| This Paper:Browse 1057 Download 141 |
码上扫一扫！ |
| Optimal finite-dimensional spectral densities for the identification of continuous-time MIMO systems |
| I.M.MITHUN,ShravanMOHAN,BharathBHIKKAJI |
|
|
| (Department of Electrical Engineering, Indian Institute of Technology, Madras, Chennai 600036, India) |
|
| 摘要: |
|
| 关键词: |
| DOI：https://doi.org/10.1007/s11768-019-8021-0 |
|
| 基金项目: |
|
| Optimal finite-dimensional spectral densities for the identification of continuous-time MIMO systems |
| I. M. MITHUN,Shravan MOHAN,Bharath BHIKKAJI |
| (Department of Electrical Engineering, Indian Institute of Technology, Madras, Chennai 600036, India) |
| Abstract: |
| This paper presents a method for designing inputs to identify linear continuous-time multiple-input multiple-output (MIMO)
systems. The goal here is to design a T-optimal band-limited spectrum satisfying certain input/output power constraints. The input
power spectral density matrix is parametrized as the product φu(jω) =1/2H(jω){H^H}(jω), where H(jω) is a matrix polynomial. This
parametrization transforms the T-optimal cost function and the constraints into a quadratically constrained quadratic program
(QCQP). The QCQP turns out to be a non-convex semidefinite program with a rank one constraint. A convex relaxation of the
problem is first solved. A rank one solution is constructed from the solution to the relaxed problem. This relaxation admits no
gap between its solution and the original non-convex QCQP problem. The constructed rank one solution leads to a spectrum that
is optimal. The proposed input design methodology is experimentally validated on a cantilever beam bonded with piezoelectric
plates for sensing and actuation. Subspace identification algorithm is used to estimate the system from the input-output data. |
| Key words: System identification, optimal input design, fisher information matrix, quadratically constrained quadratic program |
