巴中市网站建设_网站建设公司_动画效果_seo优化

书籍：Matlab实用教程
工具：Matlab2021a
在线工具：https://www.cainiaojc.com/tool/octave/
缺少一些包
在线工具：https://octave-online.net/
比较健全。

电脑信息：Intel® Xeon® CPU E5-2603 v3 @ 1.60GHz

系统类型：64位操作系统，基于X64的处理器 windows10 专业版
第6章 线性控制系统分析与设计
6.5 线性系统的频域分析
6.5.1 频域特性

num=1; den=[1 1.414 1]; w=1; Gw=polyval(num,j*w)./polyval(den,j*w) Aw=abs(Gw) Fw=angle(Gw)

Gw = 0 - 0.7072i Aw = 0.7072 Fw = -1.5708

6.5.2 连续系统频域分析
1、bode图

num=1; den=conv([1 1],[1,2]) G=tf(num,[den 0]) bode(G)

den = 1 3 2 Transfer function 'G' from input 'u1' to output ... 1 y1: ----------------- s^3 + 3 s^2 + 2 s Continuous-time model.

num=1; den=conv([1 1],[1,2]) w=logspace(-1,2); [m,p]=bode(num,den,w); subplot(2,1,1) semilogx(w,20*log10(m)) subplot(2,1,2) semilogx(w,p)

den = 1 3 2 error: bode: require at least one LTI model error: called from __frequency_response__ at line 65 column 5 bode at line 66 column 40

2、nyquist曲线

num=1; den1=[conv([1 1],[1,2]),0]; G1=tf(num,den1)

Transfer function 'G1' from input 'u1' to output ... 1 y1: ----------------- s^3 + 3 s^2 + 2 s Continuous-time model.

den2=[conv([1 1],[1 2])]; G2=tf(num,den2)

G2=tf(num,den2) Transfer function 'G2' from input 'u1' to output ... 1 y1: ------------- s^2 + 3 s + 2 Continuous-time model.

den3=[1 1 0]; G3=tf(num,den3)

Transfer function 'G3' from input 'u1' to output ... 1 y1: ------- s^2 + s Continuous-time model.

nyquist(G1,'r',G2,'b:',G3,'g-.',{0.1,180/57.3})

w=1:2; [re,im]=nyquist(G1,w)

re = -0.300000 -0.075000 im = -0.100000 0.025000

3、nichols图

ngrid('nichols1') nichols(G1)

w=1:2; [Mag,Phs]=nichols(G1,w)

Mag = 0.316228 0.079057 Phs = -161.57 -198.43

6.5.3 幅值裕度和相角裕度

G1

Transfer function 'G1' from input 'u1' to output ... 1 y1: ----------------- s^3 + 3 s^2 + 2 s Continuous-time model.

[Gm,Pm,Wcg,Wcp]=margin(G1)

Gm = 6.0000 Pm = 53.411 Wcg = 1.4142 Wcp = 0.4457

6.5.4 离散系统频域分析

dnum=[2 5 1]; dden=[1 2 3]; dbode(dnum,dden,0.1)

error: 'dbode' undefined near line 1, column 1

6.6 线性系统的根轨迹分析
6.6.1 绘制根轨迹
1、常规根轨迹

num=1; den=[conv([1,4],conv([1 -2+4i],[1 -2-4i])),0] G=tf(num,den) rlocus(G) [r,K]=rlocus(G)

den = 1 0 4 80 0 Transfer function 'G' from input 'u1' to output ... 1 y1: ------------------ s^4 + 4 s^2 + 80 s Continuous-time model.

[r,K]=rlocus(G)

