Robust nonlinear internal model control of stable Wiener systems

Many process systems can be modeled as a stable Wiener system, which is a stable linear system followed by a static nonlinearity. A nonlinear control design procedure is presented that provides robustness to uncertainties while being applicable to systems with unstable zero dynamics, unmeasured states, disturbances, and measurement noise. The design procedure combines nonlinear internal model control with linear matrix inequality feasibility or optimization problems, such that all robust stability and performance criteria are computable in polynomial-time using readily available software. Application to a pH neutralization case study demonstrates the importance of taking uncertainty into account during the design of controllers for Wiener systems. The approach is generalizable to Hammerstein and sandwich systems, whether well- or poorly conditioned, and to systems with actuator constraints.

► A robust nonlinear control design procedure is presented for stable Wiener systems.
► Nonlinear internal model control is combined with LMI feasibility or optimization problems.
► All robust stability and performance criteria are computable in polynomial-time.
► Application to a pH control case study demonstrates the importance of taking uncertainty into account.
► The approach is generalizable to Hammerstein and sandwich systems and to systems with actuator constraints.