Unmanned aerial vehicle must be controllable and fend off disturbing influences. The quality and effectiveness of fulfilling these tasksare completely determined by the instrumentation system and the software of the control system, which ensures the safety and reliability of the unmanned aerial vehicle. The synthesis of adaptive control algorithms in the presence of disturbances in most cases suggests the use of a certain disturbance model and is associated with the use of integral regulators, which increases the order of the system, and sometimes they are substantially non-linear. Adaptive algorithms use both predictive methods for assessing the dynamics of an object. For the synthesis of the control system, was considered the dynamic model of an unmanned aerial vehicle as a solid. Then the linearized equations of transverse motion can be represented by a system of differential equations. The study performed the synthesis of control system regulators by integrating the equations of the dynamic model of the object for a given control program, made a forecast of the movement of an unmanned aerial vehicle for a certain final period of time. By optimization of program control, was taking into account the restrictions imposed on the control and adjustable variables, the adjustable variables of the forecasting model approach the corresponding control signals on the forecast horizon. At the calculation step, which is a fixed small part of the forecast horizon, the optimal control found was realized and the actual state of the unmanned aerial vehicle was measured at the end of the step. The forecast horizon moves forward one step, and this procedure is repeated. The efficiency of the model predictive control as synthesis method for unmanned aerial vehicle’s control system is analyzed. A new synthesis method of adaptive control system with guaranteed accuracy under an arbitrary external disturbance is shown. The method is based on evaluating the effect of disturbances, predicting the behavior of the system and compensating the impact on the control object by the formation of a law for changing the parameters of the additional controller, which does not directly affect the quality of the control system.The results of control system’s mathematical modeling for aircraft and multicopter types of unmanned aerial vehicles are presented.
Research on the Unmanned Aerial Vehicle Adaptive Control System based on Fuzzy Control and Chaos Mechanics
