This paper proposes a design method of extended self-tuning generalized predictive control (GPC) with computation reduction focused on closed-loop characteristics. The authors have extended GPC by coprime factorization and proposed the extended controller for constructing a strongly stable system. Moreover, the proposed controller is able to be designed to make the same steady state output as pre-designed system's steady state output even if feedback loop is cut. Although self-tuning controller is one of the control methods for systems with uncertainty, there is a problem that the computation of self-tuning GPC increases as design engineer takes long prediction horizon in the design parameters. Therefore this paper considers computation reduction for extended self-tuning GPC focused on closed-loop characteristics. The validity of the proposed method is shown by numerical simulation.
|Title of host publication||11th IFAC International Workshop on Adaptation and Learning in Control and Signal Processing, ALCOSP 2013 - Proceedings|
|Number of pages||6|
|Publication status||Published - 2013|
|Event||11th IFAC International Workshop on Adaptation and Learning in Control and Signal Processing, ALCOSP 2013 - Caen, France|
Duration: Jul 3 2013 → Jul 5 2013
|Name||IFAC Proceedings Volumes (IFAC-PapersOnline)|
|Other||11th IFAC International Workshop on Adaptation and Learning in Control and Signal Processing, ALCOSP 2013|
|Period||7/3/13 → 7/5/13|
- Closed-loop gain
- Coprime factorization
- Data reduction.
- Generalized predictive control
- Self-tuning control
ASJC Scopus subject areas
- Control and Systems Engineering