Iterative weighted least-squares approach to constrained LQ predictive control

In this paper linear quadratic control of systems subject to input and/or state constraints, is considered. The solution to the corresponding quadratic programming problem is based on the so called mixed weights least-squares method. It is shown that, like in the unconstrained case, dynamic programming can be used in order to considerably alleviate the computational burden.