r = Columns 1 through 4: -4.0000 + 0i -3.9583 + 0i -3.9148 + 0i -3.8694 + 0i 0 + 0i -0.1068 + 0i -0.2148 + 0i -0.3241 + 0i 2.0000 - 4.0000i 2.0326 - 3.9964i 2.0648 - 3.9937i 2.0967 - 3.9919i 2.0000 + 4.0000i 2.0326 + 3.9964i 2.0648 + 3.9937i 2.0967 + 3.9919i Columns 5 through 8: -3.8217 + 0i -3.7715 + 0i -3.7184 + 0i -3.6620 + 0i -0.4348 + 0i -0.5472 + 0i -0.6617 + 0i -0.7785 + 0i 2.1283 - 3.9908i 2.1594 - 3.9906i 2.1900 - 3.9911i 2.2202 - 3.9922i 2.1283 + 3.9908i 2.1594 + 3.9906i 2.1900 + 3.9911i 2.2202 + 3.9922i Columns 9 through 12: -3.6016 + 0i -3.5364 + 0i -3.4654 + 0i -3.3869 + 0i -0.8983 + 0i -1.0219 + 0i -1.1504 + 0i -1.2852 + 0i 2.2499 - 3.9939i 2.2792 - 3.9962i 2.3079 - 3.9990i 2.3361 - 4.0023i 2.2499 + 3.9939i 2.2792 + 3.9962i 2.3079 + 3.9990i 2.3361 + 4.0023i Columns 13 through 16: -3.2985 + 0i -3.1961 + 0i -3.0715 + 0i -3.0351 + 0i -1.4290 + 0i -1.5858 + 0i -1.7637 + 0i -1.8134 + 0i 2.3638 - 4.0061i 2.3909 - 4.0102i 2.4176 - 4.0147i 2.4242 - 4.0158i 2.3638 + 4.0061i 2.3909 + 4.0102i 2.4176 + 4.0147i 2.4242 + 4.0158i Columns 17 through 20: -2.9956 + 0i -2.9522 + 0i -2.9038 + 0i -2.8481 + 0i -1.8660 + 0i -1.9224 + 0i -1.9839 + 0i -2.0525 + 0i 2.4308 - 4.0170i 2.4373 - 4.0182i 2.4438 - 4.0195i 2.4503 - 4.0207i 2.4308 + 4.0170i 2.4373 + 4.0182i 2.4438 + 4.0195i 2.4503 + 4.0207i Columns 21 through 24: -2.7811 + 0i -2.6922 + 0i -2.6631 + 0i -2.6282 + 0i -2.1324 + 0i -2.2341 + 0i -2.2664 + 0i -2.3045 + 0i 2.4567 - 4.0220i 2.4632 - 4.0233i 2.4648 - 4.0236i 2.4664 - 4.0239i 2.4567 + 4.0220i 2.4632 + 4.0233i 2.4648 + 4.0236i 2.4664 + 4.0239i Columns 25 through 28: -2.5824 + 0i -2.4695 - 0.0000i -2.4725 - 0.1556i -2.4754 - 0.2199i -2.3535 + 0i -2.4695 + 0.0000i -2.4725 + 0.1556i -2.4754 + 0.2199i 2.4680 - 4.0243i 2.4695 - 4.0246i 2.4725 - 4.0252i 2.4754 - 4.0258i 2.4680 + 4.0243i 2.4695 + 4.0246i 2.4725 + 4.0252i 2.4754 + 4.0258i Columns 29 through 32: -2.4784 - 0.2692i -2.4813 - 0.3106i -2.4929 - 0.4382i -2.5045 - 0.5355i -2.4784 + 0.2692i -2.4813 + 0.3106i -2.4929 + 0.4382i -2.5045 + 0.5355i 2.4784 - 4.0264i 2.4813 - 4.0270i 2.4929 - 4.0296i 2.5045 - 4.0321i 2.4784 + 4.0264i 2.4813 + 4.0270i 2.4929 + 4.0296i 2.5045 + 4.0321i Columns 33 through 36: -2.5159 - 0.6169i -2.5273 - 0.6881i -2.5385 - 0.7520i -2.5497 - 0.8104i -2.5159 + 0.6169i -2.5273 + 0.6881i -2.5385 + 0.7520i -2.5497 + 0.8104i 2.5159 - 4.0348i 2.5273 - 4.0374i 2.5385 - 4.0401i 2.5497 - 4.0429i 2.5159 + 4.0348i 2.5273 + 4.0374i 2.5385 + 4.0401i 2.5497 + 4.0429i Columns 37 through 40: -2.5607 - 0.8644i -2.6041 - 1.0492i -2.6460 - 1.2010i -2.6865 - 1.3315i -2.5607 + 0.8644i -2.6041 + 1.0492i -2.6460 + 1.2010i -2.6865 + 1.3315i 2.5607 - 4.0457i 2.6041 - 4.0573i 2.6460 - 4.0694i 2.6865 - 4.0819i 2.5607 + 4.0457i 2.6041 + 4.0573i 2.6460 + 4.0694i 2.6865 + 4.0819i Columns 41 through 44: -2.7258 - 1.4466i -2.7639 - 1.5501i -2.8008 - 1.6443i -2.8366 - 1.7309i -2.7258 + 1.4466i -2.7639 + 1.5501i -2.8008 + 1.6443i -2.8366 + 1.7309i 2.7258 - 4.0948i 2.7639 - 4.1079i 2.8008 - 4.1213i 2.8366 - 4.1349i 2.7258 + 4.0948i 2.7639 + 4.1079i 2.8008 + 4.1213i 2.8366 + 4.1349i Columns 45 through 48: -2.8715 - 1.8111i -2.9053 - 1.8860i -2.9382 - 1.9562i -2.9703 - 2.0222i -2.8715 + 1.8111i -2.9053 + 1.8860i -2.9382 + 1.9562i -2.9703 + 2.0222i 2.8715 - 4.1485i 2.9053 - 4.1623i 2.9382 - 4.1761i 2.9703 - 4.1900i 2.8715 + 4.1485i 2.9053 + 4.1623i 2.9382 + 4.1761i 2.9703 + 4.1900i Columns 49 through 52: -3.0016 - 2.0847i -3.0320 - 2.1440i -3.0617 - 2.2005i -3.0908 - 2.2543i -3.0016 + 2.0847i -3.0320 + 2.1440i -3.0617 + 2.2005i -3.0908 + 2.2543i 3.0016 - 4.2039i 3.0320 - 4.2178i 3.0617 - 4.2316i 3.0908 - 4.2454i 3.0016 + 4.2039i 3.0320 + 4.2178i 3.0617 + 4.2316i 3.0908 + 4.2454i Columns 53 through 56: -3.1191 - 2.3058i -3.1468 - 2.3552i -3.1739 - 2.4026i -3.2004 - 2.4482i -3.1191 + 2.3058i -3.1468 + 2.3552i -3.1739 + 2.4026i -3.2004 + 2.4482i 3.1191 - 4.2592i 3.1468 - 4.2729i 3.1739 - 4.2866i 3.2004 - 4.3002i 3.1191 + 4.2592i 3.1468 + 4.2729i 3.1739 + 4.2866i 3.2004 + 4.3002i Columns 57 through 60: -3.2264 - 2.4921i -3.2518 - 2.5345i -3.2767 - 2.5755i -3.3717 - 2.7270i -3.2264 + 2.4921i -3.2518 + 2.5345i -3.2767 + 2.5755i -3.3717 + 2.7270i 3.2264 - 4.3137i 3.2518 - 4.3272i 3.2767 - 4.3406i 3.3717 - 4.3932i 3.2264 + 4.3137i 3.2518 + 4.3272i 3.2767 + 4.3406i 3.3717 + 4.3932i Columns 61 through 64: -3.4601 - 2.8622i -3.5428 - 2.9843i -3.6205 - 3.0958i -3.6939 - 3.1985i -3.4601 + 2.8622i -3.5428 + 2.9843i -3.6205 + 3.0958i -3.6939 + 3.1985i 3.4601 - 4.4444i 3.5428 - 4.4940i 3.6205 - 4.5423i 3.6939 - 4.5890i 3.4601 + 4.4444i 3.5428 + 4.4940i 3.6205 + 4.5423i 3.6939 + 4.5890i Columns 65 through 68: -3.7635 - 3.2939i -3.8297 - 3.3830i -3.8929 - 3.4665i -3.9533 - 3.5454i -3.7635 + 3.2939i -3.8297 + 3.3830i -3.8929 + 3.4665i -3.9533 + 3.5454i 3.7635 - 4.6345i 3.8297 - 4.6786i 3.8929 - 4.7215i 3.9533 - 4.7632i 3.7635 + 4.6345i 3.8297 + 4.6786i 3.8929 + 4.7215i 3.9533 + 4.7632i Columns 69 through 72: -4.0112 - 3.6199i -4.0743 - 3.7001i -4.1346 - 3.7760i -4.1926 - 3.8481i -4.0112 + 3.6199i -4.0743 + 3.7001i -4.1346 + 3.7760i -4.1926 + 3.8481i 4.0112 - 4.8037i 4.0743 - 4.8485i 4.1346 - 4.8921i 4.1926 - 4.9344i 4.0112 + 4.8037i 4.0743 + 4.8485i 4.1346 + 4.8921i 4.1926 + 4.9344i Columns 73 through 76: -4.2484 - 3.9168i -4.3022 - 3.9824i -4.3541 - 4.0453i -4.4043 - 4.1057i -4.2484 + 3.9168i -4.3022 + 3.9824i -4.3541 + 4.0453i -4.4043 + 4.1057i 4.2484 - 4.9756i 4.3022 - 5.0157i 4.3541 - 5.0548i 4.4043 - 5.0930i 4.2484 + 4.9756i 4.3022 + 5.0157i 4.3541 + 5.0548i 4.4043 + 5.0930i Columns 77 through 80: -4.4529 - 4.1638i -4.5001 - 4.2197i -4.5458 - 4.2737i -4.5903 - 4.3260i -4.4529 + 4.1638i -4.5001 + 4.2197i -4.5458 + 4.2737i -4.5903 + 4.3260i 4.4529 - 5.1303i 4.5001 - 5.1667i 4.5458 - 5.2023i 4.5903 - 5.2372i 4.4529 + 5.1303i 4.5001 + 5.1667i 4.5458 + 5.2023i 4.5903 + 5.2372i Columns 81 through 84: -4.6336 - 4.3765i -4.6757 - 4.4255i -4.7168 - 4.4730i -4.7568 - 4.5192i -4.6336 + 4.3765i -4.6757 + 4.4255i -4.7168 + 4.4730i -4.7568 + 4.5192i 4.6336 - 5.2713i 4.6757 - 5.3047i 4.7168 - 5.3374i 4.7568 - 5.3695i 4.6336 + 5.2713i 4.6757 + 5.3047i 4.7168 + 5.3374i 4.7568 + 5.3695i Columns 85 through 88: -4.7959 - 4.5641i -4.8342 - 4.6078i -4.8715 - 4.6504i -4.9080 - 4.6919i -4.7959 + 4.5641i -4.8342 + 4.6078i -4.8715 + 4.6504i -4.9080 + 4.6919i 4.7959 - 5.4010i 4.8342 - 5.4320i 4.8715 - 5.4623i 4.9080 - 5.4922i 4.7959 + 5.4010i 4.8342 + 5.4320i 4.8715 + 5.4623i 4.9080 + 5.4922i Columns 89 through 92: -4.9438 - 4.7324i -4.9788 - 4.7720i -5.0132 - 4.8107i -5.0468 - 4.8485i -4.9438 + 4.7324i -4.9788 + 4.7720i -5.0132 + 4.8107i -5.0468 + 4.8485i 4.9438 - 5.5215i 4.9788 - 5.5503i 5.0132 - 5.5787i 5.0468 - 5.6066i 4.9438 + 5.5215i 4.9788 + 5.5503i 5.0132 + 5.5787i 5.0468 + 5.6066i Columns 93 through 96: -5.0799 - 4.8855i -5.2061 - 5.0261i -5.3239 - 5.1563i -5.4346 - 5.2778i -5.0799 + 4.8855i -5.2061 + 5.0261i -5.3239 + 5.1563i -5.4346 + 5.2778i 5.0799 - 5.6340i 5.2061 - 5.7398i 5.3239 - 5.8396i 5.4346 - 5.9343i 5.0799 + 5.6340i 5.2061 + 5.7398i 5.3239 + 5.8396i 5.4346 + 5.9343i Columns 97 through 100: -5.5391 - 5.3918i -5.6381 - 5.4992i -5.7323 - 5.6009i -5.8221 - 5.6976i -5.5391 + 5.3918i -5.6381 + 5.4992i -5.7323 + 5.6009i -5.8221 + 5.6976i 5.5391 - 6.0243i 5.6381 - 6.1103i 5.7323 - 6.1926i 5.8221 - 6.2716i 5.5391 + 6.0243i 5.6381 + 6.1103i 5.7323 + 6.1926i 5.8221 + 6.2716i Columns 101 through 104: -5.9081 - 5.7897i -5.9905 - 5.8777i -6.0697 - 5.9621i -6.1460 - 6.0431i -5.9081 + 5.7897i -5.9905 + 5.8777i -6.0697 + 5.9621i -6.1460 + 6.0431i 5.9081 - 6.3475i 5.9905 - 6.4207i 6.0697 - 6.4913i 6.1460 - 6.5595i 5.9081 + 6.3475i 5.9905 + 6.4207i 6.0697 + 6.4913i 6.1460 + 6.5595i Columns 105 through 108: -6.2196 - 6.1211i -6.2907 - 6.1963i -6.3595 - 6.2689i -6.4262 - 6.3391i -6.2196 + 6.1211i -6.2907 + 6.1963i -6.3595 + 6.2689i -6.4262 + 6.3391i 6.2196 - 6.6256i 6.2907 - 6.6897i 6.3595 - 6.7519i 6.4262 - 6.8124i 6.2196 + 6.6256i 6.2907 + 6.6897i 6.3595 + 6.7519i 6.4262 + 6.8124i Columns 109 through 112: -6.4910 - 6.4071i -6.5538 - 6.4731i -6.6150 - 6.5371i -6.6745 - 6.5994i -6.4910 + 6.4071i -6.5538 + 6.4731i -6.6150 + 6.5371i -6.6745 + 6.5994i 6.4910 - 6.8712i 6.5538 - 6.9285i 6.6150 - 6.9844i 6.6745 - 7.0388i 6.4910 + 6.8712i 6.5538 + 6.9285i 6.6150 + 6.9844i 6.6745 + 7.0388i Columns 113 through 116: -6.7325 - 6.6600i -6.7890 - 6.7190i -6.8442 - 6.7765i -6.8981 - 6.8326i -6.7325 + 6.6600i -6.7890 + 6.7190i -6.8442 + 6.7765i -6.8981 + 6.8326i 6.7325 - 7.0920i 6.7890 - 7.1440i 6.8442 - 7.1948i 6.8981 - 7.2445i 6.7325 + 7.0920i 6.7890 + 7.1440i 6.8442 + 7.1948i 6.8981 + 7.2445i Columns 117 through 120: -6.9508 - 6.8874i -7.0023 - 6.9409i -7.0528 - 6.9933i -7.1021 - 7.0445i -6.9508 + 6.8874i -7.0023 + 6.9409i -7.0528 + 6.9933i -7.1021 + 7.0445i 6.9508 - 7.2932i 7.0023 - 7.3409i 7.0528 - 7.3876i 