Dear all,
I am trying to solve the following optimization problem:
cvx_begin
variables xhh(4) gama
value = norm( obj_A * xhh - obj_b, 2 ) ;
minimize ( value )
subject to
X_xh-gama*eye(6)>=0
A_tri_kalman_xh * xhh >= b_tri_kalman_xh
gama>=0.1
cvx_end
where, the variable xhh is a vector of four decision variables, obj_A is a 16 x4 matrix, A_tri_kalman_xh is a 30x4 matrix, gama is a positive constant. X_xh is a 6x6 matrix, whose each element is a linear function of 4 decisions variables.
When running this code, it outputs “Calling SDPT3 4.0: 59 variables, 6 equality constraints
For improved efficiency, SDPT3 is solving the dual problem.
num. of constraints = 6
dim. of socp var = 7, num. of socp blk = 1
dim. of linear var = 52
SDPT3: Infeasible path-following algorithms
version predcorr gam expon scale_data
NT 1 0.000 1 0
it pstep dstep pinfeas dinfeas gap prim-obj dual-obj cputime
0|0.000|0.000|9.2e+02|2.4e+01|4.7e+04| 9.203833e+02 0.000000e+00| 0:0:00|------------------------------------------------------------
Status: Error
Optimal value (cvx_optval): NaN
Check for incorrect argument data type or missing argument in call to function
‘spdiags’.
Error in schurmat_lblk (line 35)
schurtmp = At{p}’ *spdiags(ddsch,0,n,n) *At{p};
Error in NTpred (line 34)
[schur,UU,EE] = schurmat_lblk(blk,At,par,schur,UU,EE,p,par.dd);
Error in sqlpmain (line 345)
NTpred(blk,At,par,rp,Rd,sigmu,X,Z,Zchol,invZchol);
Error in sqlp (line 242)
sqlpmain(blk3,At3,C3,b,par,parbarrier3,X03,y0,Z03);
Error in cvx_run_solver (line 50)
[ varargout{1:nargout} ] = sfunc( inputs{:} );
Error in cvx_sdpt3>solve (line 362)
[ obj, xx, y, zz, info ] = cvx_run_solver( @sqlp, blk, Avec, Cvec, b, OPTIONS, ‘obj’, ‘x’, ‘y’, ‘z’, ‘info’, settings, 5 ); %#ok
Error in cvxprob/solve (line 429)
[ x, status, tprec, iters, y ] = shim.solve( At, b, c, cones, quiet, prec, solv.settings, eargs{:} );
Error in cvx_end (line 88)
solve( prob );
Error in CVX_Prob_P_estimate_response_matrix (line 39)
cvx_end”.
I would appreciate it if anyone could help me to solve this problem. Thank you!