Incremental model reference adaptive polynomial controller network - Ronco, E.; Gawthrop, P.J. (Proceedings of the 36th IEEE Conference on Decision and Control, 1997)
The incremental model reference adaptive polynomial controllers network (IMRAPCN) is a self-organising nonlinear controller. This algorithm consists of a polynomial controllers network (PCN) and an incremental network construction (INC). The PCN is a network of polynomial controllers each one being valid for a different operating region of the system. The use of polynomial controllers reduces significantly the number of controllers required to control a non linear system while improving the control accuracy, and the whole, without any drawbacks since polynomials are "linear in parameters functions". Such a control system can be used for the control of a possibly discontinuous nonlinear system, it is not affected by the "stability-plasticity dilemma" and yet can have a very clear architecture. The INC enables a very efficient construction of the network architecture as well as an accurate determination of the region of validity of each controller. Hence, the INC gives to the PCN a complete autonomy since the clustering of the operating space can be achieved without any a priori knowledge about the system. These advantages highlight the great potential of the IMRAPCN to control nonlinear systems.