Development of reliable soft sensors using limited labeled samples is not an easy task in industrial processes. A selective generative adversarial network (SGAN)-based support vector regression (SGAN-SVR) soft sensor ...
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In the (bio)chemical processes, traditional hardware sensors are difficult to directly measure the quality of critical products due to their time-varying, non-linear, and dynamic characteristics. This makes process so...
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Several data compressors have been proposed in distributed optimization frameworks of network systems to reduce communication overhead in large-scale applications. In this paper, we demonstrate that effective informat...
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This paper studies the distributed bandit convex optimization problem with time-varying inequality constraints, where the goal is to minimize network regret and cumulative constraint violation. To calculate network cu...
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In this paper, a fault detection and isolation scheme for multiplicative faults in dynamic systems based on data-driven K-Gap metric and k-nearest neighbour (kNN) classification is proposed. To detect multiplicative f...
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In this paper, a fault detection and isolation scheme for multiplicative faults in dynamic systems based on data-driven K-Gap metric and k-nearest neighbour (kNN) classification is proposed. To detect multiplicative faults, the standard classification task of kNN is studied from the viewpoint of system analysis. To this end, the data-driven stable kernel representation based on input/output data is presented for feature extraction capturing the dynamic of linear time-invariant (LTI) systems. Data-driven K-Gap metric is used as an alternative tool for distance measure between two kernel subspaces in the kNN algorithm. A simulation example on the three-tank system (DTS200) demonstrates the successful detection and isolation of various multiplicative faults
Cough is a defensive behavior that protects the respiratory system from infection and clears airway *** airflow dynamics have been analyzed by a variety of mathematical and experimental *** this paper,the cough airflo...
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Cough is a defensive behavior that protects the respiratory system from infection and clears airway *** airflow dynamics have been analyzed by a variety of mathematical and experimental *** this paper,the cough airflow dynamics of 42 subjects were obtained and *** identification model based on piecewise Gauss function for cough airflow dynamics is proposed through the dimensionless method,which could achieve over 90%identification ***,an assisted cough system based on pneumatic flow servo system is *** vacuum situation and feedback control are used to increase the simulated peak cough flow rate,which are important for airway secretion clearance and to avoid airway collapse,*** simulated cough peak flow could reach 5 L/s without the external assistance such as manual pressing,patient cooperation and other ***,the backstepping control is developed to generate a simulated cough airflow that closely mimics the natural cough airflow of *** assisted cough system opens up wide opportunities of practical application in airway secretion clearance for critically ill patients with COVID 2019 and other pulmonary diseases.
Accurately predicting the Remaining Useful Life (RUL) of integrated circuits in multi-failure modes is critical for ensuring the safe and efficient operation of electronic devices. In this paper, we propose a novel RU...
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Accurately predicting the Remaining Useful Life (RUL) of integrated circuits in multi-failure modes is critical for ensuring the safe and efficient operation of electronic devices. In this paper, we propose a novel RUL prediction method that combines a locally weighted regression method, a Transformer deep neural network, and a multi-failure modes weighted collaborative prediction approach. We first use a locally weighted regression method to eliminate noise from the original feature time series. Then, the feature time series is input into the proposed classification model to classify the failure modes and establish the failure mode weighted function. Finally, the feature time series is fed into the proposed regression model for RUL prediction with weighted processing to obtain accurate RUL predictions. Our experimental results demonstrate that our method effectively captures the degradation information of integrated circuits and generates precise RUL predictions. We demonstrate the efficacy of our method on a circuit stimulation model, showing that it outperforms several state-of-the-art RUL prediction methods. Our proposed method has the potential to enhance the reliability and safety of electronic devices in various applications.
This paper investigates the problem of designing robust iterative learning control laws for discrete-time batch processes with norm-bounded parameter uncertainties. A law of proportional-differential type is designed ...
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ISBN:
(数字)9783907144107
ISBN:
(纸本)9798331540920
This paper investigates the problem of designing robust iterative learning control laws for discrete-time batch processes with norm-bounded parameter uncertainties. A law of proportional-differential type is designed to achieve robust convergence of the tracking error in the batch-to-batch direction. It is shown that the design problem can be written as a two-dimensional system. Then, the recently developed non-conservative conditions for (structural) stability analysis for a linear Roesser model are used. The conditions for the existence and computation of the required control law matrices are linear matrix inequality-based. Finally, comparative simulation results show the effectiveness of the new design.
This paper aims at eliminating the asymmetric and saturated hysteresis nonlinearities by designing hysteresis pseudo inverse compensator and robust adaptive dynamic surface control(DSC)***"pseudo inverse"mea...
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This paper aims at eliminating the asymmetric and saturated hysteresis nonlinearities by designing hysteresis pseudo inverse compensator and robust adaptive dynamic surface control(DSC)***"pseudo inverse"means that an on-line calculation mechanism of approximate control signal is developed by applying a searching method to the designed temporary control signal where the true control signal is *** main contributions are summarized as:1)to our best knowledge,it is the first time to compensate the asymmetric and saturated hysteresis by using hysteresis pseudo inverse compensator because the construction of the true saturated-type hysteresis inverse model is very difficult;2)by designing the saturated-type hysteresis pseudo inverse compensator,the construction of true explicit hysteresis inverse and the identifications of its corresponding unknown parameters are not required when dealing with the saturated-type hysteresis;3)by combining DSC technique with the tracking error transformed function,the"explosion of complexity"problem in backstepping method is overcome and the prespecified tracking performance is *** of stability and experimental results on the hardware-inloop platform illustrate the effectiveness of the proposed adaptive pseudo inverse control scheme.
Path planning algorithms are current research hotspots. Heuristic algorithms that can solve dynamic environment problems are gradually becoming the mainstream research direction. The D* algorithm, as one of the new he...
Path planning algorithms are current research hotspots. Heuristic algorithms that can solve dynamic environment problems are gradually becoming the mainstream research direction. The D* algorithm, as one of the new heuristic algorithms, has the advantages of being more computationally efficient than the A * algorithm and being able to solve dynamic problems, and has played an important role in two-dimensional path planning projects such as the NASA Mars rover. But its theoretical research and practical application in 3D environment are very rare. In this context, this paper carries out an in-depth study of the path planning problem based on the D* algorithm, and completes the theoretical derivation and simulation process in 2D and 3D environments. In this paper, a complex random 2D map is established by random generation, and the simulation of D* algorithm is realized on the map with the help of Python language, which realizes the finding of the relative optimal path. Then, in order to study the feasibility of D* solving in 3D environment, the simulation of D* algorithm under 3D map is realized with the help of Python and Unity3d. The research results show that the simulation results are good, which is valuable for the theoretical research and practical application of heuristic algorithms, and plays a role in the application of robot path planning algorithms.
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