Abstract
This paper proposes a conceptual approach to the autonomous takeoff and landing control of autonomous mobile nodes (AMNs) based on the Total Energy Control System (TECS) methodology. The study aims to enhance the operational efficiency and survivability of unmanned aviation by utilizing the aircraft's energy state as a fundamental control invariant. The proposed approach overcomes the limitations of traditional systems, specifically their high sensitivity to stochastic disturbances and degraded stabilization accuracy under atmospheric turbulence. The control algorithm is optimized based on two criteria: minimizing the deviation of the AMN's total energy from the reference flight trajectory and minimizing the imbalance between kinetic and potential energies to stabilize the rate of descent (or climb). Simulation results demonstrate that the implementation of this method provides robust resilience to external dynamic disturbances, mitigates the human factor, and enables mission execution under adverse weather conditions without rigid dependence on ground-based airfield infrastructure. Future research will focus on scaling the approach to multi-agent systems, integrating adaptation methods based on random projections, and field testing on fixed-wing platforms.