Control of nonlinear non-minimum phase systems with input-output linearization

In this paper we present a new approach of using input-output linearization to control a single input, single output, input-affine nonlinear non-minimum phase system. We will show that, if the linearized system is stabilizable, we can redefine the output of the system such that the input-output linearized system is locally asymptotically stable. Furthermore we develop an LQR technique for designing the redefined output, which assures stabilization of the zerodynamics. Simulations of a physical system show that the resulting controller, which in a way fuses LQR techniques with input-output linearization, out-performs a regular LQR feedback controller and demonstrates a big region of attraction. The presented technique can be used to regulate the system around an equilibrium and to achieve tracking for certain trajectories. Conditions are established that allow the asymptotic regulation and tracking of desired trajectories for the original output. We will demonstrate the control design on a two-dimensional Segway model.