• Title/Summary/Keyword: T/S

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UNIFORMLY LIPSCHITZ STABILITY AND ASYMPTOTIC PROPERTY OF PERTURBED FUNCTIONAL DIFFERENTIAL SYSTEMS

  • Im, Dong Man;Goo, Yoon Hoe
    • Korean Journal of Mathematics
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    • v.24 no.1
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    • pp.1-13
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    • 2016
  • This paper shows that the solutions to the perturbed functional dierential system $$y^{\prime}=f(t,y)+{\int_{t_0}^{t}}g(s,y(s),Ty(s))ds$$ have uniformly Lipschitz stability and asymptotic property. To sRhow these properties, we impose conditions on the perturbed part ${\int_{t_0}^{t}}g(s,y(s),Ty(s))ds$ and the fundamental matrix of the unperturbed system $y^{\prime}=f(t,y)$.

AN ANALOGUE OF THE HILTON-MILNER THEOREM FOR WEAK COMPOSITIONS

  • Ku, Cheng Yeaw;Wong, Kok Bin
    • Bulletin of the Korean Mathematical Society
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    • v.52 no.3
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    • pp.1007-1025
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    • 2015
  • Let $\mathbb{N}_0$ be the set of non-negative integers, and let P(n, l) denote the set of all weak compositions of n with l parts, i.e., $P(n,l)=\{(x_1,x_2,{\cdots},x_l){\in}\mathbb{N}^l_0\;:\;x_1+x_2+{\cdots}+x_l=n\}$. For any element $u=(u_1,u_2,{\cdots},u_l){\in}P(n,l)$, denote its ith-coordinate by u(i), i.e., $u(i)=u_i$. A family $A{\subseteq}P(n,l)$ is said to be t-intersecting if ${\mid}\{i:u(i)=v(i)\}{\mid}{\geq}t$ for all $u,v{\epsilon}A$. A family $A{\subseteq}P(n,l)$ is said to be trivially t-intersecting if there is a t-set T of $[l]=\{1,2,{\cdots},l\}$ and elements $y_s{\in}\mathbb{N}_0(s{\in}T)$ such that $A=\{u{\in}P(n,l):u(j)=yj\;for\;all\;j{\in}T\}$. We prove that given any positive integers l, t with $l{\geq}2t+3$, there exists a constant $n_0(l,t)$ depending only on l and t, such that for all $n{\geq}n_0(l,t)$, if $A{\subseteq}P(n,l)$ is non-trivially t-intersecting, then $${\mid}A{\mid}{\leq}(^{n+l-t-l}_{l-t-1})-(^{n-1}_{l-t-1})+t$$. Moreover, equality holds if and only if there is a t-set T of [l] such that $$A=\bigcup_{s{\in}[l]{\backslash}T}\;A_s{\cup}\{q_i:i{\in}T\}$$, where $$A_s=\{u{\in}P(n,l):u(j)=0\;for\;all\;j{\in}T\;and\;u(s)=0\}$$ and $$q_i{\in}P(n,l)\;with\;q_i(j)=0\;fo\;all\;j{\in}[l]{\backslash}\{i\}\;and\;q_i(i)=n$$.

Trajectory Tracking Control of Mobile Robot using Multi-input T-S Fuzzy Feedback Linearization (다중 입력 T-S 퍼지 궤환 선형화 기법을 이용한 이동로봇의 궤도 추적 제어)

  • Hwang, Keun-Woo;Kim, Hyeon-Woo;Park, Seung-Kyu;Kwak, Gun-Pyong;Ahn, Ho-Kyun;Yoon, Tae-Sung
    • Journal of the Korea Institute of Information and Communication Engineering
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    • v.15 no.7
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    • pp.1447-1456
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    • 2011
  • In this paper, we propose a T-S fuzzy feedback linearization method for controlling a non-linear system with multi-input, and the method is applied for trajectory tracking control of wheeled mobile robot. First, an error dynamic equation of wheeled mobile robot is represented by a T-S fuzzy model, and then the T-S fuzzy model is transformed to a linear control system through the nonlinear fuzzy coordinate change and the nonlinear state feedback input. Simulation results showed that the trajectory tracking controller by using the proposed multi-input feedback linearization method gives better performance than the trajectory tracking controller by using the PDC(Parallel Distributed Compensation) method for controlling the T-S Fuzzy system.

