The parasitic inductance of transmitting coil in transient electromagnetic transmitter causes some serious problems like the overlong falling edge time, overshoot and oscillation of the emission current. In order to s...
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The parasitic inductance of transmitting coil in transient electromagnetic transmitter causes some serious problems like the overlong falling edge time, overshoot and oscillation of the emission current. In order to solve these above problems, this paper proposes a design scheme of passive constant voltage clamping circuit of highly speeding shutoff based on TVS（Transient Voltage Suppressor） and switch. In this design scheme, resistance, TVS and switch are configured in parallel and then connected into the main launch bridge circuit. During the earlier stage of the shutoff of the emission current, TVS is utilized to form the high voltage clamping and thus realize the highly speeding shutoff of the emission current. At the later stage of the emission current decline, the energy of the load inductance is set free by the resistance to prevent the overshoot and oscillation of the emission current. In this paper, the operating procedure and principle of the circuit, the influence of the parameters of core devices on the circuit performance, and the effectiveness of this design scheme is verified by simulation and experiment. The results of simulation and experiment show that this circuit is effective to reduce the shutoff time of the emission current, restrain the overshoot and oscillation meanwhile, and hence improve the wave quality of the emission current.
It is important for the dulcimer robot to obtain the spatial coordinates of the dulcimer phonemes. However, the traditional manual positioning method is both inefficient and does not meet the intelligence requirements...
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This paper focuses on the control problem of a class of random teleoperation systems. To overcome the difficulties caused by the random environment, a new adaptive sliding mode control method for random teleoperation ...
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This paper focuses on the control problem of a class of random teleoperation systems. To overcome the difficulties caused by the random environment, a new adaptive sliding mode control method for random teleoperation system is *** with the previous work, the model in this paper is built by random differential equations. In addition, different time-varying delays are introduced between the two communication channels. Furthermore, a new design scheme for random teleoperation system with varying-time delay is proposed. Radial Basis Function neural network（RBFNN） is introduced to deal with the unknown nonlinearities of the system. Using this method, good position tracking performance and stability can be obtained.
During the construction of the tunnel excavation with the method of drilling and blasting,overbreak and underbreak occur ***,overbreak and underbreak affect the cost,efficiency,and safety of tunnel *** paper presents ...
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During the construction of the tunnel excavation with the method of drilling and blasting,overbreak and underbreak occur ***,overbreak and underbreak affect the cost,efficiency,and safety of tunnel *** paper presents a detection method for overbreak and underbreak of tunnels based on three-dimensional laser point ***,this paper obtains point cloud data of a tunnel by a 3 D laser scanner,preprocesses the point cloud data based on Gaussian filter,and extracts midlines of the tunnel based on random sampling consistency(RANSAC) to obtain attitude and trend information of the ***,cross-sections of the tunnel are extracted according to the midline of the ***,the position and value of the overbreak and underbreak are got according to comparing the projections of the cross-sections of the tunnel with a planned extent of the ***,this method was applied to an evaluation of overbreak and underbreak of a tunnel,and the results show that the method in this paper detects overbreak and underbreak easily,quickly,and accurately.
Plate shape is one of the key quality indices of steel plates after *** is of great significance to realize the prediction and optimization of plate shape for obtaining high quality steel *** paper designs a predictio...
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Plate shape is one of the key quality indices of steel plates after *** is of great significance to realize the prediction and optimization of plate shape for obtaining high quality steel *** paper designs a prediction and optimization system for plate shape in roller quenching ***,the roller quenching process is described in detail,the design objectives are analyzed,and the architecture of the system is ***,the system is designed from four parts:the prediction model of plate shape,the comprehensive evaluation model of plate shape,the intelligent optimization model of operating parameters and the case ***,the prediction and optimization system is applied to the industrial *** results of preliminary tests show that the system improves the quality of plate shape.
Electroencephalogram（EEG） emotion recognition has gained considerable attention due to its ability to reflect people’s inner emotional states objectively and *** extraction is a critical step in EEG emotion recogni...
