This article presents an intelligently optimised self-tuning fractional-order control scheme to improve the attitude-stabilisation of an inverted pendulum. Primarily, the scheme employs two Fractional-order Proportional-Derivative (FPD) controllers acting concurrently on the system to minimise the deviations in its state-trajectories. Wherein, one FPD controller compensates the variations in pendulum-angle and its fractional-order derivative to vertically balance the pendulum, where as the other FPD controller acts as a position controller and regulates the variations in arm-angle and its fractional-order derivative. The integration of fractional calculus with conventional PD controllers optimises the reference-tracking performance of the control scheme by increasing its degrees-of-freedom and design flexibility. In order to further improve the system’s immunity against exogenous disturbances, the PD gains of each controller are dynamically adjusted after each sampling interval using piecewise nonlinear functions of their respective state-variations. The hyper-parameters of the nonlinear gain-adjustment functions as well as the fractional-number power of the derivative-operator of each controller are selected via Particle-Swarm-optimisation (PSO) algorithm. The proposed adaptive control scheme is tested on the QNET Rotary Inverted Pendulum setup via ‘hardware-in-the-loop’ experiments. The optimality and robustness of the proposed control scheme are validated by comparing its performance with PSO-based fixed-gain dual-PD and dual-FPD control schemes.
No takes yet. Share an insight, caveat, or question.
Saleem et al. (2019) studied this question.
Synapse has enriched 2 closely related papers on similar clinical questions. Consider them for comparative context: