In this paper, a novel self-learning optimal control approach is established to design the decentralized guaranteed cost control of a class of complex nonlinear systems under uncertain environment. By expressing the i...
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In this paper, a novel self-learning optimal control approach is established to design the decentralized guaranteed cost control of a class of complex nonlinear systems under uncertain environment. By expressing the interconnected sub-systems as a whole system, establishing an appropriate bounded function, and defining a modified cost function, the decentralized guaranteed cost control problem is transformed into an optimal control problem. Then, the online policy iteration algorithm is employed to solve iteratively the modified Hamilton-Jacobi-Bellman equation corresponding to the nominal system. A critic neural network is constructed to obtain the optimal control approximately. At last, a simulation example is provided to verify the effectiveness of the present control approach.
This paper proposes the multiple actor-critic structures to obtain the optimal control via input-output data. The shunting inhibitory artificial neural network (SIANN) is used to classify the input-output data into on...
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This paper proposes the multiple actor-critic structures to obtain the optimal control via input-output data. The shunting inhibitory artificial neural network (SIANN) is used to classify the input-output data into one of several categories. Different performance index functions may be define for disparate categories. Neural networks are used to approximate the critic network and action network, respectively. It is proven that the model error asymptotically converges to zero and the closed unknown system is uniformly ultimately bounded. Simulation results demonstrate the performance of the proposed optimal control scheme for the unknown nonlinear system.
Weibo has become an important information sharing platform in our daily life in China. Many applications utilize Weibo data to analyze hot topic and opinion evolution patterns to gain insights into user behavior. Howe...
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Weibo has become an important information sharing platform in our daily life in China. Many applications utilize Weibo data to analyze hot topic and opinion evolution patterns to gain insights into user behavior. However, various spam messages degrade the performance of these applications and thus are essential to be filtered. In this paper, we propose a unified spam detection approach, which utilizes external knowledge sources to expand keywords features and applies an ensemble under-sampling based strategy to handle the class-imbalance problem. The experimental results show the effectiveness and robustness of our approach in Weibo data.
In this paper, we present a new framework for large scale online kernel learning, making kernel methods efficient and scalable for large-scale online learning applications. Unlike the regular budget online kernel lear...
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In this paper, we present a new framework for large scale online kernel learning, making kernel methods efficient and scalable for large-scale online learning applications. Unlike the regular budget online kernel learning scheme that usually uses some budget maintenance strategies to bound the number of support vectors, our framework explores a completely different approach of kernel functional approximation techniques to make the subsequent online learning task efficient and scalable. Specifically, we present two different online kernel machine learning algorithms: (i) Fourier Online Gradient Descent (FOGD) algorithm that applies the random Fourier features for approximating kernel functions; and (ii) Nyström Online Gradient Descent (NOGD) algorithm that applies the Nyström method to approximate large kernel matrices. We explore these two approaches to tackle three online learning tasks: binary classification, multi-class classification, and regression. The encouraging results of our experiments on large-scale datasets validate the effectiveness and efficiency of the proposed algorithms, making them potentially more practical than the family of existing budget online kernel learning approaches.
The coordinated tracking problem of networked Euler-Lagrange systems is studied in this *** to the knowledge of classical control,an integral term can eliminate the steady-state error when solving the tracking problem...
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ISBN:
(纸本)9781479947249
The coordinated tracking problem of networked Euler-Lagrange systems is studied in this *** to the knowledge of classical control,an integral term can eliminate the steady-state error when solving the tracking problem.A proportional-integral-derivative(PID)tracking protocol is then rst proposed to solve the tracking problem of Euler-Lagrange systems where the leader has a quadratic *** properly choosing parameters,it is proved that all followers can asymptotically track the leader’s quadratic trajectory if the communication topology graph has a spanning ***,a so-called PImD tracking protocol is derived by adding some high-order integral *** is shown that this PImD tracking protocol can solve the tracking problem of networked Euler-Lagrange systems with a leader having the higher-order polynomial ***,two simulation examples are presented to demonstrate the effectiveness of the proposed protocol.
