The adaptive control algorithm, its parameter adaptive recursive predicting and noise estimator is presented for a class of nonlinear discrete-time systems with multiple time delays based on dynamic approximate second-order nonlinear increment minimized recursive predicting model method.

The model-free learning adaptive control and its parameter adaptive predicting with parameter control length is presented for a class of nonlinear discrete-time systems with multiple time delays based on dynamic approximate linearization increment model in this paper.

The model-free direct adaptive control and its parameter adaptive predicting with parameter control length is presented for a class of nonlinear discrete-time systems with multiple time delays based on dynamic approximate linearization increment model.

In order to stablize the sinter chemical composition, an expert system for composition control based on adaptive prediction is developed on the basis of modern control theory and artificial intelligence.

A new method of dynamic system prediction-a developed multi -levelrecursive method (DMLRM) is proposed, based on the multi - level recursive method (MLRM) and the adaptive prediction method for systems with unknown time - varying parameters.

After the signals of cable transmission line were picked up from the input data and output data with noises, the likelihood whether there will be fault is judged early by means of the method of adaptive forecast identification.

This paper presents the imperfection of the method through analysis and introduces possible improvement using self adaptive recurrent algorithm.