7.1021 - 7.4335i 6.9508 + 7.2932i 7.0023 + 7.3409i 7.0528 + 7.3876i 7.1021 + 7.4335i Columns 121 through 124: -7.1505 - 7.0946i -7.1980 - 7.1437i -7.2445 - 7.1918i -7.2902 - 7.2390i -7.1505 + 7.0946i -7.1980 + 7.1437i -7.2445 + 7.1918i -7.2902 + 7.2390i 7.1505 - 7.4784i 7.1980 - 7.5226i 7.2445 - 7.5660i 7.2902 - 7.6086i 7.1505 + 7.4784i 7.1980 + 7.5226i 7.2445 + 7.5660i 7.2902 + 7.6086i Columns 125 through 128: -7.3350 - 7.2853i -7.3791 - 7.3308i -7.4223 - 7.3754i -7.4649 - 7.4192i -7.3350 + 7.2853i -7.3791 + 7.3308i -7.4223 + 7.3754i -7.4649 + 7.4192i 7.3350 - 7.6504i 7.3791 - 7.6916i 7.4223 - 7.7321i 7.4649 - 7.7720i 7.3350 + 7.6504i 7.3791 + 7.6916i 7.4223 + 7.7321i 7.4649 + 7.7720i Columns 129 through 132: -7.5067 - 7.4623i -7.5479 - 7.5047i -7.5883 - 7.5464i -7.6282 - 7.5873i -7.5067 + 7.4623i -7.5479 + 7.5047i -7.5883 + 7.5464i -7.6282 + 7.5873i 7.5067 - 7.8112i 7.5479 - 7.8498i 7.5883 - 7.8879i 7.6282 - 7.9254i 7.5067 + 7.8112i 7.5479 + 7.8498i 7.5883 + 7.8879i 7.6282 + 7.9254i Columns 133 through 136: -7.6675 - 7.6277i -7.7061 - 7.6674i -7.7442 - 7.7065i -7.7818 - 7.7451i -7.6675 + 7.6277i -7.7061 + 7.6674i -7.7442 + 7.7065i -7.7818 + 7.7451i 7.6675 - 7.9623i 7.7061 - 7.9988i 7.7442 - 8.0347i 7.7818 - 8.0701i 7.6675 + 7.9623i 7.7061 + 7.9988i 7.7442 + 8.0347i 7.7818 + 8.0701i Columns 137 through 140: -7.8188 - 7.7831i -7.8553 - 7.8205i -7.8914 - 7.8574i -7.9269 - 7.8938i -7.8188 + 7.7831i -7.8553 + 7.8205i -7.8914 + 7.8574i -7.9269 + 7.8938i 7.8188 - 8.1051i 7.8553 - 8.1396i 7.8914 - 8.1736i 7.9269 - 8.2072i 7.8188 + 8.1051i 7.8553 + 8.1396i 7.8914 + 8.1736i 7.9269 + 8.2072i Columns 141 through 144: -7.9620 - 7.9298i -7.9966 - 7.9652i -8.0308 - 8.0002i -8.1633 - 8.1357i -7.9620 + 7.9298i -7.9966 + 7.9652i -8.0308 + 8.0002i -8.1633 + 8.1357i 7.9620 - 8.2404i 7.9966 - 8.2732i 8.0308 - 8.3056i 8.1633 - 8.4315i 7.9620 + 8.2404i 7.9966 + 8.2732i 8.0308 + 8.3056i 8.1633 + 8.4315i Columns 145 through 148: -8.2898 - 8.2649i -8.4108 - 8.3883i -8.5268 - 8.5065i -8.6383 - 8.6200i -8.2898 + 8.2649i -8.4108 + 8.3883i -8.5268 + 8.5065i -8.6383 + 8.6200i 8.2898 - 8.5518i 8.4108 - 8.6671i 8.5268 - 8.7779i 8.6383 - 8.8846i 8.2898 + 8.5518i 8.4108 + 8.6671i 8.5268 + 8.7779i 8.6383 + 8.8846i Columns 149 through 152: -8.7457 - 8.7293i -8.8493 - 8.8346i -8.9494 - 8.9363i -9.0463 - 9.0346i -8.7457 + 8.7293i -8.8493 + 8.8346i -8.9494 + 8.9363i -9.0463 + 9.0346i 8.7457 - 8.9874i 8.8493 - 9.0868i 8.9494 - 9.1829i 9.0463 - 9.2761i 8.7457 + 8.9874i 8.8493 + 9.0868i 8.9494 + 9.1829i 9.0463 + 9.2761i Columns 153 through 156: -9.1402 - 9.1299i -9.2313 - 9.2223i -9.3198 - 9.3120i -9.4059 - 9.3992i -9.1402 + 9.1299i -9.2313 + 9.2223i -9.3198 + 9.3120i -9.4059 + 9.3992i 9.1402 - 9.3665i 9.2313 - 9.4543i 9.3198 - 9.5396i 9.4059 - 9.6227i 9.1402 + 9.3665i 9.2313 + 9.4543i 9.3198 + 9.5396i 9.4059 + 9.6227i Column 157: -9.4897 - 9.4840i -9.4897 + 9.4840i 9.4897 - 9.7037i 9.4897 + 9.7037i K = 135.98

