矩阵指数函数的性质

由矩阵指数函数的定义:
e A t = d e f I + A t + 1 2 ! A 2 t 2 + . . . = k = 0 1 k ! A k t k e^{At}\overset{def}{=}I+At+\frac{1}{2!}A^{2}t^{2}+...=\sum_{k=0}^{\infty}\frac{1}{k!}A^{k}t{^k}
可以得到以下一些基本性质:

  1. lim x 0 e A t = I \lim_{x\rightarrow 0}e^{At}=I

  1. t t τ \tau 为两个时间变量,则必成立:
    e A ( t + τ ) = e A t e A τ = e A τ e A t ( ) e^{A(t+\tau)}=e^{At}e^{A\tau}=e^{A\tau}e^{At} \\(可由数学归纳法证明)

  1. 矩阵指数函数的逆:
    ( e A t ) 1 = e A t : e A t e A t = e A ( t t ) = I (e^{At})^{-1}=e^{-At}\\ 证明: e^{At}e^{-At}=e^{A(t-t)}=I

  1. 矩阵指数函数 e A t e^{At} 对t求导为
    d d t ( e A t ) = A e A t = e A t A \frac{d}{dt}(e^{At})=Ae^{At}=e^{At}A
    证明:
    d d t ( e A t ) = A + A 2 t + 1 2 ! A 3 t 2 + . . . + 1 ( k 1 ) ! A k t k 1 = A ( I + A t + 1 2 ! A 2 t 2 + . . . 1 ( k 1 ) ! A k 1 t k 1 ) = A e A t = ( I + A t + 1 2 ! A 2 t 2 + . . . 1 ( k 1 ) ! A k 1 t k 1 ) A = e A t A ( A e A t ) \begin{aligned} \frac{d}{dt}(e^{At}) &=A+A^{2}t+\frac{1}{2!}A^{3}t^{2}+...+\frac{1}{(k-1)!}A^{k}t^{k-1}\\ &=A(I+At+\frac{1}{2!}A^{2}t^{2}+...\frac{1}{(k-1)!}A^{k-1}t^{k-1})=Ae^{At}\\ &=(I+At+\frac{1}{2!}A^{2}t^{2}+...\frac{1}{(k-1)!}A^{k-1}t^{k-1})A=e^{At}A\\ &(即矩阵A和矩阵指数函数e^{At}可交换) \end{aligned}

  1. 设有n*n维常阵 A A B B ,如果 A A B B 是可交换的,即 A B = B A AB=BA ,则必成立:
    e ( A + B ) t = e A t e B t = e B t e A t ( ) e^{(A+B)t}=e^{At}e^{Bt}=e^{Bt}e^{At}\\ (可由数学归纳法证明)

  1. 矩阵指数函数的积:
    ( e A t ) m = e A ( m t ) m = 0 , 1 , 2 , . . . ( 2 ) (e^{At})^m = e^{A(mt)} \qquad m=0,1,2,...\\ (可由性质2证明)
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