Hello ,There’s a question that’s been puzzling me.That is Why is the target function monotonically subtracting when maximize a objective function.And the following is my code which is the part of solution with cvx.

```
cvx_begin
cvx_quiet true
solver='mosek';
```

%variables

variable x(1,N)

variable y(1,N)

variable u(1,N)

variable t(1,N)

variable sig(K,N)

%objective func

expression temp1(N)

f=0;

for n=1:N

P_fea(n)=P_fea(n)*gama;

```
temp1(n)=P_fea(n)*(u_fea(n)-u(n))/((u_fea(n)^2+P_fea(n)*u_fea(n))*log(2))+log(1-P_fea(n)*pow_p(t(n)+P_fea(n),-1))/log(2);
f=f+temp1(n);
end
maximize f;
```

%constrain

subject to

% x(N+1)==400;

% y(N+1)==-200;

% x(1)=-400;

% y(1)=-200;

expression c(K,N);

expression lambda(K,N);

for k=1:K

for n=1:N

c(k,n)=-x_fea(n)^2+2*x_fea(n) x(n)-2x_E(k)x(n)+x_E(k)^2-y_fea(n)^2+2y_fea(n)y(n)-2y_E(k)y(n)+y_E(k)^2+H^2-t(n);*d;

temp=[sig(k,n)+1,0,x_E(k)-x(n);0,sig(k,n)+1,y_E(k)-y(n);x_E(k)-x(n),y_E(k)-y(n),-sig(k,n)Q(k)^2+c(k,n)];

temp == semidefinite(3);

sig(k,n)>=0;

end

end

for n=1:N-1

square_abs(x(n+1)-x(n))+square_abs(y(n+1)-y(n))<=(dvmax)^2;

end

% norm([400-x(N),-200-y(N)],2)<=vmaxd;

% norm([-400-x(1),-200-y(1)],2)<=vmax

```
square_abs(400-x(N))+square_abs(-200-y(N))<=(d*vmax)^2;
square_abs(-400-x(1))+square_abs(-200-y(1))<=(d*vmax)^2;
for n=1:N
square_abs(x(n))+square_abs(y(n))+H^2-u(n)<=0;
end
for n=1:N
t(n)>=H^2;
end
```

cvx_end

cvx_status

If anyone is kind enough to help me with my problems, I would appreciate it.