This paper presents an novel approach for tackling problems associated with flexibility of dynamic structures. A number of solutions to this problem have been developed by innovative combination of fuzzy logic and neural networks inexact algorithms. A spring-mounted pen is used in the experiments to emulate the deviation of an end-effector caused by flexibility. A pre- and post-processing vision-based machine control system is developed. Comparing the desired pattern and the actual output, the intelligent machine console can automatically make appropriate compensation through online self-learning process. Various experimental results indicate that using the algorithms developed the system can compensate for flexibility and produce excellent results, much better than human operators.