Coordinated deviation correction control for aircraft multi-actuators based on time-varying model predictive control

Runway excursions represent a significant percentage of aviation incidents, highlighting the critical limitations of current ground control methods, often restricted to a single actuator. This impedes the safe and synergistic use of multiple control surfaces for deviation correction of aircraft taxiing. To address the question, this paper proposes a novel coordinated multi-actuator control method based on a time-varying model predictive control (MPC) framework. The comprehensive methodology begins with a high-fidelity dynamic model of the aircraft’s ground taxiing phase, precisely considering complex nonlinear phenomena such as aerodynamic forces, ground friction dynamics, and tire side-slip characteristics. This model is then formulated as a linear time-varying state-space representation, which is suitable for the MPC framework. Building upon this model, a robust hierarchical inner-outer loop control architecture is designed for the systematic deviation correction task. Using a dynamic virtual target point guiding law, the outer loop converts the aircraft’s lateral position divergence from the runway centerline into an exact yaw angle instruction for the inner loop. The inner loop forms the core of the strategy, utilizing MPC for robust, coordinated control of the three primary actuators: rudder, nose wheel steering, and differential braking. A key innovation is a control weight matrix in the MPC cost function that adjusts dynamically with real-time taxiing speed. This adaptive weighting mechanism optimizes control inputs online, intelligently allocating authority across the full speed range. At high speeds, it gives priority to the rudder; at lower speeds, it smoothly switches to nose wheel steering and differential braking. For validation, a comprehensive 6-degree-of-freedom dynamic simulation platform was developed in MATLAB/Simulink. The strategy was rigorously tested under challenging conditions, including wet runways, crosswinds, and significant initial landing deviations. Simulation results consistently demonstrate that the controller enables fast, stable tracking of the runway centerline. The system effectively manages these complex scenarios, realizing smooth, efficient coordination among the actuators.