This paper introduces a kind of spectral data acquisition system based on the linear CCD. The spectral acquisition circuit, data conversion and storage circuit were designed. The synchronization of the spectral data a...
详细信息
In this paper, the fuzzy [Formula: see text] output-feedback control problem is investigated for a class of discrete-time T-S fuzzy systems with channel fadings, sector nonlinearities, randomly occurring interval dela...
详细信息
In this paper, the fuzzy [Formula: see text] output-feedback control problem is investigated for a class of discrete-time T-S fuzzy systems with channel fadings, sector nonlinearities, randomly occurring interval delays (ROIDs) and randomly occurring nonlinearities (RONs). A series of variables of the randomly occurring phenomena obeying the Bernoulli distribution is used to govern ROIDs and RONs. Meanwhile, the measurement outputs are subject to the sector nonlinearities ( the sensor saturations) and we assume the system output is [Formula: see text], [Formula: see text]. The th-order Rice model is utilized to describe the phenomenon of channel fadings by setting different values of the channel coefficients. The aim of this work is to deal with the problem of designing a full-order dynamic fuzzy [Formula: see text] output-feedback controller such that the fuzzy closed-loop system is exponentially mean-square stable and the [Formula: see text] performance constraint is satisfied, by means of a combination of Lyapunov stability theory and stochastic analysis along with LMI methods. The proposed fuzzy controller parameters are derived by solving a convex optimization problem via the semidefinite programming technique. Finally, a numerical simulation is given to illustrate the feasibility and effectiveness of the proposed design technique.
By ordinary Takagi-Sugeno(TS) fuzzy models, complex nonlinear systems can be represented to a set of linear submodels by using fuzzy sets and fuzzy reasoning. This paper is concerned with the problem of observer-based...
详细信息
ISBN:
(纸本)9781479947249
By ordinary Takagi-Sugeno(TS) fuzzy models, complex nonlinear systems can be represented to a set of linear submodels by using fuzzy sets and fuzzy reasoning. This paper is concerned with the problem of observer-based state estimation for fuzzy neural networks(FNNs) with time-varying structured uncertainties and time-varying delay. The problem addressed is to estimate the neuron states, through available output measurements, such that the dynamics of the estimation error is globally exponentially stable. An effective linear matrix inequality approach is developed to solve the neuron state estimation *** particular, we derive the conditions for the existence of the desired estimators of the delayed neural networks for all admissible parametric uncertainties. The designed controller simultaneously contains both the current state information and nonlinear disturbances on the network outputs and can be derived by solving a linear matrix inequality(LMI). A numerical example is included to illustrate the applicability of the proposed design method.
In this paper, a control simulation of the autonomous landing process of a Vertical Take-Off and Landing(VTVL) Reusable Launch Vehicle(RLV) is proposed and we consider the effects of the inner liquid propellant sloshi...
详细信息
ISBN:
(纸本)9781479947249
In this paper, a control simulation of the autonomous landing process of a Vertical Take-Off and Landing(VTVL) Reusable Launch Vehicle(RLV) is proposed and we consider the effects of the inner liquid propellant sloshing, elastic vibration, disturbance force, disturbance torque and other complex conditions in the virtual RLV model. On the basis of dynamics modeling of the RLV, we analyzed RLV's landing process. The landing control system was designed under certain conditions. Co-simulation Research was achieved by ADAMS and MATLAB/Simulink. The simulation results show that the control system performs well.
Active disturbance rejection control is proposed to study the problems on trajectory tracking and decoupling for a two-joint system driven by pneumatic artificial muscles. Because of coupling and nonlinearity, it is v...
详细信息
Active disturbance rejection control is proposed to study the problems on trajectory tracking and decoupling for a two-joint system driven by pneumatic artificial muscles. Because of coupling and nonlinearity, it is very hard to obtain good performance in trajectory tracking for the two-joint system. The active disturbance rejection nonlinear controller includes a tracking differentiator, an extended state observer and a nonlinear error feedback controller. The tracking differentiator is introduced to arrange a transitional process to track input signal and get differential signal. The extended state observer is designed to estimate the non-linearity of system. The nonlinear error feedback controller is designed to improve the performance of system. Simulation results are given to show the effectiveness of proposed controller in this paper.
Based on the nonlinear dynamics principle, the nonlinear dynamic model of electro-hydraulic servo system (EHSS) was established. The influence laws of nonlinear spring force and friction on dynamic characteristics of ...
