Finite-Horizon Tracking Control for Repetitive Systems with Uncertain Initial Conditions
Repetitive systems stand for a kind of systems that
perform a simple task on a fixed pattern repetitively, which are
widely spread in industrial fields. Hence, many researchers have been
interested in those systems, especially in the field of iterative learning
control (ILC). In this paper, we propose a finite-horizon tracking
control scheme for linear time-varying repetitive systems with uncertain
initial conditions. The scheme is derived both analytically
and numerically for state-feedback systems and only numerically for
output-feedback systems. Then, it is extended to stable systems with
input constraints. All numerical schemes are developed in the forms
of linear matrix inequalities (LMIs). A distinguished feature of the
proposed scheme from the existing iterative learning control is that
the scheme guarantees the tracking performance exactly even under
uncertain initial conditions. The simulation results demonstrate the
good performance of the proposed scheme.
[1] Tae-Jeong Chang, Chong-Ho Choi, Hyun-Sik Ahn, "Iterative Learning
Control in Feedback Systems", Automatica, Vol. 31, No. 2, 1995.
[2] Tommy W. S. Chow, Yong Fang, "An Interative Learning Control Method
for Continuous-Time Systems Based on 2-D System Theory", IEEE
Trans. on Autom. Cont., Vol. 45, No. 4, 1998
[3] Yong Fang, Tommy W. S. Chow, "Iterative Learning Control of Linear
Discrete-Time Multivariable Systems", Automatica, Vol. 34, No. 11, 1998.
[4] Yong Fang, Tommy W. S. Chow, "2-D Analysis for Iterative Learning
Controller for Discrete-Time Systems With Variable Initial Conditions",
IEEE Trans. on Circuits Syst. I: Fundamental Theory and Applica.t., Vol.
50, No. 5, pp. 722-727, 2003.
[5] Jerzy E. Kurek, Marek B. Zaremba, "Iterative Learning Control Synthesis
Based on 2-D System Theory", IEEE Trans. on Autom. Cont., Vol. 38,
No. 1, 1993.
[6] Samer S. Saab, "A Discrete-Time Learning Control Algorithm for a Class
of Linear Time-Invariant Systems", IEEE Trans. on Atuom. Cont., Vol.
40, No. 6, 2002.
[7] Luis G. Sison, Edwin K. P. Chong, "Design of Repetitive Learning
Control.", Proceedings of the 36th Conference on Decision & Control,
San Diego, California, USA, 1997.
[1] Tae-Jeong Chang, Chong-Ho Choi, Hyun-Sik Ahn, "Iterative Learning
Control in Feedback Systems", Automatica, Vol. 31, No. 2, 1995.
[2] Tommy W. S. Chow, Yong Fang, "An Interative Learning Control Method
for Continuous-Time Systems Based on 2-D System Theory", IEEE
Trans. on Autom. Cont., Vol. 45, No. 4, 1998
[3] Yong Fang, Tommy W. S. Chow, "Iterative Learning Control of Linear
Discrete-Time Multivariable Systems", Automatica, Vol. 34, No. 11, 1998.
[4] Yong Fang, Tommy W. S. Chow, "2-D Analysis for Iterative Learning
Controller for Discrete-Time Systems With Variable Initial Conditions",
IEEE Trans. on Circuits Syst. I: Fundamental Theory and Applica.t., Vol.
50, No. 5, pp. 722-727, 2003.
[5] Jerzy E. Kurek, Marek B. Zaremba, "Iterative Learning Control Synthesis
Based on 2-D System Theory", IEEE Trans. on Autom. Cont., Vol. 38,
No. 1, 1993.
[6] Samer S. Saab, "A Discrete-Time Learning Control Algorithm for a Class
of Linear Time-Invariant Systems", IEEE Trans. on Atuom. Cont., Vol.
40, No. 6, 2002.
[7] Luis G. Sison, Edwin K. P. Chong, "Design of Repetitive Learning
Control.", Proceedings of the 36th Conference on Decision & Control,
San Diego, California, USA, 1997.
@article{"International Journal of Electrical, Electronic and Communication Sciences:49324", author = "Sung Wook Yun and Yun Jong Choi and Kyong-min Lee and Poogyeon Park*", title = "Finite-Horizon Tracking Control for Repetitive Systems with Uncertain Initial Conditions", abstract = "Repetitive systems stand for a kind of systems that
perform a simple task on a fixed pattern repetitively, which are
widely spread in industrial fields. Hence, many researchers have been
interested in those systems, especially in the field of iterative learning
control (ILC). In this paper, we propose a finite-horizon tracking
control scheme for linear time-varying repetitive systems with uncertain
initial conditions. The scheme is derived both analytically
and numerically for state-feedback systems and only numerically for
output-feedback systems. Then, it is extended to stable systems with
input constraints. All numerical schemes are developed in the forms
of linear matrix inequalities (LMIs). A distinguished feature of the
proposed scheme from the existing iterative learning control is that
the scheme guarantees the tracking performance exactly even under
uncertain initial conditions. The simulation results demonstrate the
good performance of the proposed scheme.", keywords = "Finite time horizon, linear matrix inequality (LMI), repetitive system, uncertain initial condition.", volume = "1", number = "8", pages = "1082-4", }