Identification of parameters in distributed parameter systems by regularization. (English) Zbl 0563.93018
The authors investigate the parameter identification problem for distributed parameter systems. The problem of parameter identification in distributed parameter systems from noisy data is both nonlinear and ill- posed. They develop the concept of regularization, which is widely used in solving linear Fredholm integral equations, for the identification of parameters in distributed parameter systems. They first present a general regularization identification theory and then apply it to the identification of parabolic systems. The performance of the regularization identification method is evaluated by numerical experiments on the identification of a spatially varying diffusivity in the diffusion equation.
Reviewer: T.Kobayashi
MSC:
93B30 | System identification |
93C05 | Linear systems in control theory |
93C20 | Control/observation systems governed by partial differential equations |
35R25 | Ill-posed problems for PDEs |
93C99 | Model systems in control theory |
35R30 | Inverse problems for PDEs |
35K20 | Initial-boundary value problems for second-order parabolic equations |