详细信息
Based on the nonlinear dynamics principle, the nonlinear dynamic model of electro-hydraulic servo system (EHSS) was established. The influence laws of nonlinear spring force and friction on dynamic characteristics of EHSS were explored. Moreover, the bifurcation characteristics arising from primary excitations were investigated. The incentives of nonlinear dynamics behaviors (NDBs) in EHSS were revealed. Results show that the dynamic differential equations of EHSS can be described by Duffing-Van Der Pol equation. When EHSS is in working, excitation force, spring force nonlinear term and damping can result in complicated NDBs. The results can provide theoretical guidance for the parameter optimization during EHSS designing.
The trigger voltage walkin effect has been investigated by designing two different laterally diffused metal-oxide-semiconductor (LDMOS) transistors with an embedded silicon controlled rectifier (SCR). By inserting...
详细信息
The trigger voltage walkin effect has been investigated by designing two different laterally diffused metal-oxide-semiconductor (LDMOS) transistors with an embedded silicon controlled rectifier (SCR). By inserting a P+ implant region along the outer and the inner boundary of the N+ region at the drain side of a conventional LDMOS transistor, we fabricate the LDMOS-SCR and the SCR-LDMOS devices with a different triggering order in a 0.5/zm bipolar-CMOS-DMOS process, respectively. First, we perform transmission line pulse (TLP) and DC-voltage degradation tests on the LDMOS-SCR. Results show that the trigger voltage walk-in effect can be attributed to the gate oxide trap generation and charge trapping. Then, we perform TLP tests on the SCR-LDMOS. Results indicate that the trigger voltage walk-in effect is remarkably reduced. In the SCR-LDMOS, the embedded SCR is triggered earlier than the LDMOS, and the ESD current is mainly discharged by the parasitic SCR structure. The electric potential between the drain and the gate decreases significantly after snapback, leading to decreased impact ionization rates and thus reduced trap generation and charge trapping. Finally, the above explanation of the different trigger voltage walk-in behavior in LDMOS-SCR and SCR-LDMOS devices is confirmed by TCAD simulation.
Complex industrial processes often have multiple operating modes and present time-varying behavior. The data in one mode may follow specific Gaussian or non-Gaussian distributions. In this paper, a numerically efficie...
详细信息
Complex industrial processes often have multiple operating modes and present time-varying behavior. The data in one mode may follow specific Gaussian or non-Gaussian distributions. In this paper, a numerically efficient movingwindow local outlier probability algorithm is proposed, lies key feature is the capability to handle complex data distributions and incursive operating condition changes including slow dynamic variations and instant mode shifts. First, a two-step adaption approach is introduced and some designed updating rules are applied to keep the monitoring model up-to-date. Then, a semi-supervised monitoring strategy is developed with an updating switch rule to deal with mode changes. Based on local probability models, the algorithm has a superior ability in detecting faulty conditions and fast adapting to slow variations and new operating modes. Finally, the utility of the proposed method is demonstrated with a numerical example and a non-isothermal continuous stirred tank reactor.
As keyphrase is a small set of words that can best represent a document, they play significant roles in varieties of text-related tasks. In recent years, many unsupervised and supervised methods have been proposed for...
详细信息
As keyphrase is a small set of words that can best represent a document, they play significant roles in varieties of text-related tasks. In recent years, many unsupervised and supervised methods have been proposed for keyphrase extraction. However, keyphrase extraction is an imbalanced classification problem in nature and contains many unlabeled data, which have not been paid attention to in the previous studies. In this research, a new semi-supervised learning method, COS-training, is proposed for keyphrase extraction based on co-training and SMOTE. For the testing and illustration purpose, a keyphrase extraction dataset is selected to verify the effectiveness of the proposed method. Empirical results reveal that COS-training is a potential solution for keyphrase extraction. Among the compared methods, COS-training gets the best result. Al l these results illustrate that COS-training can be used as an alternative method for keyphrase extraction.
In this paper, an improved nonlinear process fault detection method is proposed based on modified kernel partial least squares(KPLS). By integrating the statistical local approach(SLA) into the KPLS framework, two new...
详细信息
In this paper, an improved nonlinear process fault detection method is proposed based on modified kernel partial least squares(KPLS). By integrating the statistical local approach(SLA) into the KPLS framework, two new statistics are established to monitor changes in the underlying model. The new modeling strategy can avoid the Gaussian distribution assumption of KPLS. Besides, advantage of the proposed method is that the kernel latent variables can be obtained directly through the eigen value decomposition instead of the iterative calculation, which can improve the computing speed. The new method is applied to fault detection in the simulation benchmark of the Tennessee Eastman process. The simulation results show superiority on detection sensitivity and accuracy in comparison to KPLS monitoring.
暂无评论