A control system using a genetic analyzer based on discrete constraints is described.
In one embodiment, a genetic algorithm with step-coded chromosomes is used to develop
a teaching signal that provides good control qualities for a controller with discrete
constraints, such as, for example, a step-constrained controller. In one embodiment,
the control system uses a fitness (performance) function that is based on the physical
laws of minimum entropy. In one embodiment, the genetic analyzer is used in an
off-line mode to develop a teaching signal for a fuzzy logic classifier system
that develops a knowledge base. The teaching signal can be approximated online
by a fuzzy controller that operates using knowledge from the knowledge base. The
control system can be used to control complex plants described by nonlinear, unstable,
dissipative models. In one embodiment, the step-constrained control system is configured
to control stepping motors.