Steady-state iterative learning control for a class of nonlinear PDE processes

In this paper, a P-type steady-state iterative learning control (ILC) scheme is applied to the boundary control of a class of nonlinear processes described by partial differential equations (PDEs), which cover many important industrial processes such as heat exchangers, industrial chemical reactors, biochemical reactors, and biofilters. Under several practical properties such as physical input–output monotonicity, process stability, and repeatability, the control problem is first transformed to an output regulation problem in the spatial domain. Next, the learning convergence condition of steady-state ILC, the learning rate, as well as the robustness, are derived through rigorous analysis. The adopted ILC scheme fully utilizes the process repetition and deals with both parametric and non-parametric uncertainties. In the end, an illustrative example is presented to demonstrate the performance of the proposed ILC scheme.

► A P-type steady-state ILC scheme is applied to the boundary control of a class of nonlinear processes described by PDE.
► It cover many important industrial processes.
► The adopted ILC scheme fully utilizes the process repetition and deals with both parametric and non-parametric uncertainties.
► Due to the simple structure, it is practically implementable.