自适应控制——仿真实验三 用超稳定性理论设计模型参考自适应系统-三、问题求解
将原题中给定的参考模型和可调系统的传递函数写成输入输出方程的形式:
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\begin{gathered} &\left(0.08^{2} p^{2}+2 \times 0.08 \times 0.75 p+1\right) y_{m}=r \\ &\left(T_{1}^{2} p^{2}+2 T_{1} \xi_{1} p+1\right) y_{s f}=k_{1} r_{f} \end{gathered} \tag{17}
(0.082p2+2×0.08×0.75p+1)ym=r(T12p2+2T1ξ1p+1)ysf=k1rf(17)
再将上式写成首一古尔维兹多项式的形式:
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\begin{gathered} \left(p^{2}+\frac{2 \times 0.08 \times 0.75}{0.08^{2}} p+\frac{1}{0.08^{2}}\right) y_{m}=\frac{1}{0.08^{2}} r \\ \left(p^{2}+\frac{2 T_{1} \xi_{1}}{T_{1}^{2}}+\frac{1}{T_{1}^{2}}\right) y_{s f}=\frac{k_{1}}{T_{1}^{2}} r_{f} \end{gathered} \tag{18}
(p2+0.0822×0.08×0.75p+0.0821)ym=0.0821r(p2+T122T1ξ1+T121)ysf=T12k1rf(18)
对照(7)式和(11)式,可知相关参数如下:
a m 1 = 2 × 0.08 × 0.75 0.0 8 2 = 18.75 a m 0 = 1 0.0 8 2 = 156.25 b m 0 = 1 0.0 8 2 = 156.25 a s 1 ( v , t ) = 2 T 1 ( t ) ξ 1 ( t ) T 1 2 ( t ) = 2 ( 0.8 − 0.01 t ) ( 0.036 + 0.004 t ) a s 0 ( v , t ) = 1 T 1 2 ( t ) = 1 ( 0.036 + 0.004 t ) 2 b s 0 ( v , t ) = k 1 ( t ) T 1 2 ( t ) = 1.12 − 0.008 t ( 0.036 + 0.004 t ) 2 (19) \begin{aligned} &a_{m 1}=\frac{2 \times 0.08 \times 0.75}{0.08^{2}}=18.75 \\ &a_{m 0}=\frac{1}{0.08^{2}}=156.25 \\ &b_{m 0}=\frac{1}{0.08^{2}}=156.25 \\ &a_{s 1}(v, t)=\frac{2 T_{1}(t) \xi_{1}(t)}{T_{1}^{2}(t)}=\frac{2(0.8-0.01 t)}{(0.036+0.004 t)} \\ &a_{s 0}(v, t)=\frac{1}{T_{1}^{2}(t)}=\frac{1}{(0.036+0.004 t)^{2}} \\ &b_{s 0}(v, t)=\frac{k_{1}(t)}{T_{1}^{2}(t)}=\frac{1.12-0.008 t}{(0.036+0.004 t)^{2}} \end{aligned} \tag{19} am1=0.0822×0.08×0.75=18.75am0=0.0821=156.25bm0=0.0821=156.25as1(v,t)=T12(t)2T1(t)ξ1(t)=(0.036+0.004t)2(0.8−0.01t)as0(v,t)=T12(t)1=(0.036+0.004t)21bs0(v,t)=T12(t)k1(t)=(0.036+0.004t)21.12−0.008t(19)
进而可知, a s 1 ( 0 ) ≈ 44.4 a_{s 1}(0) \approx 44.4 as1(0)≈44.4, a s 0 ( 0 ) ≈ 771.6 a_{s 0}(0) \approx 771.6 as0(0)≈771.6, b s 0 ( 0 ) ≈ 864.2 b_{s 0}(0) \approx 864.2 bs0(0)≈864.2。
设输出的广义误差为
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\varepsilon_{f}=y_{m f}-y_{s f} \tag{20}
εf=ymf−ysf(20)
串联补偿器方程为
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v=D(p) \varepsilon_{f}=\left(d_{1} p+d_{0}\right) \varepsilon_{f} \tag{21}
v=D(p)εf=(d1p+d0)εf(21)
选取的自适应规律如下
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\begin{aligned} a_{s i}(v, t)&=\int_{0}^{t} \varphi_{1 i}(v, t, \tau) d \tau+\varphi_{2 i}(v, t)+a_{s i}(0), i=0,1 \\ b_{s 0}(v, t)&=\int_{0}^{t} \psi_{10}(v, t, \tau) d \tau+\psi_{20}(v, t)+b_{s 0}(0) \end{aligned} \tag{22}
