This article concerns a previously developed, Fractional-order, Generalised Predictive Control (FGPC) approach to control system design. Here, fractional order concepts are utilised to extend the design flexibility of the FGPC algorithm, in comparison to conventional Generalised Predictive Control (GPC). The performance of FGPC is investigated via Monte Carlo simulation. With a focus on plots of the closed-loop eigenvalues, these results are utilised to develop recommendations for how to optimise the extra design coefficients introduced in the fractional order case. One of the simulation examples involves a hydraulically actuated robotic manipulator. Finally, FGPC methods are applied to control airflow in a laboratory 1 m by 2 m by 2 m forced ventilation environmental test chamber.
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