# Goals and Objectives

Model Predictive Control approaches formulate the control problem as an optimisation problem in which the control to be applied to the system at hand is one that minimises a cost function made up of tracking error and control activity. In general the tracking error component comprises one measure of predicted tracking error for every sample time interval from the present up to a given prediction horizon time (generally a large number of intervals). This optimisation and computation of the corresponding control law are very computationally expensive. The general technique Model Predictive Control (MPC) promises specific benefits for the control of highly dynamic systems such as aircraft because of its pre-emptive action, ability to handle system constraints and to minimise future tracking errors because of its use of in-built system models. These advantages of MPC allow it to potentially have a better control and tracking performance compared to classical control techniques which are currently in use. Standard MPC, however, involves a high computational load due to high-rate prediction requirements. In contrast Algebraic Model Predictive Control is able to use only a few predictions points and multiple horizon lengths for multi-input-multi-output situations, and accordingly has significant computational performance benefits and is amenable to simpler design strategies. The exact algebraic nature of AMPC allows the control problem to be solved using a deterministic solution rather than a numerical optimization technique which is required with standard MPC. A complete demonstration of this method’s potential will provide a powerful new method of control for manned and unmanned aerial vehicles. A particular strength is its potential as an effective means of gust attenuation because of its predictive qualities. Predictive gust attenuation would have a significant impact in the design, efficiency and safety of aerial vehicles. Aircraft structures would not have to be designed to handle as large gust loads, resulting in lighter and more efficient vehicles. The ability to predict the aircraft response from future gusts and apply hard constraints in the MPC solution (i.e. ground level) would minimise accidents resulting from gusts, particularly on landing.