2、零度根轨迹

num=[-1 -2]; den=conv([1 3],[1 2 3]); G=tf(num,den) rlocus(G)

Transfer function 'G' from input 'u1' to output ... -s - 2 y1: --------------------- s^3 + 5 s^2 + 9 s + 9 Continuous-time model.

6.6.2 根轨迹的其它工具
1、指定点的开环增益

[K,p]=rlocfind(G)

error: 'rlocfind' undefined near line 1, column 7

2、主导极点的等ζ线和等wn线

num=1; den=[conv([1,1],[1 2]),0] G1=tf(num,den) rlocus(G1) sgrid(0.707,10)

[K,p]=rlocfind(G1)

error: 'rlocfind' undefined near line 1, column 7

G=feedback(0.6233*G1,1)

Transfer function 'G' from input 'u1' to output ... 0.6233 y1: -------------------------- s^3 + 3 s^2 + 2 s + 0.6233 Continuous-time model.

3、系统根轨迹的设计工具rltool

num=1; a=[1 0]; b=[1 4]; c=[1 4 20]; den=conv(a,b); den=conv(den,c); G=tf(num,den); rltool(G)

error: 'rltool' undefined near line 1, column 1

6.7 线性系统的状态空间设计
6.7.1 极点配置法
1、单输入系统的极点配置

A=[0 1 0;0 0 1;-1 -5 -6]; B=[0;0;1]; P=[-2+2j -2-2j -10]; K=acker(A,B,P)

K = 79 43 8

2、多输入系统的极点配置
3、离散系统的极点配置
6.7.2 最优二次型设计
1、连续系统最优二次型设计

a=[0 1 0;0 0 1;-35 -27 -9]; b=[0;0;1]; q=eye(3); r=1; [k,p,e]=lqr(a,b,q,r)

k = 0.014283 0.110723 0.067604 p = 4.262533 2.495659 0.014283 2.495659 2.815027 0.110723 0.014283 0.110723 0.067604 e = -5.0958 + 0i -1.9859 + 1.7110i -1.9859 - 1.7110i

2、离散系统最优二次型设计
3、对输出加权的最优二次型设计