Title :
Decentralized adaptive internal model control for multi-input multi-output systems
Author :
Xing, Lei ; Datta, Aniruddha
Author_Institution :
Dept. of Electr. Eng., Texas A&M Univ., College Station, TX, USA
Abstract :
A continuous-time decentralized adaptive internal model controller is proposed for the control of an N×N MIMO system with unknown parameters. By treating the MIMO system as an interconnection of N linear SISO subsystems with “weak” interactions, robust adaptive internal model controllers are designed for each isolated subsystem. Each local adaptive control law utilizes a normalizing signal which is generated using the local output and the inputs of all the subsystems. This necessitates the exchange of input signals between the different subsystems so that the scheme is no longer totally decentralized. This, however, does not pose any problem in industrial process control applications, where all the signals are anyway brought to or originate from a central control room. An additional feature which makes the scheme very attractive is the fact that its computational complexity is about the same as that of a totally decentralized one
Keywords :
MIMO systems; computational complexity; control system synthesis; decentralised control; model reference adaptive control systems; robust control; uncertain systems; MIMO system; central control room; computational complexity; continuous-time decentralized adaptive internal model control; industrial process control; linear SISO subsystems; normalizing signal; robust adaptive internal model controllers; unknown parameters; weak interactions; Adaptive control; Centralized control; Computational complexity; Industrial control; MIMO; Process control; Programmable control; Robust control; Signal generators; Signal processing;
Conference_Titel :
American Control Conference, 1999. Proceedings of the 1999
Conference_Location :
San Diego, CA
Print_ISBN :
0-7803-4990-3
DOI :
10.1109/ACC.1999.782736