Regular Papers

International Journal of Control, Automation and Systems 2021; 19(2): 931-941

Published online December 6, 2020

https://doi.org/10.1007/s12555-020-0209-z

© The International Journal of Control, Automation, and Systems

Adaptive State-space Control of Under-actuated Systems Using Error-magnitude Dependent Self-tuning of Cost Weighting-factors

Omer Saleem* and Khalid Mahmood-ul-Hasan

National University of Computer and Emerging Sciences

Abstract

This article methodically constructs a novel adaptive self-tuning state-space controller that enhances the robustness of under-actuated systems against bounded exogenous disturbances. The generic Linear-Quadratic-Regulator (LQR) is employed as the baseline controller. The main contribution of this article is the formulation of a hierarchical online gain-adjustment mechanism that adaptively modulates the weighting-factors of LQR’s quadratic-performance-index by using pre-calibrated continuous hyperbolic scaling functions. The hyperbolic scaling functions are driven by the magnitude of system’s state-error variables. This augmentation dynamically updates the solution of the Matrix-Riccati-Equation which modifies the state-feedback gains after every sampling interval. The efficacy of the proposed adaptive controller is validated by conducting hardware-in-the-loop experiments on QNET Rotary Pendulum setup. The experimental outcomes show that the proposed adaptive control scheme yields stronger damping against oscillations and faster error-convergence rate, while maintaining the controller’s asymptotic-stability, under the influence of parametric uncertainties.

Keywords Hyperbolic scaling function, linear quadratic regulator, performance-index, rotary pendulum, selftuning, weighting-factors.

Article

Regular Papers

International Journal of Control, Automation and Systems 2021; 19(2): 931-941

Published online February 1, 2021 https://doi.org/10.1007/s12555-020-0209-z

Copyright © The International Journal of Control, Automation, and Systems.

Adaptive State-space Control of Under-actuated Systems Using Error-magnitude Dependent Self-tuning of Cost Weighting-factors

Omer Saleem* and Khalid Mahmood-ul-Hasan

National University of Computer and Emerging Sciences

Abstract

This article methodically constructs a novel adaptive self-tuning state-space controller that enhances the robustness of under-actuated systems against bounded exogenous disturbances. The generic Linear-Quadratic-Regulator (LQR) is employed as the baseline controller. The main contribution of this article is the formulation of a hierarchical online gain-adjustment mechanism that adaptively modulates the weighting-factors of LQR’s quadratic-performance-index by using pre-calibrated continuous hyperbolic scaling functions. The hyperbolic scaling functions are driven by the magnitude of system’s state-error variables. This augmentation dynamically updates the solution of the Matrix-Riccati-Equation which modifies the state-feedback gains after every sampling interval. The efficacy of the proposed adaptive controller is validated by conducting hardware-in-the-loop experiments on QNET Rotary Pendulum setup. The experimental outcomes show that the proposed adaptive control scheme yields stronger damping against oscillations and faster error-convergence rate, while maintaining the controller’s asymptotic-stability, under the influence of parametric uncertainties.

Keywords: Hyperbolic scaling function, linear quadratic regulator, performance-index, rotary pendulum, selftuning, weighting-factors.

IJCAS
July 2024

Vol. 22, No. 7, pp. 2055~2340

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