Least Square Optimal Approximation Simulation Techniques.
CASE WESTERN RESERVE UNIV CLEVELAND OHIO SYSTEMS RESEARCH CENTER
Pagination or Media Count:
The report addresses the use of a quadratic objective function in an optimal control setting to construct an approximate solution for distributed parameter models. The systems are first order with respect to time and linear and time-dependent with respect to the spatial operator. The Least Squares variational technique is compared with the Galerkin finite element method in order to ascertain the worth of the optimal simulation on a digital computer. The Least Squares approach is demonstrated to be a powerful tool in simulating stable physical systems. In addition, the use of a coupled basis and a weighting matrix in the quadratic objective function can be used to tune the approximate solution. Thus, refined numerical simulations for certain classes of partial differential equations are readily accomplished with the Least Squares optimal simulation techniques. Author
- Statistics and Probability