faizul ikhsan 12518241005.docx

Laporan Praktikum SISTEM KENDALI CERDASCrisp Sets and Fuzzy SetsOleh:Faizul Ikhsan (12518241005)

I. TujuanDapat mengetahui perbedaan fuzzy set dan crips setII. Hasil dan AnalisisDeskripsikan hasil yang diperoleh beserta analisisnyaa. Contradiction and Excluded Middle%tuliskan kode program di sini%Contradiction and Excluded Middle figure (2)clfhold on subplot(221)plot(x,A,'--',x,1-A,'-.',x,min(A,1-A),'r');axis ([-inf inf 0 1.2]);title('A And (Not A)');%set (gca, 'xtick',[0 10 20 30]);%text (13,1.1,'A');text(60,1.1,'Not A'); subplot(222)plot(x,Az,'--',x,1-Az,'-.',x,min(Az,1-Az),'r');axis ([-inf inf 0 1.2]);title('A And (Not A)');%set (gca, 'xtick',[0 10 20 30]);%text (13,1.1,'A');text(60,1.1,'Not A'); subplot(223)plot(x,A,'--',x,1-A,'-.',x,max(A,1-A),'r');axis ([-inf inf 0 1.2]);title('A Or (Not A)');%set (gca, 'xtick',[0 10 20 30]);%text (13,1.1,'A');text(60,1.1,'Not A'); subplot(224)plot(x,Az,'--',x,1-Az,'-.',x,max(Az,1-Az),'r');axis ([-inf inf 0 1.2]);title('A OR (Not A)');%set (gca, 'xtick',[0 10 20 30]);%text (13,1.1,'A');text(60,1.1,'Not A'); hold off

tampilkan gambar seperti berikut ini:

Gambar 1 Grafik hasil simulasi MATLABtambahkan perhitungan bila perlu1. Contradiction = 2. Excluded Middle = b. Idempotency%Model regresi ARX dengan metode Least Square yang diukur secara offline%idempotencyfigure (3)clfhold on subplot(221)plot(x,A,'b',x,Az,'r');axis([-inf inf 0 1.2]);title ('A');%set (gca,'xtick',[0 10 20 30]); subplot(222)plot(x,min(A,A),'b',x,min(Az,Az),'r');axis([-inf inf 0 1.2]);title ('A And A');%set (gca,'xtick',[0 10 20 30]); subplot(223)plot(x,max(A,A),'b',x,max(Az,Az),'r');axis([-inf inf 0 1.2]);title ('A Or A');%set (gca,'xtick',[0 10 20 30]); subplot(224)plot(x,1-(1-A),'b',x,1-(1-Az),'r');axis([-inf inf 0 1.2]);title ('A (Not A)');%set (gca,'xtick',[0 10 20 30]); hold off

c. Commutative%Model regresi ARX dengan metode Least Square yang diukur secara offlinefigure (4)clfhold on subplot (221)plot(x,min(A,B),'b',x,min(Az,Bz),'r');axis([-inf inf 0 1.2]);title('A And B');%set (gca,'xtick',[0 10 20 30]}; subplot (222)plot(x,min(B,A),'b',x,min(Bz,Az),'r');axis([-inf inf 0 1.2]);title('B And A');%set (gca,'xtick',[0 10 20 30]}; subplot (223)plot(x,max(A,B),'b',x,max(Az,Bz),'r');axis([-inf inf 0 1.2]);title('A Or B');%set (gca,'xtick',[0 10 20 30]}; subplot (224)plot(x,max(B,A),'b',x,max(Bz,Az),'r');axis([-inf inf 0 1.2]);title('B Or A');%set (gca,'xtick',[0 10 20 30]}; hold off

d. Associatiativy%Model regresi ARX dengan metode Least Square yang diukur secara offline%Associatiativy figure(5)clfhold on subplot (221)plot(x,min(min(A,B),C),'b',x,min(min(Az,Bz),Cz),'r');axis([-inf inf 0 1.2]);title('(A And B) And C');%set(gca,'xtick',[0 10 20 30]); subplot (222)plot(x,min(A,min(B,C)),'b',x,min(Az,min(Bz,Cz)),'r');axis([-inf inf 0 1.2]);title('A And (B And C)');%set(gca,'xtick',[0 10 20 30]); subplot (223)plot(x,max(max(A,B),C),'b',x,max(max(Az,Bz),Cz),'r');axis([-inf inf 0 1.2]);title('(A Or B) Or C');%set(gca,'xtick',[0 10 20 30]); subplot (224)plot(x,max(A,max(B,C)),'b',x,max(Az,max(Bz,Cz)),'r');axis([-inf inf 0 1.2]);title('A Or (B Or C)');%set(gca,'xtick',[0 10 20 30]);

Hold off

e. Distributivity%Model regresi ARX dengan metode Least Square yang diukur secara offline%Distributivity figure (6)clfhold onsubplot (221)plot(x,max(A,min(B,C)),'b',x,max(Az,min(Bz,Cz)),'r');axis([-inf inf 0 1.2]);title('A Or (B And C)');%set (gca,'xtick',[0 10 20 30]); subplot (222)plot(x, min(max(A,B),max(A,C)),'b',x,min(max(Az,Bz),max(Az,Cz)),'r');axis([-inf inf 0 1.2]);title('A Or B) And(A Or C)');%set (gca,'xtick',[0 10 20 30]); subplot (223)plot(x,min(A,max(B,C)),'b',x,min(Az,max(Bz,Cz)),'r');axis([-inf inf 0 1.2]);title('A And (B Or C)');%set (gca,'xtick',[0 10 20 30]); subplot (224)plot(x, max(min(A,B),min(A,C)),'b',x,max(min(Az,Bz),min(Az,Cz)),'r');axis([-inf inf 0 1.2]);title('A And B) or(A And C)');%set (gca,'xtick',[0 10 20 30]); hold off

III. KesimpulanDari simulasi di atas, dapat diperoleh kesimpulan sebagai berikut:Dapat mengetahui perbedaan fuzzy set dan crips set

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