MODEL-FREE ADAPTIVE CONTROL FOR INDUSTRIAL PROCESSES

摘要

An enhanced model-free adaptive controller is disclosed, which consists of a dynamic neural network (18) that can be easily configured and put in automatic mode to control simple to complex processes. The neural network contains a normalizing unit (26) and a scaling function (25) for normalizing and scaling an input signal. The input signal comprises an error signal representing a difference between the controlled process output and a predetermined setpoint. Two multivariable model-free adaptive controller designs are disclosed. An enhanced anti-delay model-free adaptive controller is introduced to control processes with large time delays. A feedforward/feedback model-free adaptive control system with two designs is introduced to compensate for measurable disturbances.