Stability Enhancement of Aircraft Ground Handling Qualities via Model Predictive Control Allocation

Control allocation is a fundamental task to achieve efficient distribution of the control effort in an over-actuated mechanical system. The conventional approach to tackle this problem is to assume that the actuator’s dynamics are negligible with respect to the rest of the system so that the problem can be posed as a static allocation task. In the field of aircraft ground handling, the actuators used to steer the aircraft might have significantly different dynamics, being also subject to delays, thus invalidating the static allocation assumptions. In this paper, we propose using a Model Predictive Control Allocation (MPCA) strategy to cope with the actuator’s dynamics. An analytical model of a tricycle landing gear aircraft is derived and used to pose the control allocation problem. Then, the MPCA optimization problem is formulated and successfully evaluated in a validated multibody simulator for a target aircraft against a static allocation strategy. The results show that the MPCA is effective in preventing instabilities induced by delays and rate limits in the actuators, as well as in ensuring superior tracking performance.