Galerkin approximation for inverse problems for nonautonomous nonlinear distributed systems

We develop an abstract framework and convergence theory for Galerkin approximation for inverse problems involving the identification of nonautonomous, in general nonlinear, distributed parameter systems. We provide a set of relatively easily verified conditions which are sufficient to guarantee the existence of optimal solutions and their approximation by a sequence of solutions to a sequence of approximating finite-dimensional identification problems. Our approach is based upon the theory of monotone operators in Banach spaces and is applicable to a reasonably broad class of nonlinear distributed systems. Operator theoretic and variational techniques are used to establish a fundamental convergence result. An example involving evolution systems with dynamics described by nonstationary quasi-linear elliptic operators along with some applications and numerical results are presented and discussed.Part of this research was carried out while the first and third authors were visiting scientists at the Institute for Computer Applications in Science and Engineering (ICASE), NASA Langley Research Center. Hampton, VA, which is operated under NASA Contracts NAS1-17070 and NAS1-18107. Also, a portion of this research was carried out with computational resources made available through a grant to the second and third authors from the San Diego Supercomputer Center operated for the National Science Foundation by General Atomics, San Diego, CA. The research of the first author was supported in part under Grants NSF MCS-8504316, NASA NAG-1-517, AFOSR-84-0398, and AFOSR-F49620-86-C-0111. The second author's research was supported in part by the Fund for the Promotion of Research at the Technion and by the Technion VPR Fund. The research of the third author was supported in part under Grants AFOSR-84-0393 and AFOSR-87-0356.