Invariant immersion method for adaptive robust control of complex electromechanical moving objects with compensation of uncertainties, input constraints and unknown external disturbances

This paper investigates the problem of adaptive and robust control for complex electromechanical moving objects (CEMMO) under conditions of parametric uncertainty, uncertain input matrix, control input constraints, and unknown external disturbances. A nonlinear mathematical model of CEMO is developed in the form of Lagrange-Euler equations, accounting for external disturbances and control input constraints. A novel adaptive robust control system for CEMMO is developed, which ensures high performance even under the simultaneous action of parametric uncertainty, uncertain input matrix, input control constraints, and unknown external disturbances. A disturbance observer is synthesized based on the invariant immersion method, whose estimation accuracy is determined by parameter selection and the bound of the second derivative of the total disturbance vector. The developed adaptive robust tuning law with σ-modification, designed under invariant immersion conditions, ensures not only flexible formation of estimation error dynamics in complex nonlinear systems under parametric uncertainties, but also convergence of unknown parameter estimates to their true values. An auxiliary dynamic subsystem is introduced specifically to compensate for input signal saturation effects while maintaining unchanged control system accuracy. Stability analysis demonstrates boundedness and exponential convergence of all closed-loop system signals to the largest invariant set. The results of simulation experiments confirm the operability and efficiency of the proposed adaptive robust control algorithm.

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

Direction: Electrical Engineering

Keywords: complex electromechanical moving objects (CEMMO), adaptive robust control, invariant immersion method (I&I), disturbance observer, function approximation method, Lyapunov functions method, parametric uncertainty, input matrix uncertainty, input constraints, unknown external disturbances

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