly important in dynamic environments such as logistics transportation and disaster response. However, current tasks often rely on human operators to monitor aerial videos ...
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Recently, generative adversarial networks(GANs)have become a research focus of artificial intelligence. Inspired by two-player zero-sum game, GANs comprise a generator and a discriminator, both trained under the adver...
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Recently, generative adversarial networks(GANs)have become a research focus of artificial intelligence. Inspired by two-player zero-sum game, GANs comprise a generator and a discriminator, both trained under the adversarial learning *** goal of GANs is to estimate the potential distribution of real data samples and generate new samples from that *** their initiation, GANs have been widely studied due to their enormous prospect for applications, including image and vision computing, speech and language processing, etc. In this review paper, we summarize the state of the art of GANs and look into the future. Firstly, we survey GANs' proposal background,theoretic and implementation models, and application ***, we discuss GANs' advantages and disadvantages, and their development trends. In particular, we investigate the relation between GANs and parallel intelligence,with the conclusion that GANs have a great potential in parallel systems research in terms of virtual-real interaction and integration. Clearly, GANs can provide substantial algorithmic support for parallel intelligence.
First of all, I would like to take this opportunity to express my sincere and deep thanks to our Editor-in-Chief, Professor Meng Chu Zhou, who took over my position after I was drafted for rejuvenating IEEE Transactio...
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First of all, I would like to take this opportunity to express my sincere and deep thanks to our Editor-in-Chief, Professor Meng Chu Zhou, who took over my position after I was drafted for rejuvenating IEEE Transactions on Computational Social systems in 2017. During the past five years, Meng Chu’s professional leadership and dedication has transformed IEEE/CAA Journal of Automatica Sinica(JAS) from its infancy to a young and high-impact publication in the world that is full of vitality and actively engaged by a group of talented and charged associate Ei Cs and editors, which is clearly demonstrated in Meng Chu’s farewell editorial [1]. I am very glad that Professor Qing-Long Han, an influential and leading scientist of the world-class in AI, control, automation, and intelligent science and technology from Australia, as well as a staunch supporter and great leader of this journal from its beginning, will take over the Ei C torch from Meng Chu next year, since I am extremely confident that our journal will reach a new high for its service and quality under his new leadership.
In this paper,an adaptive approximation image reconstruction method based on orthogonal triangular with column pivoting(QRCP) decomposition algorithm is proposed for single sample problem in face *** using QRCP the si...
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ISBN:
(纸本)9781479947249
In this paper,an adaptive approximation image reconstruction method based on orthogonal triangular with column pivoting(QRCP) decomposition algorithm is proposed for single sample problem in face *** using QRCP the single sample and its transpose are decomposed to two sets of basis *** an adaptive approximation image reconstruction method is proposed to reconstruct two approximation images from the two basis image sets *** single training sample and its two approximation images of each object form a new training set,which can make the fisher linear discriminant analysis(FLDA) be applied to single sample problem in face *** performance of the proposed method is verified on Yale,FERET,and ORL face *** experimental results indicate that the proposed method is efficient and outperforms some existing methods which are proposed to overcome the single sample problem.
This paper studies the distributed sensor activation and target tracking problem for wireless sensor networks with limited sensing range. A novel approach based on a fully distributed event-triggered sensor activation...
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This paper focuses on the challenge of fixed-time control for spatiotemporal neural networks(SNNs) with discontinuous activations and time-varying coefficients. A novel fixed-time convergence lemma is proposed, which ...
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This paper focuses on the challenge of fixed-time control for spatiotemporal neural networks(SNNs) with discontinuous activations and time-varying coefficients. A novel fixed-time convergence lemma is proposed, which facilitates the handling of time-varying coefficients of SNNs and relaxes the restriction on the non-positive definiteness of the derivative of the Lyapunov function. Besides, a more flexible and economical aperiodically switching control technique is presented to stabilize SNNs within a fixed time,efectively reducing the amount of information transmission and control costs. Under the newly established fixed-time convergence lemma and aperiodically switching controller, many more general algebraic conditions are deduced to ensure the fixed-time stabilization of SNNs. Numerical examples are provided to manifest the validity of the results.
This paper estimates an off-policy integral reinforcement learning(IRL) algorithm to obtain the optimal tracking control of unknown chaotic systems. Off-policy IRL can learn the solution of the HJB equation from the...
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This paper estimates an off-policy integral reinforcement learning(IRL) algorithm to obtain the optimal tracking control of unknown chaotic systems. Off-policy IRL can learn the solution of the HJB equation from the system data generated by an arbitrary control. Moreover, off-policy IRL can be regarded as a direct learning method, which avoids the identification of system dynamics. In this paper, the performance index function is first given based on the system tracking error and control error. For solving the Hamilton–Jacobi–Bellman(HJB) equation, an off-policy IRL algorithm is *** is proven that the iterative control makes the tracking error system asymptotically stable, and the iterative performance index function is convergent. Simulation study demonstrates the effectiveness of the developed tracking control method.
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