Sampled-data, output feedback predictive control of uncertain, nonlinear systems

Abstract

Abstract: We present a model predictive control approach for uncertain, continuous-time, constrained, nonlinear systems with noisy, discrete time measurements. The proposed discrete-time controller combines a state estimator with a suitably robustified predictive control law. For this purpose the continuous-time dynamics is discretized and rigorous bounds on the truncation errors as well as the noise are derived. We combine these bounds with ideas from tube based predictive control to derive conditions to guarantee constraint satisfaction, robust recursive feasibility and robust stability. An example illustrates the results.