asi(v,t)bs0(v,t)=∫0tφ1i(v,t,τ)dτ+φ2i(v,t)+asi(0),i=0,1=∫0tψ10(v,t,τ)dτ+ψ20(v,t)+bs0(0)(22)
参考(16)式的形式,可得可调参数的自适应规律如下:
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\begin{aligned} \varphi_{1 0}&=-k_{a 0}(t-\tau) v(\tau) y_{sf}(\tau), \quad \tau \le t \\ \varphi_{2 0}&=-k_{a 0}^{\prime}(t) v(t) y_{s f}(t) \\ \varphi_{1 1}&=-k_{a 1}(t-\tau) v(\tau) p y_{sf}(\tau), \quad \tau \le t \\ \varphi_{2 1}&=-k_{a 1}^{\prime}(t) v(t) p y_{s f}(t) \\ \psi_{1 0}&=k_{b 0}(t-\tau) v(\tau) r_{f}(\tau), \quad \tau \leqslant t \\ \psi_{2 0}&=k_{b 0}^{\prime}(t) v(t) r_{f}(t) \end{aligned} \tag{23}
φ10φ20φ11φ21ψ10ψ20=−ka0(t−τ)v(τ)ysf(τ),τ≤t=−ka0′(t)v(t)ysf(t)=−ka1(t−τ)v(τ)pysf(τ),τ≤t=−ka1′(t)v(t)pysf(t)=kb0(t−τ)v(τ)rf(τ),τ⩽t=kb0′(t)v(t)rf(t)(23)
式中, k a 0 ( t − τ ) k_{a 0}(t-\tau) ka0(t−τ)、 k a 1 ( t − τ ) k_{a 1}(t-\tau) ka1(t−τ) 和 k b 0 ( t − τ ) k_{b 0}(t-\tau) kb0(t−τ) 为正定积分核, k a 0 ′ ( t ) k_{a 0}^{\prime}(t) ka0′(t)、 k a 1 ′ ( t ) k_{a 1}^{\prime}(t) ka1′(t) 和 k b 0 ′ ( t ) k_{b 0}^{\prime}(t) kb0′(t) 对 ∀ t ≥ 0 \forall t \ge 0 ∀t≥0 均为非负标量增益。
下面再讨论一下引入的串联补偿器中的参数
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d1 的取值范围,系统的等价前向线性方块传递函数为:
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h(s)=\frac {d_1(s)+d_0} {s^2+a_{m1}s+a_{m0}} \tag{24}
h(s)=s2+am1s+am0d1(s)+d0(24)
其对应的能控标准型如下:
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\begin{aligned} \boldsymbol{\dot e} &= \boldsymbol{A_m} \boldsymbol{e} + b \omega_1 \\ v &= d^T \boldsymbol{e} \end{aligned} \tag{25}
e˙v=Ame+bω1=dTe(25)
式中,
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\boldsymbol{e}=\left[ \begin{matrix} \varepsilon \\ \dot \varepsilon \end{matrix} \right]
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\boldsymbol{A_m}=\left[ \begin{matrix} 0 & 1 \\ -a_{m0} & -a_{m1} \end{matrix} \right]
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d=\left[ \begin{matrix} d_0 \\ d_1 \end{matrix} \right]
d=[d0d1]。
要求
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h(s) 是一个严格正实传递函数,则必定存在正定对称矩阵
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\left\{ \begin{aligned} &P A_m + A_m^T P = -Q\\ &P b = d \end{aligned} \right. \tag{26}
{PAm+AmTP=−QPb=d(26)
由此可解得:
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d_0 > 0, \quad \frac {d_1} {d_0} > \frac {1} {a_{m_1}} =0.053 \tag{27}
d0>0,d0d1>am11=0.053(27)
最终搭建的仿真模型框图如 图1 所示:
具体的 Simulink 仿真文件我已上传至百度网盘中,链接如下:experiment_3.slx_免费高速下载|百度网盘-分享无限制 (baidu.com)
输入信号与广义输出误差信号如 图2 所示:
输入信号与增益信号如 图3 所示:
输入信号与可调参数1的变化曲线如 图4 所示:
输入信号与可调参数2的变化曲线如 图5 所示: