Technologies of process dynamics modelling and control for industrial use have been developed in an Idemitsu petrochemical plant. In this paper, the application of process dynamics modelling using a physical approach, a time-series analysis, a neural networks approach, a genetic algorithm and a chaotic time-series analysis of nonlinear process, and application of process control systems design using feedfoward control with a physical model, a model predictive control, an iterative learning control, a self-tuning fuzzy control and a simple adaptive control are presented. The future tasks of process control systems design for industrial use are discussed.