AC-DC-AC converter-fed induction motor (IM) drive is mainly realized by back-to-back three-phase converters. However, fault in a single semiconductor switch will make it inoperative. To enable continued controllable o...
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AC-DC-AC converter-fed induction motor (IM) drive is mainly realized by back-to-back three-phase converters. However, fault in a single semiconductor switch will make it inoperative. To enable continued controllable operation in case of the faults occurring in the converter, the five-leg converter with a shared leg between the grid and load sides is a possible solution. However, this topology poses an inherent two-objective control problem, because its grid and load sides should be controlled simultaneously. More importantly, the potential increase of the shared-leg current may destroy the converters. In this paper, a new control scheme based on the FCS-MPC combined with intrinsic characteristic of the five-leg converter is proposed for independent control of the rectifier and inverter subsystem with the shared-leg overcurrent constraint. The condition for independent control is analyzed. In order to give a complete evaluation of the proposed control scheme, the conventional pulsewidth modulation (PWM) control scheme is conducted for comparison. Experimental results are provided to validate the effectiveness of the proposed scheme.
A novel fault-tolerant system for a multi-motor drive with one-leg, two-leg, and secondary faults is designed in this study. Fault tolerance is realized from pre-fault to post-fault via a topology reconstruction schem...
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A novel fault-tolerant system for a multi-motor drive with one-leg, two-leg, and secondary faults is designed in this study. Fault tolerance is realized from pre-fault to post-fault via a topology reconstruction scheme and an integrated control law. The scheme develops a reconstructible topology and its reconstruction algorithm. The multi-motor drive can be reconstructed into appropriate tolerant topologies on the basis of the diagnosis results. The control law based on the predictive torque control method is universal under any topology by designing a unified voltage vector model and an optimal switching state decision. The proposed system can cope with more types of faults and effectively switch from a healthy state to a fault-tolerant state under any fault. The effectiveness and performance of the fault-tolerant system are verified and demonstrated by simulation and experiment results.
Many industrial processes are operated in multiple modes due to different manufacturing strategies. Multimodality of process data is often accompanied with nonlinear and non-Gaussian characteristics, which makes data-...
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Many industrial processes are operated in multiple modes due to different manufacturing strategies. Multimodality of process data is often accompanied with nonlinear and non-Gaussian characteristics, which makes data-driven monitoring more complicated. In this paper, statistics pattern analysis (SPA) is introduced to extract low- and high-order statistics from raw process data. Support vector data description (SVDD), which can deal with nonlinear and non-Gaussian problems, is applied to monitor multimode process in this paper. To improve detection performance of SVDD for training multimode data with outliers, modified local reachability density ratio (mLRDR) is proposed as a weight factor to be embedded in the weighted-SVDD (wSVDD) model, in which the local neighbors in terms of both space and time are considered. Finally, the effectiveness and superiority of our proposed method are demonstrated by the Tennessee-Eastman (TE) process and wastewater treatment process (WWTP).
This study addresses the set-membership estimation problem for a class of discrete time-varying systems with incomplete observations. A set-membership filter is developed and a recursive algorithm is proposed to calcu...
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This study addresses the set-membership estimation problem for a class of discrete time-varying systems with incomplete observations. A set-membership filter is developed and a recursive algorithm is proposed to calculate the state estimate ellipsoid which contains the true value. To solve the problem that the conventional set-membership filter cannot guarantee the stability when applied to discrete time-varying systems with incomplete observations, a quantitative analysis method about incomplete observations is developed and a tight bound of the estimation error is found based on interval analysis and some bounded noise assumptions. In terms of bounded assumptions, the relationship between the bound of estimated error and the data dropout rate is obtained. If the data dropout rate is less than a maximal value, the set-membership filter is asymptotically stable. The proposed filter is applied to a two-state example to demonstrate the effectiveness of theoretical results. (C) 2019 Elsevier Inc. All rights reserved.
Transient sensor malfunction, improper replacement measures, and large non-Gaussian noise can cause data outliers in real-world scenarios. In this article, an outlier-robust zonotope set-membership filter is proposed ...
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Transient sensor malfunction, improper replacement measures, and large non-Gaussian noise can cause data outliers in real-world scenarios. In this article, an outlier-robust zonotope set-membership filter is proposed for uncertain nonlinear systems susceptible to outliers. In order to linearize nonlinear systems, a linearization method based on Stirling's interpolation formula is proposed. Then, an outlier detector utilizing the linearization error bounds, the prediction domain, and the output feasible domain is constructed. Based on the linearized system, a tight strip construction method is given to reduce the conservatism of the estimated enclosure. Moreover, a prediction-correction-backward reconstruction filter structure is designed to improve estimation accuracy and reduce conservatism. The proposed structure fuses historical data to attenuate the impact of uncertainty on the system. The robustness, guarantee, and convergence of the proposed filter are investigated. Finally, the effectiveness of the proposed approach is evaluated by two simulation examples.
Semantic parts have shown a powerful discriminative capacity for action recognition. However, many existing methods select parts according to predefined heuristic rules, which may cause the correlation among parts to ...
