Incremental model reference adaptive polynomial controller network

• Published in: Proceedings of the 36th IEEE Conference on Decision and Control Vol. 5; pp. 4171 - 4172 vol.5
• Main Authors: Ronco, E., Gawthrop, P.J.
• Format: Conference Proceeding
• Language: English
• Published: IEEE 1997
• Subjects: Adaptive control; Adaptive systems; Control systems; Least squares approximation; Linear systems; Nonlinear control systems; Personal communication networks; Polynomials; Programmable control; Torque control
• ISBN: 0780341872; 9780780341876
• ISSN: 0191-2216
• DOI: 10.1109/CDC.1997.649487

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.