Finitely parameterised implementation of receding horizon control for constrained linear systems

Recent work by the authors has provided a finitely parameterised characterisation of receding horizon control (RHC) for linear models with quadratic performance index and linear constraints. Using a closed-form solution to quadratic programming, we have expressed the RHC law via a "look-up table" consisting of a partition of the state space into regions in which the corresponding control law has an explicit form. This paper investigates numerical properties of the table look-up implementation of the RHC solution and compares its performance with traditional methods for on-line optimisation (such as active constraint methods for quadratic programming). Issues that we consider include computation times, code complexity and data storage.