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This article presents a robust adaptive controller for electrically driven robots using Bernstein polynomials as universal approximator. The lumped uncertainties including unmodeled dynamics, external disturbances, and nonimplemented control signals (they assumed as a function of time, instead a function of several variables) are represented with this powerful mathematical tool. The polynomial coefficients are then tuned based on the adaptation law obtained in the stability analysis. A comprehensive approach is adopted to include the saturated and unsaturated areas and also the transition between these areas in the stability analysis. As a result, the stability and the performance of the proposed controller have been improved considerably in dealing with actuator saturation. Also, in comparison with a recent paper based on uncertainty estimation using Taylor series, the proposed controller is less computational due to reducing the size of the matrix of convergence rate. A performance evaluation has been carried out to verify satisfactory performance of transient response of the controller.Simulation results on a Puma560 manipulator actuated by geared permanent magnet dc motors have been presented to guarantee its satisfactory performance. K E Y W O R D Sactuator saturation, adaptive uncertainty estimation, Bernstein polynomials, electrically driven robots, stability analysis 1 Int J Robust Nonlinear Control. 2020;30:2719-2735.wileyonlinelibrary.com/journal/rnc

Real-time fractional-order control of electrically driven flexible-joint robots has been addressed in this article. An important contribution of this article is that the control law is designed based on the Fourier series that eliminates the need for computation of regressor matrix. Moreover, the nonlinear effects of actuator saturation are considered in the control law. The lumped uncertainty can be approximated using Fourier series with unknown coefficients. Then, the unknown coefficients are estimated using the adaptation law obtained in the stability analysis. The overall closed-loop system is proven to be robust and bounded-input bounded-output stable. In addition, it has been shown that the joint-position errors are uniformly bounded based on Lyapunov’s stability concept. The satisfactory performance of the proposed control scheme is verified by experimental results. To highlight the superiority of the proposed method, experimental results of two voltage-based controllers are also presented.