By taking into account the hits-density imaging technique that has been introduced by authors' previous publications, the acoustic emission bursts emitted from the automatic-gauge-control hydraulic cylinder under ...
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By taking into account the hits-density imaging technique that has been introduced by authors' previous publications, the acoustic emission bursts emitted from the automatic-gauge-control hydraulic cylinder under normal loading and early-stage vibration were investigated. First, six acoustic emission descriptors that showed significance regarding the cumulative probability distribution were visualised, followed by the reconstruction of the hits-density images using these features;Through the visual examination of the hits-density images regarding the cylinders' normal loading and early-stage vibration, apparent visual differences between normal and early-stage vibration under the same loading can be observed;By projecting the hits-density images onto the principal component space, a trajectory which represents the condition developments was observed, which shows a visual-based resolution for dealing with vast transient bursts data reduction,reconstruction and visualisation.
Underwater cave exploration has always been a tough problem for autonomous underwater *** a primary step towards this problem,we explore the underwater cave search and entry with a free-swimming robotic fish character...
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ISBN:
(纸本)9781479947249
Underwater cave exploration has always been a tough problem for autonomous underwater *** a primary step towards this problem,we explore the underwater cave search and entry with a free-swimming robotic fish characterized by flexible control and embedded *** particular,we use a colored ring instead of the cave and acquire its contour by its binary *** we propose an algorithm combining the Meanshift algorithm with the bump characteristic of the ring contour to eliminate the mirror image effects and background *** a bio-inspired Central Pattern Generator control method is adopted to smoothly drive the robotic fish to swim towards the *** proposed algorithms are implemented in real time with a hybrid controlsystem consisting of two embedded microprocessors(TI DM3730 and STMicroelectronics STM32F407).Preliminary aquatic experiments demonstrate that a fairly good exploration effect is resulted and the interference caused by mirror image effect and background is largely *** proposed robotic fish-based scheme offers an alternative to cave exploration in complex aquatic environments.
This paper studies the output consensus problem of single-input single-output(SISO)multi-agent *** is assumed that the multi-agent system works in a noisy environment(state noises,measurement noises and communication ...
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ISBN:
(纸本)9781479947249
This paper studies the output consensus problem of single-input single-output(SISO)multi-agent *** is assumed that the multi-agent system works in a noisy environment(state noises,measurement noises and communication noises).A dynamic output-feedback based protocol is proposed to solve the stochastic output consensus problem in this *** is proved that the mathematical expectations of relative outputs between agents are convergent to zero,and the second-order moments of relative outputs between agents are uniformly ***,some simulation examples are presented to demonstrate this phenomenon.
In fighting the coronary heart diseases,percutaneous coronary intervention is proved to be a powerful and reliable clinical procedure in the modern catheterization labs all over the *** to its minimally invasive chara...
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ISBN:
(纸本)9781479947249
In fighting the coronary heart diseases,percutaneous coronary intervention is proved to be a powerful and reliable clinical procedure in the modern catheterization labs all over the *** to its minimally invasive characteristics,the procedure must be performed in the image-guided way,which makes this important skill very difficult to *** make the learning more accessible,a computer-aided surgical simulator is planned to be implemented in our *** now,the prototyping model is completed and the further validation is being *** implementing the virtual anatomic environment,we aim to provide the trainee an intuitive visual effect so that the models of the organs bear resemblance to their counterpart of the human'*** the blood vessels per se,the surrounding organs seen in the real surgery also need to be visualized during the *** heart is undoubtedly the most critical one among *** segmentation of the heart is a challenging task because of the noisy and indistinct boundaries of the heart in the images due to the natural heart beating during the image *** this paper,an approach based on the active contours method is developed to fulfill this *** experimental results demonstrate the effectiveness of our approach.
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