A fractional computational algorithm for designing advanced feedback controllers of dynamical nonlinear systems
by Ammar Soukkou; Salah Leulmi
International Journal of Modelling, Identification and Control (IJMIC), Vol. 26, No. 2, 2016

Abstract: This paper contributes a new alternative for the designing of a simple and efficient controller extracted from a partially complex approach for controlling complex dynamical systems. The developed adjustable form of fractional-order proportional-integral (A2Fo-PI) controller with optimal structure and parameters represents a powerful and simple approach to provide a reasonable tradeoff between computational overhead, storage space and numerical accuracy in the modelling and control of dynamical nonlinear systems. The multiobjective genetic learning algorithm with chaotic mutation, adopted in this work, can be visualised as a combination of structural and parametric genes of a controller orchestrated in a hierarchical fashion and is applied to select an optimal knowledge base, which characterises the developed controller, and satisfies various contradictory design specifications such as simplicity, accuracy, stability and robustness. Good simulation results have been obtained in regulation of the activated sludge process (ASP) in a highly disturbed environment and with transient behaviour, showing the efficiency of the proposed design and demonstrating that the proposed A2Fo-PI offers encouraging advantages and has better performances.

Online publication date: Mon, 15-Aug-2016

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