Nonlinear system parameter estimation of drying process using modified state transition algorithm in cloud environment

摘要

The parameter estimation optimisation with constraints for the nonlinear complex system requires a serious of computation. This paper introduced a novel constrained optimisation method named Lagrangian-based state transition algorithm (LSTA) to solve problems in distributed cloud computing environment. LSTA with the physical constraints involved in solving the problems which occurs while the conventional techniques are used. In LSTA, the updating of the result to an optimisation problem with constraints known as, a state transition. The Lagrangian multiplier is used as a constraint for state transition process to estimate the drying process system effectively. The experiments are conducted in the cloud computing environment and simulated results validated the proposed LSTA methodology for parameter estimation. This method is a promising way for system identification due to its searching competency, enduring performance considering physical limitations and quick convergence.