Adaptive neurocontrollers for drive systems: Basic concepts, theory and applications

Abstract

In this chapter basic principles of neurocontrol are revised and discussed from the point of view of applications in converter-fed drive systems. The main neural network structures used as neural controllers are presented and classified into two groups: off-line and on-line trained controllers. From the point of view of drive system uncertainties, caused by simplifying assumptions under mathematical model formulation, errors in drive parameters identification and changes of the models and their parameters under different operation conditions, on-line adaptive neural controllers are proposed. Various neural structures and their on-line training methods are discussed. The chosen neurocontrollers were verified in simulation and experimental tests for converter-fed drives with rigid and resilient mechanical connections between the driving motor and loading machine. © Springer International Publishing Switzerland 2014.