Efficient output feedback nonlinear model predictive control

We investigate the efficient implementation of continuous time output feedback nonlinear model predictive control (NMPC) using a moving horizon observer (MHE) for state estimation. For this purpose we briefly review some aspects of MHE and some results on the computationally efficient implementation of nonlinear model predictive control. For the MHE we outline how an efficient dynamic optimization strategy for NMPC, the so called real-time iteration scheme, can be suitably adapted leading to a computationally efficient MHE implementation. The scheme is based on the multiple shooting method, a well known robust technique for nonlinear dynamic estimation problems. Application of the scheme allows us to use the MHE based output feedback NMPC controller in practice for reasonably sized problems. We exemplify the performance and computational demand of the proposed scheme by a simulation study considering the control of a high-purity distillation column.