Towards Industrialization of FOPID Controllers: A Survey on Milestones of Fractional-Order Control and Pathways for Future Developments

Abstract

The interest in fractional-order (FO) control can be traced back to the late nineteenth century. The growing tendency towards using fractional-order proportional-integral-derivative (FOPID) control has been fueled mainly by the fact that these controllers have additional "tuning knobs" that allow coherent adjustment of the dynamics of control systems. For instance, in certain cases, the capacity for additional frequency response shaping gives rise to the generation of control laws that lead to superior performance of control loops. These fractional-order control laws may allow fulfilling intricate control performance requirements that are otherwise not in the span of conventional integer-order control systems. However, there are underpinning points that are rarely addressed in the literature: (1) What are the particular advantages (in concrete figures) of FOPID controllers versus conventional, integer-order (IO) PID controllers in light of the complexities arising in the implementation of the former? (2) For real-time implementation of FOPID controllers, approximations are used that are indeed equivalent to high-order linear controllers. What, then, is the benefit of using FOPID controllers? Finally, (3) What advantages are to be had from having a near-ideal fractional-order behavior in control practice? In the present paper, we attempt to address these issues by reviewing a large portion of relevant publications in the fastgrowing FO control literature, outline the milestones and drawbacks, and present future perspectives for industrialization of fractional-order control. Furthermore, we comment on FOPID controller tuning methods from the perspective of seeking globally optimal tuning parameter sets and how this approach can benefit designers of industrial FOPID control. We also review some CACSD (computer-aided control system design) software toolboxes used for the design and implementation of FOPID controllers. Finally, we draw conclusions and formulate suggestions for future research.

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“…The use of FO controllers should be properly justified by superior performance or at least the same efficiency as the conventional controllers. A Technology Readiness Level(TRL) may have to be established for an industry-implementation ready FO controller [152].…”

Novel Fractional-Order Model Predictive Control: State-Space Approach

“…It could be a problem, for instance, for the industrial devices like programmable logic controllers (PLC) due to they limitations on memory storage and microprocessor speed. Some very useful notes and a list of references on design and implementation methods were described in [26]. Moreover, an explicit MPC optimization can also be implemented in real time even on very simple devices such as PLC by using an idea for reducing the required memory size of the optimization algorithm with help of method proposed in [27].…”

Design and Control of Grid-Connected PWM Rectifiers by Optimizing Fractional Order PI Controller Using Water Cycle Algorithm

“…It can provide more tuning flexibility and better design specifications. Future focus should be to evolve the tools and directions so as to implement the transition to FOPID controllers [7]. The author has used FOPID in hybrid renewable power plant for the purpose of integration through a voltage source inverter.…”

“…FOPID controllers offer much better adaptive behavior due to its five parameters available for tuning. The tuning algorithm for FOPID controllers are reviewed in [7] .The different methods have been applied for tuning of FOPID controller parameters in the literature such as simulated annealing, genetic algorithm, chaotic ant swarm, grey wolf optimization, particle swarm optimization, slap swarm algorithm, colliding bodies optimization, tabu search based algorithm, continuous state transition, moth flame, fire-fly and other meta-heuristic algorithms [7]. FOPID controllers are applied to AVR systems in many research papers and different optimization techniques have been used…”