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Electroencephalogram（EEG） emotion recognition has gained considerable attention due to its ability to reflect people’s inner emotional states objectively and *** extraction is a critical step in EEG emotion recognition because of non-stationarity and irregularity of EEG signals.A feature extraction method using Variational Modal Decomposition（VMD）to extract Dispersion Entropy（DispEn） is proposed in this *** EEG signal is decomposed into several components,and DispEn of each component is extracted in eight emotion-related *** method was tested on DEAP dataset in which the EEG emotional states are accessed in Valence-Arousal emotional *** emotional states（i.e.,HVHA,HVLA,LVHA,LVLA） are classified by Support Vector Machine（SVM）.The experimental results show that the accuracy of emotion recognition is 77.87%,which demonstrates its effectiveness.
This paper investigates the problem of model predictive control（MPC） for systems with polytopic uncertainties under the event-triggered communication mechanism. To save network resources, a new dynamic event-trigger...
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This paper investigates the problem of model predictive control（MPC） for systems with polytopic uncertainties under the event-triggered communication mechanism. To save network resources, a new dynamic event-triggered mechanism（DETM） is proposed, which contains an adaptive internal dynamic variable（IDV） and a time-varying parameter. A "min-max"optimization problem is put forward to dealing with the MPC problem for systems with polytopic uncertainties. With the aid of a Lyapunov-like function dependent on the IDV of the DETM, an auxiliary optimization problem is devised with constraints in terms of linear matrix inequalities. By solving such an auxiliary optimization problem, sub-optimal feedback gains are obtained which ensure the input-to-state practical stability of the closed-loop system. A numerical example is provided to demonstrate the effectiveness of the devised MPC algorithm.
In view of the loss of speed caused by the attack of the four-rotor UAV executor, an adaptive control method is designed to maintain the altitude and posture of the UAV without the attack diagnostic mechanism. Adaptiv...
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In view of the loss of speed caused by the attack of the four-rotor UAV executor, an adaptive control method is designed to maintain the altitude and posture of the UAV without the attack diagnostic mechanism. Adaptive event trigger control methods also consider the mechanism of event triggering. The main impact of attacks on UAVs is the loss of thrust from UAVs. The attack-tolerant method designed in this paper can ensure that the tracking error of multi-acting device can maintain altitude and attitude when attacked is gradually convergent. At the same time, the event trigger method reduces the use of communication resources. Simulation proves the validity of the method.
Aiming at the multi-condition problem of Continuous Annealing Processes(CAP), this paper proposes a new method based on Long Short-Term Memory(LSTM) and Gated Recurrent Unit(GRU) models to identify multiple conditions...
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Aiming at the multi-condition problem of Continuous Annealing Processes(CAP), this paper proposes a new method based on Long Short-Term Memory(LSTM) and Gated Recurrent Unit(GRU) models to identify multiple conditions in ***, this work analyzes the parameters in CAP, selects the key variables that affect the working conditions, and then selects a piece of data in the CAP work process as the training data set to train the constructed LSTMRU neural network. This method realizes the recognition of different working conditions in CAP, which saves training time, simplifies internal *** with the traditional method, this method avoids the recognition error caused by personal experience factors, and the model accuracy has greatly improved.
Wind power prediction is the basis of power grid energy dispatching. However, wind instability increases the difficulty of wind power prediction. The paper proposes a wind power prediction method based on long and sho...
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Wind power prediction is the basis of power grid energy dispatching. However, wind instability increases the difficulty of wind power prediction. The paper proposes a wind power prediction method based on long and short-term memory network to improve the accuracy of wind power prediction. First, wind power sequence is decomposed by empirical mode decomposition(EMD) method, and the noise in the original sequence was removed by effective component reconstruction. Then, long shortterm memory(LSTM) with the ability of information memory predicts model of wind power sequence. The improved particle swarm optimization algorithm(IPSO) optimized the parameters of LSTM to solve the problem that the parameters of LSTM, such as the number of neurons, the learning rate and the number of iterations, are difficult to determine and thus affect the prediction accuracy of the model. Finally, the proposed EMD-IPSO-LSTM method makes rolling prediction of wind power series of actual wind farm, and the prediction results are compared with other prediction models. The results show that the prediction model has higher accuracy.
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