Robust Control of IPMSM Using T-S Fuzzy Disturbance Observer (T-S 퍼지 외란 관측기를 이용한 IPMSM의 강인 제어)

  • Kim, Min-Chan;Li, Xiu-Kun;Park, Seung-Kyu;Kwak, Gun-Pyong;Ahn, Ho-Kyun;Yoon, Tae-Sung
    • Journal of the Korea Institute of Information and Communication Engineering
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    • v.19 no.4
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    • pp.973-983
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    • 2015
  • To improve the control performance of the IPMSM, a novel nonlinear disturbance observer is proposed by using the T-S fuzzy model. A T-S fuzzy model is the combination of local linear models considered at each operating point. Usually the inverse model is easy to obtain in linear systems but not in nonlinear systems. To design a nonlinear disturbance observer, a nonlinear inverse model is obtained based on nonlinear inverse model which is the fuzzy combination of the local linear inverse models. The proposed DOB is used with a PDC controller which is one of the T-S fuzzy controller, and its performance improvement is shown from the simulation results.

[r, s, t; f]-COLORING OF GRAPHS

  • Yu, Yong;Liu, Guizhen
    • Journal of the Korean Mathematical Society
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    • v.48 no.1
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    • pp.105-115
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    • 2011
  • Let f be a function which assigns a positive integer f(v) to each vertex v $\in$ V (G), let r, s and t be non-negative integers. An f-coloring of G is an edge-coloring of G such that each vertex v $\in$ V (G) has at most f(v) incident edges colored with the same color. The minimum number of colors needed to f-color G is called the f-chromatic index of G and denoted by ${\chi}'_f$(G). An [r, s, t; f]-coloring of a graph G is a mapping c from V(G) $\bigcup$ E(G) to the color set C = {0, 1, $\ldots$; k - 1} such that |c($v_i$) - c($v_j$ )| $\geq$ r for every two adjacent vertices $v_i$ and $v_j$, |c($e_i$ - c($e_j$)| $\geq$ s and ${\alpha}(v_i)$ $\leq$ f($v_i$) for all $v_i$ $\in$ V (G), ${\alpha}$ $\in$ C where ${\alpha}(v_i)$ denotes the number of ${\alpha}$-edges incident with the vertex $v_i$ and $e_i$, $e_j$ are edges which are incident with $v_i$ but colored with different colors, |c($e_i$)-c($v_j$)| $\geq$ t for all pairs of incident vertices and edges. The minimum k such that G has an [r, s, t; f]-coloring with k colors is defined as the [r, s, t; f]-chromatic number and denoted by ${\chi}_{r,s,t;f}$ (G). In this paper, we present some general bounds for [r, s, t; f]-coloring firstly. After that, we obtain some important properties under the restriction min{r, s, t} = 0 or min{r, s, t} = 1. Finally, we present some problems for further research.

State Feedback Linearization of Discrete-Time Nonlinear Systems via T-S Fuzzy Model (T-S 퍼지모델을 이용한 이산 시간 비선형계통의 상태 궤환 선형화)

  • Kim, Tae-Kue;Wang, Fa-Guang;Park, Seung-Kyu;Yoon, Tae-Sung;Ahn, Ho-Kyun;Kwak, Gun-Pyong
    • Journal of the Korean Institute of Intelligent Systems
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    • v.19 no.6
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    • pp.865-871
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    • 2009
  • In this paper, a novel feedback linearization is proposed for discrete-time nonlinear systems described by discrete-time T-S fuzzy models. The local linear models of a T-S fuzzy model are transformed to a controllable canonical form respectively, and their T-S fuzzy combination results in a feedback linearizable Tagaki-Sugeno fuzzy model. Based on this model, a nonlinear state feedback linearizing input is determined. Nonlinear state transformation is inferred from the linear state transformations for the controllable canonical forms. The proposed method of this paper is more intuitive and easier to understand mathematically compared to the well-known feedback linearization technique which requires a profound mathematical background. The feedback linearizable condition of this paper is also weakened compared to the conventional feedback linearization. This means that larger class of nonlinear systems is linearizable compared to the case of classical linearization.