Nuclear norm system identification with missing inputs and outputs

This condition holds generically when the inputs are chosen at random. Under this assumptionthe first term on the right-hand side of (4) has rank n x and its range equals the rangeof O r . In the absence of noise (E = 0), one therefore hasn x = rank(Y 0,r,N Π 0,r,N ), range(O r ) = range(Y 0,r,N Π 0,r,N ).In the presence of noise (E ≠ 0), these identities hold only approximately and one can estimatenx andrange(O r )fromalow-rankapproximationofY 0,r,N Π 0,r,N , obtainedbytruncatingan SVD.An efficient implementation of this scheme is the MOESP (MIMO Output-Error State-Space) algorithm [20]. In this method one first computes an LQ factorization[ ]U0,r,N=Y 0,r,N[ ][ ]L11 0 Q1L 21 L 22 Q 2of the stacked input and output Hankel matrices. The diagonal blocks L 11 and L 22 aretriangular matrices of order rn m and rn p , respectively. The matrices Q 1 and Q 2 have Ncolumns and satisfy Q 1 Q T 1 = I, Q 2 Q T 2 = I, Q 1 Q T 2 = 0. We have Π 0,r,N = I −Q T 1Q 1 andHenceY 0,r,N Π 0,r,N = (L 21 Q 1 +L 22 Q 2 )(I −Q T 1Q 1 ) = L 22 Q 2 .range(Y 0,r,N Π 0,r,N ) = range(L 22 )and the range space of O r can be estimated from an SVD of L 22 .Instrumental variables. The basic projection method described in the previous paragraphis not consistent: the range of Y 0,r,N Π 0,r,N does not necessarily converge to the range of O ras N goes to infinity. This deficiency can be resolved by the use of instrumental variables[21, 22]. We define an instrumental variable matrix[ ]U−s,s,NΦ =(7)Y −s,s,Nby combining Hankel matrices of ‘past’ inputs and outputs. (More generally, one can usedifferent row dimensions for the two Hankel matrices in Φ, but we will take them equal forsimplicity. In the experiments of section 5 we will use s = r.) Multiplying (4) on the rightwith Φ T givesY 0,r,N Π 0,r,N Φ T = O r X 0,1,N Π 0,r,N Φ T +EΠ 0,r,N Φ T .It can be shown that lim N→∞ (1/N)EΠ 0,r,N Φ T = 0 and that, under weak assumptions, thelimit1limN→∞ N X 0,1,NΠ 0,r,N Φ Thas full rank n x (see [8, §9.6] for a detailed discussion). As a consequence, the range ofY 0,r,N Π 0,r,N Φ T gives a consistent estimate of the range of O r . In practice, for finite N, atruncated SVD of Y 0,r,N Π 0,r,N Φ T is used to estimate range(O r ).4(6)