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Stability of First and High Order Iterative Learning Control with Data Dropouts
Xuhui Bu,Zhongsheng Hou,Fashan Yu 제어·로봇·시스템학회 2011 International Journal of Control, Automation, and Vol.9 No.5
This paper presents a stability analysis of the iterative learning control (ILC) problem for discrete-time systems when the plants are subject to output measurement data dropouts. It is assumed that data dropout occurs during the data transfers from the plant to the ILC controller, resulting in what is called intermittent ILC. Using the super-vector approach for ILC, the expectation of output error is used to develop conditions for stability of the first order ILC and high order ILC processes. Through the theoretical analysis, it is shown that the convergence of the intermittent ILC is guaranteed although some measurements are missing. The analysis is also supported by numerical examples.
Formation Control of Mobile Robots with Input Constraints
Xiaohan Chen,Yingmin Jia,Junping Du,Fashan Yu 제어로봇시스템학회 2011 제어로봇시스템학회 국제학술대회 논문집 Vol.2011 No.10
This paper considers the problem of formation control for mobile robots which are subject to input constraints. The control strategy based on virtual robot tracking is proposed, which leads to a compact controller form in terms of two feedback parameters by Lyapunov method. The introduced elliptic approximation of input constraints brings much convenience to obtain suitable feedback parameters. It is show that the presented sufficient condition guarantees the existence of feasible feedback parameters. Moreover, guidelines for the selection of feedback parameters are provided with geometric analysis. Simulation results verify the effectiveness of the proposed control strategy.
Yang Liu,Yingmin Jia,Junping Du,Fashan Yu 제어로봇시스템학회 2009 제어로봇시스템학회 국제학술대회 논문집 Vol.2009 No.8
This paper is devoted to the consensus control for a network of autonomous agents with high-dimension linear coupling dynamics and subject to external disturbances. By transforming the consensus control problem into an H∞ control problem, we propose a distributed state feedback protocol, and obtain conditions in terms of linear matrix inequalities (LMIs) to ensure the consensus with a prescribed H∞ performance level for networks with zero and nonzero communication delays, respectively. Furthermore, the undetermined feedback matrix of the proposed protocol is also solved. A numerical example is included to validate the theoretical results.
Adaptive Multi-class Support Vector Machine for Microarray Classification and Gene Selection
Juntao Li,Yingmin Jia,Junping Du,Fashan Yu 제어로봇시스템학회 2009 제어로봇시스템학회 국제학술대회 논문집 Vol.2009 No.8
This paper proposes an adaptive multi-classs upport vector machine for simultaneous microarray classification and gene selection. By evaluating the gene ranking significance, the adaptive multi-class support vector machine is shown to encourage an adaptive grouping effect in the process of building classifiers, thus leading as parse multi-classifiers with enhanced interpretability. Based on a reasonablec orrelation between the two regularization parameters, an efficient solution path algorithm is developed for solving the proposed support vector machine. Experiments performed on the leukaemia data set are provided to verify the obtained results.