Author :
Yamamoto, Tom ; Aoyama, Jun ; Nakano, Koutaro
Abstract :
Model predictive controllers have been widely used in process industries as an advanced control technology. Among them, generalized predictive controller (GPC) has been proposed by Clarke, el al. Especially, since the GPC is designed based on multi-step prediction, it is well known that the GPC is effective for systems with ambiguous time-delays and/or time-variant time-delays. On the other hand, most real systems have uncertainty, and self-tuning controllers and robust controllers are proposed to cope with such uncertainties. According to the self-tuning control scheme, the stability is not necessarily guaranteed in connection with the convergence of estimated parameters. Moreover, in robust control, the control system becomes quite conservative, and tracking properties are not good. In this paper, a new design scheme of robust self-tuning 2-degree-of-freedom GPC. That is, the closed-loop controller is designed so that the robust stability is satisfied, and the pre-filter is designed to improve the transient response in an on-line manner. According to the newly proposed control scheme, the transient property for the set point response can be improved keeping the robust stability. Finally, the proposed scheme is numerically evaluate on two simulation examples.
Keywords :
closed loop systems; control system synthesis; convergence; delays; filters; predictive control; process control; real-time systems; robust control; transient response; 2-degree-of-freedom GPC; 2DOF robust self-tuning GPC; advanced control technology; closed-loop controller; estimated parameters convergence; multistep prediction; predictive controller; predictive controllers; prefilter design; preview control; process control; real systems; robust control; robust controllers; robust stability; self-tuning control scheme; time-variant time-delays; transient response; uncertainty; Control systems; Convergence; Electrical equipment industry; Industrial control; Parameter estimation; Predictive models; Robust control; Robust stability; Robustness; Uncertainty;