A genetic approach to hybrid control of sampled-data uncertain system with input time delay

This paper utilizes genetic algorithms (GAs) to convert a continuous-time uncertain system with input time delay to an equivalent discrete-time interval model. Also, the GAs are used to find the interval control law for a sampled-data uncertain system with input time delay. The developed discrete-time interval model match closely the exact discrete-time uncertain system with input time delay. Based on the principle of equivalent areas and GAs, a new implementable digital control law, taking into account the intersample behavior and implementation errors, is developed for digital control of the input time-delay continuous-time uncertain system so that the states of the digitally controlled sampled-data uncertain system optimally match those of the originally well-designed continuous-time uncertain system.