Title :
Identified predictive control
Author :
Bialasiewicz, Jan T. ; Horta, Lucas G. ; Phan, Minh Q.
Author_Institution :
Dept. of Electr. Eng., Colorado Univ., Denver, CO, USA
fDate :
29 June-1 July 1994
Abstract :
A new approach to the long-range predictive control, named identified predictive control (IPC), is proposed. The process predictor model, used to determine the control sequence, is derived from a state space formulation of the ARIMAX model and is directly identified using current input-output sequences. Since IPC uses a properly defined observer model of the minimum-variance j-step-ahead predictor, its implicit identification has dead beat properties that makes IPC particularly suitable for control of flexible structures. A numerical example is used to demonstrate the algorithm.
Keywords :
autoregressive moving average processes; flexible structures; observers; predictive control; state-space methods; ARIMAX model; dead beat; flexible structure control; identification; identified predictive control; input-output sequences; minimum-variance j-step-ahead predictor; observer model; process predictor model; state space; Flexible structures; NASA; Optimal control; Polynomials; Prediction algorithms; Predictive control; Predictive models; Process control; State-space methods; Torque control;
Conference_Titel :
American Control Conference, 1994
Print_ISBN :
0-7803-1783-1
DOI :
10.1109/ACC.1994.735174
