毕业设计&课设-文章题目为“通信时延和多址条件下的容错周期性事件触发共识”的MATLAB仿真代码….zip

close all clear all global A B K Laplacian j_sim na e x_broad ma u_s gamma_bar N=5; %number of agents % agent model % A=[0 1; 0 -0.4 ]; % B=[0.8 0.5]'; A=[0 -0.5; 0.5 0]; B=[0;1]; % A=[0 1; 0 0]; % B=[0;1]; % A=rand(2,2); na=size(A,1); % B=rand(2,1); ma=size(B,2); %% initial parameters tau=0.01; % buffer time h=0.02; % sampling period mu=tau+h; zeta1=0.3; % exponential rate Theta_bar=0.3; gamma_bar=0.02; u_s=0.1; psi_FDI=0.5; Omega=0.3; t_sim=0:0.01:20; alpha0=3; alpha1=0.2; alpha2=0.1; sample_period=0.01; %DOS ATTACKS alpha=3.5; for i =1:10 d(i)=(i)+0.5*i*(i)-(1/alpha)*(i); d_plus_tau(i)=d(i)+(1/alpha)*(i); end %% Laplacian Laplacian=[2 0 0 -1 -1; 0 2 -1 0 -1; 0 -1 2 -1 0; -1 0 -1 2 0; 0 0 0 0 0]; Laplacian = [ 2 -1 0 0 -1; -1 2 -1 0 0; 0 -1 2 -1 0 ; 0 0 -1 2 -1 ; -1 0 0 -1 2 ]; % Laplacian=[2 -1 0 -1; -1 2 -1 0; 0 -1 2 -1; -1 0 -1 2]; L=Laplacian; [aa,bb]=eig(L); V_inverse=inv(aa); J=bb(2:end,2:end); V=V_inverse(2:end,:); temp=sort(eig(L)); [a,b]=eig(L); W_inverse=inv(a); J_tild=b(2:end,2:end); V=W_inverse(2:end,:); J=b(1:end-1,1:end-1); [aa,bb]=eig(L); V_inverse=inv(aa); J=bb(2:end,2:end); V=V_inverse(2:end,:); %% decision variables Q=sdpvar(na,na); Y111=sdpvar(na,na); Y112=sdpvar(na,na,'full'); Y122=sdpvar(na,na); Y211=sdpvar(na,na); Y212=sdpvar(na,na,'full'); Y222=sdpvar(na,na); Y311=sdpvar(na,na); Y312=sdpvar(na,na,'full'); Y322=sdpvar(na,na); Y1=[Y111 Y112; Y112' Y122]; Y2=[Y211 Y212; Y212' Y222]; Y3=[Y311 Y312; Y312' Y322]; P1=sdpvar(na,na); P2=sdpvar(na,na); P3=sdpvar(na,na); P4=sdpvar(na,na); P5=sdpvar(na,na); H=sdpvar(na,na,'full'); F1=sdpvar(na,na,'full'); F2=sdpvar(na,na,'full'); F=[F1' F2']'; E1=sdpvar(na,na,'full'); E2=sdpvar(na,na,'full'); E=[E1' E2']'; G1=sdpvar(na,na,'full'); G2=sdpvar(na,na,'full'); G=[G1' G2']'; S1=sdpvar(na,na,'full'); S2=sdpvar(na,na,'full'); S=[S1' S2']'; U1=sdpvar(na,na,'full'); U2=sdpvar(na,na,'full'); U=[U1' U2']'; D1=sdpvar(na,na,'full'); D2=sdpvar(na,na,'full'); D=[D1' D2']'; M=sdpvar(ma,na); %%%%%%%%% BLOCKS %%%%%%%%%%%% W11=kron(eye(N-1),P2+P3+E1+E1'+S1'+S1+A*H'+H*A'+tau*Y111+mu*Y211+(mu-tau)*Y311+2*zeta1*P1); W12=kron(eye(N-1),G1-E1+E2'+F1-S1+S2'+U1-D1+H*A'+tau*Y112+mu*Y212+(mu-tau)*Y312)+kron(J,B*M); W13= kron(eye(N-1),D1-F1); W14=kron(eye(N-1),-G1-U1); W15=kron(eye(N-1),P1-H'+H*A'); W16=kron(J*V,B*M); T11=Theta_bar*kron(J*V,B*M); T12=kron(V,B); T13=-kron(V,B); T14=-kron(V,B); T15= zeros((N-1)*na,(N)*ma); T16= zeros((N-1)*na,N*ma); W21=W12'; W22=kron(eye(N-1),F2+F2'+G2+G2'+U2+U2'-S2-S2'-E2-E2'-D2-D2'+tau*Y122+mu*Y222+(mu-tau)*Y322)+kron(J,B*M)+kron(J,B*M)'; W23=kron(eye(N-1),D2-F2); W24=kron(eye(N-1),-G2-U2); W25=-kron(eye(N-1),H')+kron(J,M'*B'); W26=kron(J*V,B*M); T21=Theta_bar*kron(J*V,B*M); T22=kron(V,B); T23=-kron(V,B); T24=-kron(V,B); T25=gamma_bar*kron(J*V,M'); T26= zeros((N-1)*na,N*ma); W31=W13'; W32=W23'; W33=kron(eye(N-1),-exp(-2*tau*zeta1)*P2); W34=zeros((N-1)*na,(N-1)*na); W35=zeros((N-1)*na,(N-1)*na); W36=zeros((N-1)*na,(N)*na); T31=zeros((N-1)*na,(N)*na); T32=zeros((N-1)*na,(N)*ma); T33=zeros((N-1)*na,(N)*ma); T34=zeros((N-1)*na,(N)*ma); T35=zeros((N-1)*na,(N)*ma); T36=zeros((N-1)*na,(N)*ma); W41=W14'; W42=W24'; W43=W34'; W44=kron(eye(N-1),-exp(-2*mu*zeta1)*P3); W45=zeros((N-1)*na,(N-1)*na); W46=zeros((N-1)*na,(N)*na); T41=zeros((N-1)*na,(N)*na); T42=zeros((N-1)*na,(N)*ma); T43=zeros((N-1)*na,(N)*ma); T44=zeros((N-1)*na,(N)*ma); T45=zeros((N-1)*na,(N)*ma); T46=zeros((N-1)*na,(N)*ma); W51=W15'; W52=W25'; W53=W35'; W54=W45'; W55=kron(eye(N-1),tau*P4+mu*P4+(mu-tau)*P5-H'-H); W56=kron(J*V,B*M); T51=Theta_bar*kron(J*V,B*M); T52=kron(V,B); T53=-kron(V,B); T54=-kron(V,B); T55=zeros((N-1)*na,(N)*ma); T56= zeros((N-1)*na,(N)*ma); W61=W16'; W62=W26'; W63=W36'; W64=W46'; W65=W56'; W66=-kron(eye(N),Q); T61=zeros((N)*na,(N)*na); T62=zeros((N)*na,(N)*ma); T63=zeros((N)*na,(N)*ma); T64=zeros((N)*na,(N)*ma); T65=zeros((N)*na,(N)*ma); T66=gamma_bar*kron(V'*J*V,M'); W=[W11 W12 W13 W14 W15 W16; W21 W22 W23 W24 W25 W26; W31 W32 W33 W34 W35 W36; W41 W42 W43 W44 W45 W46; W51 W52 W53 W54 W55 W56; W61 W62 W63 W64 W65 W66]; T=[T11 T12 T13 T14 T15 T16; T21 T22 T23 T24 T25 T26; T31 T32 T33 T34 T35 T36; T41 T42 T43 T44 T45 T46; T51 T52 T53 T54 T55 T56; T61 T62 T63 T64 T65 T66]; R=blkdiag(-kron(eye(N),H+H')+eye(N*na),-eye(N*ma),-eye(N*ma),-eye(N*ma),-eye((N)*ma),-eye(N*ma)); C1=[ W T; T' R]; C2=[Y1 F;F' exp(-2*tau*zeta1)*P4]; C3=[Y1 E;E' exp(-2*tau*zeta1)*P4]; C4=[Y2 G;G' exp(-2*mu*zeta1)*P4]; C5=[Y2 S;S' exp(-2*mu*zeta1)*P4]; C6=[Y3 U;U' exp(-2*mu*zeta1)*P5]; C7=[Y3 D;D' exp(-2*mu*zeta1)*P5]; zeta2=zeta1*(1-Omega)/Omega; C8=[A*H'+H*A'-2*zeta2*P1+P2+P3 P1-H'+H*A'; (P1-H'+H*A')' -H-H'+(tau+mu)*P4+(mu-tau)*P5]; constraints =[ C1<=0, C2>=0, C3>=0, C4>=0, C5>=0, C6>=0, C8<=0, C7>=0, P1>=0, P2>=0, P3>=0, P4>=0, P5>=0, Q>=0 ]; info=solvesdp(constraints,[], sdpsettings('solver','sdpt3')) %% Design parameters for leaders K=double(M)*inv(double(H)') Phi=inv(double(H))*double(Q)*inv(double(H)') % eig(kron(eye(N-1),A)+kron(J,B*K)) %%%%%%%%%%% bar_P1=inv(double(H))*double(P1)*inv(double(H)'); bar_P2=inv(double(H))*double(P2)*inv(double(H)'); bar_P3=inv(double(H))*double(P3)*inv(double(H)'); b1=max(eig(bar_P1))+tau*max(eig(bar_P2))+mu*max(eig(bar_P3)); b2=min(eig(bar_P1)); b_ratio=sqrt(b1/b2); c=sqrt(N*(u_s^2+psi_FDI^2+alpha0+alpha2)/(2*zeta1)); %%%%%%%%%%% %% real-time consensus %%%%%%%%%%%%%%%%%%%%%% for i=1:N x_init=[6*i i]'; %%% initial values X_init{i}= x_init; X_init_exp{i}=X_init{i}' ; x_stack{i}=[]; u_stack{i}=[]; event_time{i}=0; end %%% Initial values for X X_init_save=X_init; for i=1:N x_broad{i}=X_init{i}; x_broad_for_e{i}=X_init{i}; x_old{i}=X_init{i}; xi5_old{i}=0; end counter=zeros(1,N); Tk=zeros(1,N); z_store=[]; rate_upper_bound_store=[]; z_zero=norm(kron(V,eye(na))*reshape(cell2mat(X_init),[1 N*na])'); DoS=0; DoS_history=0; for iterations=1:length(t_sim)-2 x_store=[]; for i=1:10 if t_sim(iterations)>d(i) && t_sim(iterations)<d_plus_tau(i) DoS=1; end end %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% if DoS ==0 %%%%%%%% No DoS for j_sim=1:N if rand <=gamma_bar flag=1; else flag=0; end K=double(M)*inv(double(H)'); [t,xx] =ode45(@IS_dif,[t_sim(iterations) t_sim(iterations+1) t_sim(iterations+2) ],x_old{j_sim}); x_stack{j_sim} = [ x_stack{j_sim} xx(2,:)']; current_x{j_sim}=xx(2,:)'; x_store=[x_store; current_x{j_sim} ]; e{j_sim}=(x_broad_for_e{j_sim})-current_x{j_sim}; x_old{j_sim}=xx(2,:); end if mod(iterations,h*100)==0 for j_sim=1:N % z{j_sim}=norm((kron(Laplacian(j_sim,:),eye(na)))*cell2mat((x_broad)')); if e{j_sim}'*Phi*e{j_sim}>alpha0*exp(-alpha1*t_sim(iterations))+alpha2 || DoS_history==1 x_broad_for_e{j_sim}=current_x{j_sim}; if rand <=Theta_bar x_broad{j_sim}=current_x{j_sim}+psi_FDI*tanh(0.1*j_sim*t_sim(iterations)); else x_broad{j_sim}=current_x{j_sim}; end counter(j_sim)=counter(j_sim)+1; %%%%%%% event isnats event_time{j_sim}=[event_time{j_sim} t_sim(iterations)]; Tk(j_sim)=t_sim(iterations); end end DoS_history=0; end end %%%%%%%%%%%%%%%%%%% if DoS ==1 %%%%%%%% in DoS