This paper deals with the problem of the state estimation and the sensor faults detection for nonlinear perturbed systems described by Takagi-Sugeno (T-S) fuzzy models with unmeasurable premise variables. Indeed, a ...
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This paper deals with the problem of the state estimation and the sensor faults detection for nonlinear perturbed systems described by Takagi-Sugeno (T-S) fuzzy models with unmeasurable premise variables. Indeed, a T-S observer is synthesized, in descriptor form, to estimate both the system states and the sensor faults simultaneously. The idea of the proposed approach is to introduce the sensor fault as an auxiliary variable in the state vector. Besides, the T-S model with unmeasurable premise variables is reduced to a perturbed model with measurable variables. Convergence conditions are established with Lyapunov theory and the H∞ performance in order to guarantee the best robustness to disturbances. These conditions are expressed in terms of linear matrix inequalities (LMIs). The parameters of the observer are computed using the solution of the LMI conditions. Finally, a numerical example is given to illustrate the design procedures. Simulation results show the satisfactory performances.
In mammographic images, the presence of microcalcification clusters is a primary indicator of breast cancer. However, not all microcalcification clusters are malignant and it is difficult and time consuming for radiol...
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The sequence alignment is one of the most important tasks in Bioinformatics, playing an important role in the sequences analysis. There are many strategies to perform sequence alignment, since those use deterministic ...
The sequence alignment is one of the most important tasks in Bioinformatics, playing an important role in the sequences analysis. There are many strategies to perform sequence alignment, since those use deterministic algorithms, as dynamic programming, until those ones, which use heuristic algorithms, as Progressive, Ant Colony (ACO), Genetic Algorithms (GA), Simulated Annealing (SA), among others. In this work, we have implemented the objective function COFFEE in the MSA-GA tool, in substitution of Weighted Sum-of-Pairs (WSP), to improve the final results. In the tests, we were able to verify the approach using COFFEE function achieved better results in 81% of the lower similarity alignments when compared with WSP approach. Moreover, even in the tests with more similar sets, the approach using COFFEE was better in 43% of the times.
In networked control systems (NCS), the communication between sensors, controllers, and actuators is supported by a shared communication channel that is subject to variable communication delays, limited bandwidth, pac...
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This paper considers using reset control to improve transient performance and overcome some fundamental limitations of linear systems. First, an auxiliary system is presented, then, based on which, a new reset control...
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This paper considers using reset control to improve transient performance and overcome some fundamental limitations of linear systems. First, an auxiliary system is presented, then, based on which, a new reset control model is proposed, such that the non-overshoot performance specification can be met for any minimum phase relative degree one plants, the results imply some limitations of linear systems are overcome and clearly illustrate the advantages of reset control. A numerical example is given to show the effectiveness.
The Brain Extraction Tool (BET) developed by Smith is widely used for brain segmentation due to its simplicity, accuracy and insensitivity to parameter settings. However, it typically requires a large number of iterat...
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ISBN:
(纸本)9781479952106
The Brain Extraction Tool (BET) developed by Smith is widely used for brain segmentation due to its simplicity, accuracy and insensitivity to parameter settings. However, it typically requires a large number of iterations to generate acceptable results. It also sometimes fails to recognize boundaries of the brain. Moreover, obvious under-segmentation occurs for some datasets. In this paper, we present an improved BET method where at each iteration, we enhance the vertex displacement, add a new search path and embed an independent surface reconstruction process. These strategies lead to much faster convergence. Furthermore, a scheme based on fuzzy c-means is proposed to refine the segmentation. Experimental results based on various datsets demonstrated that the proposed method significantly outperforms the original BET and other competing methods.
The results of a PLC implementation of embedded Model Predictive control (MPC) for an industrial problem are presented in this paper. The embedded MPC developed is based on the linear MPC module in SEPTIC (Statoil Est...
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The results of a PLC implementation of embedded Model Predictive control (MPC) for an industrial problem are presented in this paper. The embedded MPC developed is based on the linear MPC module in SEPTIC (Statoil Estimation and Prediction Tool for Identification and control), and it combines custom ANSI C code generation with problem size reduction methods, embedded real-time considerations, and a primal-dual first-order method that provides a fast and light QP solver obtained from the FiOrdOs code generator toolbox. Since the primal-dual first-order method proposed in this paper is new in the control community, an extensive comparison study with other state-of-the-art first-order methods is conducted to underline its potential. The embedded MPC was implemented on the ABB AC500 PLC, and its performance was tested using hardware-in-the-loop simulation of Statoil's newly patented subsea compact separation process. A warm-start variant of the proposed first-order method outperforms a tailored interior-point method by a factor of 4 while occupying 40% less memory.
The Z-source neutral point clamped (NPC) inverters can realize buck-boost energy conversion with all satisfying advantages of the three-level inverters. A significant problem related to this topology is the fluctuatio...
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ISBN:
(纸本)9781479940318
The Z-source neutral point clamped (NPC) inverters can realize buck-boost energy conversion with all satisfying advantages of the three-level inverters. A significant problem related to this topology is the fluctuation of the neutral-point potential (NP). However, the previous modulation techniques for this topology cannot achieve the considerate stable voltage. In this paper, based on the analysis of the relationship among the shoot-through duty cycle and the NP voltage, the average NP current, switching frequency capacitor value, a new feed-forward compensator by modifying the shoot-through duty cycle which can improve to balance the NP voltage balancing is proposed. Meanwhile, in consideration of a low voltage gain caused by the NP voltage balance method, a new control method based on a maximum constant boost control method is proposed, which brings the benefits in both high voltage gain and low-frequency ripple. The considerate stable NP voltage and the high voltage gain have been proven in simulation and through experimental results from a prototype converter.
Barrier coverage is a critical issue in wireless sensor networks for security applications (e.g., border protection), the performance of which is highly related with locations of sensor nodes. Existing work on barrier...
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Barrier coverage is a critical issue in wireless sensor networks for security applications (e.g., border protection), the performance of which is highly related with locations of sensor nodes. Existing work on barrier coverage mainly assume that sensor nodes have accurate location information, however, little work explores the effects of location errors on barrier coverage. In this paper, we study the barrier coverage problem when sensor nodes have location errors and deploy mobile sensor nodes to improve barrier coverage if the network is not barrier covered after initial deployment. We analyze the relationship between the true distance and the measured distance of two stationary sensor nodes and derive the minimum number of mobile sensor nodes needed to connect them with a guarantee when nodes location errors. Furthermore, we propose a fault tolerant weighted barrier graph, based on which we prove that the minimum number of mobile sensor nodes needed to form barrier coverage with a guarantee is the length of the shortest path on the graph. Simulation results validate the correctness of our analysis.
For most practical nonlinear state estimation problems, the conventional nonlinear filters do not usually work well for some cases, such as inaccurate system model, sudden change of state-interested and unknown varian...
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