A linear-quadratic model-predictive controller for control and state constrained nonlinear control problems

Abstract

We consider nonlinear control problems subject to control and state constraints and develop a model-predictive controller which aims at tracking a given reference solution. Instead of solving the nonlinear problem, we suggest solving a local linear-quadratic approximation in each step of the algorithm. Application of the virtual control concept introduced in [1, 4] ensures that the occuring control-state constrained linear-quadratic problems are solvable and accessible to fast function space methods like semi-smooth Newton methods. Numerical examples support this approach and illustrate the idea. © 2010 Springer -Verlag Berlin Heidelberg.