%0 Journal Article
%T Performance enhancement of multivariable model reference optimal adaptive motor speed controller using error-dependent hyperbolic gain functions
%A Khalid Mahmood-ul-Hasan
%A Mohsin Rizwan
%A Muaaz Ahmad
%A Omer Saleem
%J Automatika
%D 2020
%R https://doi.org/10.1080/00051144.2019.1688508
%X The main contribution of this paper is to formulate a robust-adaptive and stable state-space speed control strategy for DC motors. The linear-quadratic-integral (LQI) controller is utilized as the baseline controller for optimal speed-regulation, accurate reference-tracking and elimination of steady-state fluctuations in the motor¡¯s response. To reject the influence of modelling errors, the LQI controller is augmented with a Lyapunov-based model reference adaptation system (MRAS) that adaptively modulates the controller gains while maintaining the asymptotic stability of the controller. To further enhance the system¡¯s robustness against parametric uncertainties, the adaptation gains of MRAS online gain-adjustment law are dynamically adjusted, after every sampling interval, using smooth hyperbolic functions of motor¡¯s speed-error. This modification significantly improves the system¡¯s response-speed and damping against oscillations, while ensuring its stability under all operating conditions. It dynamically re-configures the control-input trajectory to enhance the system¡¯s immunity against the detrimental effects of random faults occurring in practical motorized systems such as bounded impulsive-disturbances, modelling errors, and abrupt load¨Ctorque variations. The efficacy of the proposed control strategy is validated by conducting credible hardware-in-the-loop experiments on QNET 2.0 DC Motor Board. The experimental results successfully validate the superior tracking accuracy and disturbance-rejection capability of the proposed control strategy as compared to other controller variants benchmarked in this article
%U https://www.tandfonline.com/doi/full/10.1080/00051144.2019.1688508