离散线性系统能控性与能观性

离散线型系统

状态方程
x t + 1 = A x t + B u t \begin{array}{ll} x_{t+1} = Ax_t+Bu_t \end{array}
输出方程
y t + 1 = C x t + 1 + D u t \begin{array}{ll} y_{t+1} = Cx_{t+1}+Du_{t} \end{array}
A R n × n , B R n × m , C R o × n , D R o × m , A\in R^{n\times n}, B\in R^{n\times m}, C\in R^{o\times n},D\in R^{o\times m},
x R n , u R m , y R o . x\in R^n, u\in R^m, y\in R^o.

能控性

能控性:可以通过控制输入 u u ,使得系统状态从任意初始状态 x 0 x_0 到达任意终止状态 x t . x_t.


x 1 = A x 0 + B u 0 , x 2 = A x 1 + B u 1 = A ( A x 0 + B u 0 ) + B u 1 = A 2 x 0 + A B u 0 + B u 1 , x t = A t x 0 + [ A t 1 B A B B ] [ u 0 u t 1 ] \begin{array}{ll} x_1 &= Ax_0 + Bu_0, \\ x_2 &= Ax_1 + Bu_1 = A(Ax_0 + Bu_0) + Bu_1 = A^2x_0 + ABu_0 + Bu_1,\\ &\ldots \\ x_t &= A^tx_0 + \left[ \begin{array}{llll} A^{t-1}B &\cdots &AB &B \end{array} \right] \left[ \begin{array}{c} u_0\\ \vdots\\ u_{t-1} \end{array} \right] \end{array}

要使 x t x_t 到达任意状态,必须有 C [ A t 1 B A B B ] C \triangleq \left[ \begin{array}{llll} A^{t-1}B &\cdots &AB &B \end{array} \right] 行满秩.

有哈密顿凯莱定理可知
r a n k ( [ A t 1 B A B B ] ) = r a n k ( [ A n 1 B A B B ] ) rank(\left[ \begin{array}{llll} A^{t-1}B &\cdots &AB &B \end{array} \right])= rank(\left[ \begin{array}{llll} A^{n-1}B &\cdots &AB &B \end{array} \right])
所以能控性充要条件为:
r a n k ( [ A n 1 B A B B ] ) = n rank(\left[ \begin{array}{llll} A^{n-1}B &\cdots &AB &B \end{array} \right]) =n

能观性

能观性:系统的当前状态 x 0 x_0 可以由有限时间[t_0, t]内的输入输出完全确定.


y 0 = C x 0 + D u 0 , y t = C x t + D u t = C ( A t x 0 + [ A t 1 B A B B ] [ u 0 u t 1 ] ) + D u t \begin{array}{ll} y_0 &= Cx_0 + Du_0, \\ & \vdots \\ y_t &= Cx_t + Du_t\\ &=C\left( A^tx_0 + \left[ \begin{array}{llll} A^{t-1}B &\cdots &AB &B \end{array} \right] \left[ \begin{array}{c} u_0\\ \vdots\\ u_{t-1} \end{array} \right]\right) +D u_t \end{array}

y 0 D u 0 = C x 0 , y t [ C A t 1 B C A B C B ] [ u 0 u t 1 ] D u t = C A t x 0 \begin{array}{ll} y_0 - Du_0&= Cx_0 , \\ & \vdots \\ y_t - \left[ \begin{array}{llll} CA^{t-1}B &\cdots &CAB &CB \end{array} \right] \left[ \begin{array}{c} u_0\\ \vdots\\ u_{t-1} \end{array} \right] -D u_t&= CA^tx_0 \end{array}

[ y 0 D u 0 y t C A t 1 B u 0 C A B u t 2 C B u t 1 D u t ] = [ C C A t ] x 0 \left[ \begin{array}{c} y_0 - Du_0\\ \vdots \\ y_t - CA^{t-1}Bu_0 -\cdots -CABu_{t-2} -CBu_{t-1} -D u_t& \end{array} \right]= \left[ \begin{array}{c} C\\ \vdots \\ CA^t \end{array} \right]x_0
上式的左端已知,为唯一确定出 x 0 x_0 ,必须有 [ C C A t ] \left[ \begin{array}{c} C\\ \vdots \\ CA^t \end{array} \right] 列满秩.

由哈密顿凯莱定理, t n 1 t\geq n-1 时,
r a n k ( [ C C A t ] ) = r a n k ( [ C C A n 1 ] ) rank(\left[ \begin{array}{c} C\\ \vdots \\ CA^t \end{array} \right])= rank(\left[ \begin{array}{c} C\\ \vdots \\ CA^{n-1} \end{array} \right])
所以系统能观的充要条件为: r a n k ( [ C C A n 1 ] ) = n rank(\left[ \begin{array}{c} C\\ \vdots \\ CA^{n-1} \end{array} \right])=n

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