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Semantic parts have shown a powerful discriminative capacity for action recognition. However, many existing methods select parts according to predefined heuristic rules, which may cause the correlation among parts to be lost, or do not appropriately consider the cluttered candidate part space, which may result in weak generalizability of the resulting action labels. Therefore, better consideration of the correlation among parts and refinement of the candidate space will lead to a more discriminative action representation. This paper achieves improved performance by more elegantly addressing these two factors. First, considering the cluttered nature of the candidate space, we propose a recursive part elimination strategy for iterative refinement of the candidate parts. In each iteration, we eliminate the parts with the lowest weights, which are deemed to be noise. Second, we measure the discriminative capabilities of the candidates and select the top-ranked parts by applying a maximum margin model, which can alleviate overfitting while simultaneously improving generalizability and correlation extraction. Finally, using the selected parts, we extract mid-level features. We report experiments conducted on four datasets (KTH, Olympic Sports, UCF50, and HIVIDB51). The proposed method can achieve significant improvements compared with other recent methods, including a lower computational cost, a faster speed, and higher accuracy.
Based on the nonlinear characteristics of permanent magnet synchronous motor (PMSM), a nonlinear speed and direct torque control (DTC) using sliding mode backstepping method for PMSM is presented in this paper. The sl...
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Based on the nonlinear characteristics of permanent magnet synchronous motor (PMSM), a nonlinear speed and direct torque control (DTC) using sliding mode backstepping method for PMSM is presented in this paper. The sliding mode speed controller is implemented with exponential reaching law to improve the robustness of the system, and further a step-by-step recursive design for backstepping torque and flux controllers is presented. The system stability with proposed scheme is mathematically proved using Lyapunov stability criteria. At the same time, the load torque is observed with the extended state observer (ESO), and is fed-forward to the controller for rejecting the load disturbance and to mitigate the chattering affect due to the sliding mode controller. Finally, simulation test results are demonstrated to support the effectiveness and feasibility of the proposed strategy.
Three-phase voltage-source inverters fed induction motor with space-vector controlled scheme are widely used in industrial applications. The suffered failures will degrade the system performance with output torque rip...
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Three-phase voltage-source inverters fed induction motor with space-vector controlled scheme are widely used in industrial applications. The suffered failures will degrade the system performance with output torque ripple and harmonic currents. In this paper, a novel diagnosis method is proposed to detect and locate the insulated gate bipolar translator open-circuit fault. Discrete wavelet transform is used as a pre-treatment technique for three-phase output currents, the approximate coefficients are applied to obtain energy vectors. Euclidean distance between every two of the energy vectors are calculated for measuring the current similarity to diagnose fault. When IGBTs occur open-circuit fault, the values of Euclidean distance will be smaller than that under normal conditions, then faults can be detected. Faults can also be located according to extracted features. Simulation and experimental results show high efficiency and merits of the proposed method. (C) 2017 Elsevier Ltd. All rights reserved.
The nonredundant voltage-source inverter, which exploits the possibility ofminimum additional components for reconfiguration and operation, is a promising solution to manage faults in one inverter leg. However, contro...
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The nonredundant voltage-source inverter, which exploits the possibility ofminimum additional components for reconfiguration and operation, is a promising solution to manage faults in one inverter leg. However, control schemes at prefault and postfault conditions are always designed, separatelymaking it hard for control scheme adaptation from normal to fault tolerant. In order to achieve smooth transitions from prefault to postfault, an embeddable fault-tolerant method based on predictive torque control (PTC) is proposed. A generalized voltage vectors, switching command, and cost function accounting for both healthy and faulty conditions are introduced to carry out a general control scheme. A novel fault-diagnosis method based on probability density analysis of the sampling currents is presented for open-circuit fault isolation under PTC scheme. Seamless likely and rapid transient processes from fault occurrence to postfault operation are achieved. Experimental results have demonstrated that the proposed scheme can make power switch fault easily managed by the controller itself.
Biological long short-term memory (B-LSTM) can effectively help human process all kinds of received information. In this work, a memristive B-LSTM circuit which mimics a conversion from short-term memory to long-term ...
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Biological long short-term memory (B-LSTM) can effectively help human process all kinds of received information. In this work, a memristive B-LSTM circuit which mimics a conversion from short-term memory to long-term memory is proposed. That is, the stronger the signal, the more profound the memory and the higher the output. On this basis, an image binarization circuit using adaptive row threshold algorithm is proposed. It can make the image remain a deep impression on the strong pixel information and effectively filter the relatively weak pixel information. In combination with the function of image binarization, a memristive circuit for eyes state detection is proposed by adding corresponding horizontal projection calculation, subtraction calculation and judgement open or closed eyes modules. The proposed circuit can detect whether there is a blink between two adjacent facial images, which uses the characteristics of memristor to detect the difference of horizontal projection between two images. Due to the use of memristor, the proposed circuit can realize in-memory computing, which fundamentally avoids the problem of storage wall and shorten the execution time. Finally, an expectation application in fatigue driving based on the proposed method is demonstrated, which indicates the practicability of the circuit design in this work.
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