• Dr. Fen Wu
  • North Carolina State University
  • 104D Surge Building
  • 4:00 p.m.
  • Faculty Host: Dr. Cornel Sultan

The linear parameter-varying (LPV) plants are finite-dimensional linear systems with known, parameter-dependent state-space data. It is assumed that the parameters are measurable in real-time and thus available for control use. LPV models have been used to approximate nonlinear dynamics. The study of LPV control is motivated by the gain-scheduling design methodology in industrial practice, and provides a systematic approach for gain-scheduling control. In this talk, we will first give an overview of existing LPV control techniques.

Then we will address the gain-scheduling control synthesis problem for nonlinear systems. For nonlinear gain-scheduling control, the LPV model is obtained by plant linearization about zero-error trajectories upon which an LPV controller is synthesized. A key issue would be how to find a nonlinear output feedback compensator which can guarantee the closed-loop system of nonlinear plant and compensator linearizes to the interconnection of LPV model and LPV controller. Consequently, the stability and performance properties about the zero-error trajectories can be inherited when the nonlinear compensator is implemented. By incorporating equilibrium input and measured output into an auxiliary LPV model, the nonlinear compensation problem would satisfy the linearization requirement. Moreover, the compensator synthesis condition can be reformulated as linear matrix inequalities (LMIs) based on parameter-dependent Lyapunov functions (PDLF) and is solvable using convex optimization algorithms. The validity of the proposed approach will be demonstrated through a ball and beam design example.