Restricted structure adaptive predictive control of nonlinear systems

The application of novel adaptive predictive optimal controllers of low order, that involve a multi-step cost index and future set-point knowledge, is considered. A non-linear system is assumed to be represented by multiple linear discrete-time state-space models, where n of these models are linearisations of the underlying non-linear system at an operating point, determined off-line. At each sample instant an extra model is identified on-line. The optimisation is performed across this range of n+1 models to produce a single low order controller.