LAUSR

Abstract A novel formulation for infinite horizon model predictive control that is general and can accurately approximate and minimize the control cost is proposed. This method allows output tracking over a finite horizon when constraints are considered and equilibrium tracking in the linearized dynamics after that for the infinite horizon when constraints are not considered. The method allows prescribing weights simultaneously on the output tracking error, control rates, and control energy. Methods of weight selection are discussed to ensure strong cost convexity for reliable optimization. The control method is used to bring a helicopter that is far from a ship to a stable flight condition that is much closer to the ship. This is very important for helicopter ship landing automation.