Hybrid Genetic and Nelder-Mead Algorithms for Identification of Time Delays

The identification of time delay in the linear plant is one of the important identification tasks. Most of the conventional identification techniques, such as those based on least mean-squares, are essentially gradient-guided local search techniques and they require a smooth search space or a differentiable performance index. New possibility in this field is opened by an application of the hybrid genetic algorithms. The center of mass simplex crossover (CMSPX) algorithm is proposed in the paper. This algorithm is compared with other classical and genetic methods, by using the efficiency of looking for time delay and time of computation as a performance measure. The obtained results suggest that the proposed method performs well in estimating the model parameters.