title: Efficient decentralized iterative learning tracker for unknown sampled-data interconnected large-scale state-delay system with closed-loop decoupling property.
abstract: In this paper, an efficient decentralized iterative learning tracker is proposed to improve the dynamic performance of the unknown controllable and observable sampled-data interconnected large-scale state-delay system, which consists of N multi-input multi-output (MIMO) subsystems, with the closed-loop decoupling property. The off-line observer/Kalman filter identification (OKID) method is used to obtain the decentralized linear models for subsystems in the interconnected large-scale system. In order to get over the effect of modeling error on the identified linear model of each subsystem, an improved observer with the high-gain property based on the digital redesign approach is developed to replace the observer identified by OKID. Then, the iterative learning control (ILC) scheme is integrated with the high-gain tracker design for the decentralized models. To significantly reduce the iterative learning epochs, a digital-redesign linear quadratic digital tracker with the high-gain property is proposed as the initial control input of ILC. The high-gain property controllers can suppress uncertain errors such as modeling errors, nonlinear perturbations, and external disturbances (Guo et al., 2000) [18]. Thus, the system output can quickly and accurately track the desired reference in one short time interval after all drastically-changing points of the specified reference input with the closed-loop decoupling property.
authors.affiliation: Control System Laboratory, Department of Electrical Engineering, National Cheng Kung University, Tainan 701, Taiwan, ROC. shtsai@mail.ncku.edu.tw
authors.forename: Jason Sheng-Hong
authors.initials: JS
authors.lastname: Tsai
authors.forename: Fu-Ming
authors.initials: FM
authors.lastname: Chen
authors.forename: Tze-Yu
authors.initials: TY
authors.lastname: Yu
authors.forename: Shu-Mei
authors.initials: SM
authors.lastname: Guo
authors.forename: Leang-San
authors.initials: LS
authors.lastname: Shieh
mesh_terms: D000465:Algorithms; D001185:Artificial Intelligence; D003198:Computer Simulation; D007221:Industry / Q000295:instrumentation; D016014:Linear Models; D016571:Neural Networks, Computer; D017711:Nonlinear Dynamics; D016011:Normal Distribution