Izvorni znanstveni članak
https://doi.org/10.1080/00051144.2019.1688508
Performance enhancement of multivariable model reference optimal adaptive motor speed controller using error-dependent hyperbolic gain functions
Omer Saleem
; Department of Electrical Engineering, National University of Computer and Emerging Sciences, Lahore, Pakistan
Mohsin Rizwan
; Department of Mechatronics and Control Engineering, University of Engineering & Technology, Lahore, Pakistan
Khalid Mahmood-ul-Hasan
; Department of Electrical Engineering, University of Engineering and Technology, Lahore, Pakistan
Muaaz Ahmad
; Department of Electrical Engineering, National University of Computer and Emerging Sciences, Lahore, Pakistan
Sažetak
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–torque 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.
Ključne riječi
Model reference adaptive control; LQI control; Lyapunov theory; hyperbolic function; QNET 2.0 DC Motor Board
Hrčak ID:
239857
URI
Datum izdavanja:
3.12.2019.
Posjeta: 613 *