  By transforming identification and control for nonlinear system into
optimization problems, a novel optimization method named state transition
algorithm (STA) is introduced to solve the problems. In the proposed STA, a
solution to a optimization problem is considered as a state, and the updating
of a solution equates to a state transition, which makes it easy to understand
and convenient to implement. First, the STA is applied to identify the optimal
parameters of the estimated system with previously known structure. With the
accurate estimated model, an off-line PID controller is then designed optimally
by using the STA as well. Experimental results have demonstrated the validity
of the methodology, and comparisons to STA with other optimization algorithms
have testified that STA is a promising alternative method for system
identification and control due to its stronger search ability, faster
convergence rate and more stable performance.
