title: Auto-tuning of PID controller parameters with supervised receding horizon optimization.
abstract: In this paper, a novel two-layer online auto-tuning algorithm is presented for a nonlinear time-varying system. The lower layer consists of a conventional proportional-integral-derivative (PID) controller and a plant process, while the upper layer is composed of identification and tuning modules. The purpose of the upper layer is to find a set of optimal PID parameters for the lower layer via an online receding horizon optimization approach, which result in a time-varying PID controller. Through mathematical analysis, the proposed system performance is equivalent to that of a standard generalized predictive control. Simulation and experiment demonstrate that the new method has a better control system performance compared with conventional PID controllers.
authors.affiliation: Institute of Automation, Shanghai Jiao Tong University, Shanghai, China.
authors.forename: Min
authors.initials: M
authors.lastname: Xu
authors.forename: Shaoyuan
authors.initials: S
authors.lastname: Li
authors.forename: Chenkun
authors.initials: C
authors.lastname: Qi
authors.forename: Wenjian
authors.initials: W
authors.lastname: Cai