In this paper, a robust fault detection and diagnosis (FDD) method is proposed for multiple-model systems with modeling uncertainties. A compensation step is introduced to modify the mixed states and their variances o...
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The paper focuses on a stabilizing controller design problem for networked systems with quantization,mixed delays,and a series of packet losses due to the signal transmission through the unreliable communication *** o...
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The paper focuses on a stabilizing controller design problem for networked systems with quantization,mixed delays,and a series of packet losses due to the signal transmission through the unreliable communication *** of both sensor-to-controller and controller-to-actuator are taken into account for the networked systems,and the distributed time delay is also considered in the network *** conditions for designing the controller as well as the system parameters can be obtained by solving certain linear matrix ***,the effectiveness of the designed method is proved by a numerical example.
Brain-computer interface (BCI) plays an important role in helping the people with severe motor disability. In event-related potential (ERP) based BCIs, subjects were asked to count the target stimulus in the offline e...
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Brain-computer interface (BCI) plays an important role in helping the people with severe motor disability. In event-related potential (ERP) based BCIs, subjects were asked to count the target stimulus in the offline experiment, the recorded electroencephalogram (EEG) data was used to train the classification mode. However, subjects may make mistakes in counting the target stimulus or be affected by the non-target stimulus. The target trials may not contain expected ERPs and the non-target trials may contain unexpected ERPs, which was called error samples. This paper intends to survey whether the classification accuracy could be improved after removing these error samples from offline training data. The result showed that the online performance of BCI system could be improved after selecting the offline samples for training the classification mode.
This paper presents a brain-computer interface (BCI) in which the face paradigm was optimized for the visual mismatch negativity (MMN). There were 12 cells in a LCD monitor. A single letter was at the bottom of each c...
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ISBN:
(纸本)9781467368513
This paper presents a brain-computer interface (BCI) in which the face paradigm was optimized for the visual mismatch negativity (MMN). There were 12 cells in a LCD monitor. A single letter was at the bottom of each cell. In the new paradigm, a color face appeared above each of the 12 cells randomly while the gray faces appeared in others 11 cells. A traditional face paradigm with single character pattern was compared. Three healthy subjects participated in the experiment. Results showed that the new paradigm elicited larger N200 and N400 components than traditional face paradigm and had better performance in online session. The results demonstrated the advantages of the new paradigm in our P300 speller system.
This study investigates an event-triggered model predictive control for wireless networked control system with packet losses in the sensor-to-controller channel. Based on a predictive control compensation strategy, th...
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ISBN:
(纸本)9781479987313
This study investigates an event-triggered model predictive control for wireless networked control system with packet losses in the sensor-to-controller channel. Based on a predictive control compensation strategy, the closed-loop model with packet losses is established. The event-triggered conditions are derived by choosing the performance objective function of MPC as a Lyapunov function. Further, the maximal allowable number of successive packet losses is presented. Under the proposed mechanism, the energy consumption of the wireless network is alleviated and closed-loop stability is guaranteed. Finally, simulation results are shown to illustrate the effectiveness of the proposed method.
With new dynamics and uncertainties in today's power grids, traditional fixed-interval State Estimation (SE) may be unable to track the variability and monitor the power grid effectively. This paper presents a new...
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ISBN:
(纸本)9781479958306
With new dynamics and uncertainties in today's power grids, traditional fixed-interval State Estimation (SE) may be unable to track the variability and monitor the power grid effectively. This paper presents a new architecture to transfer data and execute SE on demand. A list of situations are summarized to direct the SE-demand generator in system control center. As SCADA and PMU measurements are co-exist in realistic power systems, time skew problem is inevitable. To mitigate the influence of time skew, a state estimator based on time skew oriented weight adaptation is considered. In each SE circle, the weights assigned to the measurements not only correspond to their noise, but also the time offsets relative to the SE-demand point. Numerical examples demonstrate the improved accuracy of our estimator compared with the conventional hybrid SE when measurements time skew is present.
This paper investigates the stability and L_2-gain problems for a class of continuous-time periodic piecewise linear systems with possibly non-Hurwitz subsystems. First, the exponential stability of periodic piecewise...
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ISBN:
(纸本)9781479917730
This paper investigates the stability and L_2-gain problems for a class of continuous-time periodic piecewise linear systems with possibly non-Hurwitz subsystems. First, the exponential stability of periodic piecewise systems is studied by allowing the Lyapunov function to possibly non-monotonically decreasing over a period. A sufficient condition is established in terms of matrix inequalities. In light of the proposed Lyapunov function, the L_2-gain criterion is derived for periodic piecewise linear systems as well.
This paper investigates the problems of observer-based feedback controller synthesis for discrete-time linear systems under bounded peak disturbances. The control objective is to make the system state of the closed-lo...
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ISBN:
(纸本)9781479917730
This paper investigates the problems of observer-based feedback controller synthesis for discrete-time linear systems under bounded peak disturbances. The control objective is to make the system state of the closed-loop system under bounded peak disturbances converges to an ellipsoid that is as small as possible or converges to a pre-specified ellipsoid. In order to determine the observer gain and feedback gain in the observer-based controller, the matrix decoupling technique is adopted to derive the single-step matrix inequality conditions. A numerical example is given to show the validity of the theoretical findings.
This paper presents that the majorization theory plays an essential role in a class of sensor scheduling problems, whose solutions all have periodic or uniformly distributed patterns. This paper revisits the problem o...
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ISBN:
(纸本)9781479978878
This paper presents that the majorization theory plays an essential role in a class of sensor scheduling problems, whose solutions all have periodic or uniformly distributed patterns. This paper revisits the problem of communication time scheduling for a single sensor with local computation capability, and strengthens its original result by the majorization theory. The scheduling for a single normal sensor in a general-order system is also studied, and the optimal schedules for minimizing the upper bound of the objective function is provided. Examples are provided at the end.
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