Decentralized Input-Constraint Trackers for Unknown Large-Scale Interconnected Sampled-Data Systems with State Delay

Y.-Y. Du, J.S.-H. Tsai, Y.-H. Chen, S.-M. Guo (Taiwan), and L.-S. Shieh (USA)


Observer/Kalman filter identification, digital redesign, linear quadratic tracker, input constraint


Decentralized modeling and linear observers/input constraint trackers for a more general class of unknown large-scale interconnected sampled-data linear systems with state delay and closed-loop decoupling property are proposed in this paper. First, the off-line observer/Kalman filter identification (OKID) method is used to determine the appropriate (low-) order decentralized linear observers for the unknown large-scale interconnected sampled-data linear system with state delay. Then, a digital redesign approach with the high-gain property is applied to overcome the modeling error of the above observers effectively. Moreover, a digital-redesign observer-based linear quadratic digital tracker with high-gain property for the sampled-data system is presented, and it provides high performance on trajectory tracking with the closed-loop decoupling property. Finally, to reduce the magnitude of control input, which is caused by the high-gain property to fit the requirement of the input constraint, the modified linear quadratic digital tracker (LQDT) is proposed. And the control input can be compressed effectively without losing the original high performance of tracking much.

Important Links:

Go Back