Comparative Analysis of Parametric Robustness of Nonlinear Algorithms for Tracking Control of a Flight Quadcopter under Conditions of Variable Load and External Disturbances

In recent years, the popularity of small multirotor unmanned aerial vehicles and, in particular, quadrocopters (QC) has increased significantly, due to both their characteristics and the low cost of manufacturing and operation. At the same time, one of the promising ways to increase the efficiency of using QC to solve a wide variety of tasks in both civilian and military spheres is to improve the flight control algorithms of the spacecraft. However, despite the presence of numerous classical and modern methods for synthesizing flight control algorithms, many of them turn out to be ineffective in conditions of a priori uncertainty of the mathematical model of vehicle dynamics, as well as in conditions of wind disturbance. QC as an object of control is a complex, nonlinear, multidimensional, multi-connected dynamic system of the 12th order with the presence of indeterminate parameters and external disturbances. The paper considers the problem of synthesizing an algorithm for the subsequent flight control of a spacecraft, which provides tracking by a vector of controlled variables of its arbitrarily set, programmatic change. As indicators of the effectiveness of the synthesized monitoring control algorithm, the QC summer uses, firstly, direct indicators of the quality of the control process (control time and overshoot), characterizing the speed and tendency of the system to oscillate, and, secondly, the maximum amplitude of the controlling effects, characterizing the energy consumption for their generation. The article is devoted to a comparative analysis of the parametric robustness properties of QC flight tracking algorithms synthesized on the basis of the most popular modern methods of nonlinear control of dynamic objects: the sliding mode method, the integrator bypass method, the feedback linearization method, the MPC proactive control method, the "deep" feedback method, the method of inverse dynamics problems with compensation for non-linearity. At the same time, the effectiveness of the synthesized flight tracking control algorithms was analyzed by computer verification in the Python environment under conditions of variable load and uncontrolled disturbing wind effects.