Synthesis of an adaptive robust control system for a tricopter with rotary propellers under conditions of uncertain aerodynamic coefficients, partially uncertain input matrix, influence of external disturbances and input constraints

In this article, an adaptive robust control system for a tricopter equipped with three rotary propellers is developed and studied under the following conditions: a) uncertain aerodynamic coefficients; b) partially uncertain input matrix; c) influence of unknown external disturbances; and d) input constraints. When constructing a complete nonlinear mathematical model of the dynamics of a tricopter with rotary propellers in the form of Lagrange-Euler equations, the input constraints are taken into account. The synthesis of an adaptive robust control system for a tricopter with rotary propellers is carried out on the basis of the modified computed torque control (Li–Slotine method) and the function approximation technique to eliminate the influence of uncertainty. Unknown external disturbances are compensated by a smooth sliding mode control using an adaptive estimate of the upper bound of the sum of external disturbances and approximation errors of uncertain functions in the mathematical model. To compensate for the negative effects of input constraints, an auxiliary dynamic system is constructed, the state variables of which are used to synthesize the control law. The robustness of the adaptive system and the desired tracking accuracy of the reference signals are proven using the Lyapunov function method. Simulation results using MatLab/Simulink are presented to illustrate the effectiveness of the proposed control law.

Authors: Duy Khanh Nguyen, V. V. Putov, V. N. Sheludko

Direction: Electrical Engineering

Keywords: tricopter with rotary propellers, adaptive robust control system, modification of the computed torque control, function approximation method, smooth sliding mode control, auxiliary dynamic system, input constraints, partial uncertainty of the input matrix, uncertain aerodynamic coefficients, unknown external disturbances, modeling

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