Robust H∞ filtering with error variance constraints for uncertain discrete-time systems

The robust H∞ filtering problem is considered for discrete-time systems subject to norm-bounded parameter uncertainties in both the state and the output matrices of the state-space model. Sufficient conditions for the filter to satisfy the prescribed H∞ performance and steady-state estimation error variance constraints are given in terms of two discrete algebraic Riccati inequalities. The filter obtained does not depend on the perturbation parameter which is assumed to be unmeasured. An example is provided to illustrate the use of the results for filter design.published_or_final_versio

Robust H-infinity state estimation for discrete-time state-delayed and measurement-delayed systems with uncertainties

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Robust mixed H2/H∞ filtering with regional pole assignment for uncertain discrete-time systems

This paper deals with the robust mixed H2/H∞ filtering problem with regional pole assignment for linear uncertain discrete-time systems in the presence of two sets of exogenous disturbance inputs. A general framework for solving this problem is established using a linear matrix inequality (LMI) approach in conjunction with regional pole constraints, and H2 and H∞ optimization characterization. Necessary and sufficient conditions for the solvability of the problem are given in terms of a set of feasible LMIs. A numerical example is provided to illustrate the effectiveness of the proposed design algorithm.published_or_final_versio

EBW technology applied on the ICRF antenna component

Central conductor is one of the key components of ion cyclotron ranges of heating antenna, which is usually formed by welding due to the complex structures. High level of welding seam quality and small deformation are very important to central conductor. Electron beam welding (EBW) is suggested as the central conductor welding. To meet EBW requirements and reduce the risk, complex and high level of the accuracy welding fixture have been designed for central conductor EBW. Some samples were manufactured to do test and examination for EBW qualification before central conductor welding. Based on the welding parameters, thermal analysis using finite element method for the welding seam have been carried out. One mockup of central conductor for EBW has been made for proving welding parameters. In addition, some postwelding process were employed after one central conductor EBW. Results of examination and inspection of one central conductor using EBW are presented in this paper

Robust H-infinity filtering for systems with deterministic and stochastic parametric uncertainties

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Room Temperature Ionic Liquid as Electrolyte for Lithium Ion Battery

Symposium: Physical and Analytical Electrochemistry: no. I3, Molten Salts and Ionic Liquids 18published_or_final_version222nd Meeting of Electrochemical Society and Pacific Rim Meeting of Related Societies on Electrochemical and Solid-State Science (PRiME 2012), Honolulu, Hawaii, USA, 7-12 October 2012. In Electrochemical Society Meeting Abstracts, v. MA2012-02, abstract no. 372

Mixed H2/H∞ filtering for uncertain systems with regional pole assignment

The mixed H2/H∞ filtering problem for uncertain linear continuous-time systems with regional pole assignment is considered. The purpose of the problem is to design an uncertainty-independent filter such that, for all admissible parameter uncertainties, the following filtering requirements are simultaneously satisfied: 1) the filtering process is asymptotically stable; 2) the poles of the filtering matrix are located inside a prescribed region that compasses the vertical strips, horizontal strips, disks, or conic sectors; 3) both the H2 norm and the norm on the respective transfer functions are not more than the specified upper bound constraints. We establish a general framework to solve the addressed multiobjective filtering problem completely. In particular, we derive necessary and sufficient conditions for the solvability of the problem in terms of a set of feasible linear matrix inequalities (LMIs). An illustrative example is given to illustrate the design procedures and performances of the proposed method. © 2005 IEEE.published_or_final_versio

Fuzzy EMG classification for prosthesis control

This paper proposes a fuzzy approach to classify single-site electromyograph (EMG) signals for multifunctional prosthesis control. While the classification problem is the focus of this paper, the ultimate goal is to improve myoelectric system control performance, and classification is an essential step in the control. Time segmented features are fed to a fuzzy system for training and classification. In order to obtain acceptable training speed and realistic fuzzy system structure, these features are clustered without supervision using the Basic Isodata algorithm at the beginning of the training phase, and the clustering results are used in initializing the fuzzy system parameters. Afterwards, fuzzy rules in the system are trained with the back-propagation algorithm. The fuzzy approach was compared with an artificial neural network (ANN) method on four subjects, and very similar classification results were obtained. It is superior to the latter in at least three points: slightly higher recognition rate; insensitivity to overtraining; and consistent outputs demonstrating higher reliability. Some potential advantages of the fuzzy approach over the ANN approach are also discussed.published_or_final_versio

A new fuzzy approach for pattern recognition with application to EMG classification

A fuzzy logic system with center average defuzzifier, product-inference rule, nonsingleton fuzzifier and Gauss membership function is discussed. The fuzzy sets are initially defined by the cluster parameters from the Basic ISO-DATA algorithm on input space. The system is then trained via back error propagation algorithm so that the fuzzy sets are fine-tuned. The system is applied to functional EMG classification and compared with its ANN counterpart. It is superior to the latter in at least three points: higher recognition rate; insensitive to over-training; and more consistent outputs thus having higher reliability.published_or_final_versio

A new fuzzy classifier with triangular membership functions

Fuzzy logic is widely applied in control and modeling for its robustness, simplicity and clarity. It is also applied in classifier design with rules directly generated from numerical data. Some available rule generation methods, however, are either too complicated to implement or impractical for high dimensions. In this paper, we propose a new fuzzy classifier architecture. At the very beginning the training data is clustered at the input space. Fuzzy sets are then defined based on these clusters with triangular membership function. The outputs in the rule conclusion are initially determined by the “normalized vote” in the corresponding cluster. Fuzzy sets and conclusions can be adjusted through training. The proposed fuzzy system is simple in structure, and can be fast trained and easily implemented. Its classification performance is generally better than artificial neural network.published_or_final_versio