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Öğe FOPID Controllers and Their Industrial Applications: A Survey of Recent Results(Elsevier, 2018) Tepljakov, Aleksei; Alagoz, Baris Baykant; Yeroglu, Celaleddin; Gonzalez, Emmanuel; HosseinNia, S. Hassan; Petlenkov, EduardThe interest towards using Fractional-order (FO) PID controllers in the industry is mainly fueled by the fact that these controllers have two additional tuning knobs that can be used to adjust the control law in a way that would benefit the control loop. However, there are certain points that are rarely addressed in literature, namely: (1) What are the particular advantages (in concrete numbers) of FOPID controllers versus conventional, integer-order (IO) PID controllers in the light of complexities arising in the implementation of the former? (2) For real-time implementation of FOPID controllers, approximations are used that are equivalent to high order linear controllers. What, then, is the benefit of using FOPID controllers? In the present paper, we attempt to address these issues by reviewing recent literature in the field and by providing relevant analysis and recommendations. (C) 2018, IFAC (International Federation of Automatic Control) Hosting by Elsevier Ltd. All rights reserved.Öğe A Numerical Study for Plant-Independent Evaluation of Fractional-order PID Controller Performance(Elsevier, 2018) Alagoz, Baris Baykant; Tepljakov, Aleksei; Yeroglu, Celaleddin; Gonzalez, Emmanuel; HosseinNia, S. Hassan; Petlenkov, EduardA stunning outcome of fractional calculus for control practice are fractional-order PID (FOPID) controllers. Based on their experimental and numerical results, several studies have reported improvements in control performance of closed loop control systems by FOPID controllers compared to classical PID controllers. However, the industry at large is still cautious about adopting FOPID controllers because of the lack of concrete data about the related cost benefit trade-off. Main concerns arise at the point that there have not been a quantitative evaluation scheme that clearly demonstrates for which concrete cases FOPID controllers can provide considerable improvements in control. Therefore, there is a need for more thorough theoretical and quantitative demonstrations. To that end, this study presents a plant function independent evaluation methodology to reveal inherent advantages of FOPID control. Impacts of two additional controller coefficients, namely fractional orders of differentiator and integrator, are analyzed in the frequency domain and their contributions to open loop gain maximization, phase margin and Reference to Disturbance Rate (RDR) performance are investigated. (C) 2018, IFAC (International Federation of Automatic Control) Hosting by Elsevier Ltd. All rights reserved.Öğe Optimal Fractional Order PID Controller Design for Fractional Order Systems by Stochastic Multi Parameter Divergence Optimization Method with Different Random Distribution Functions(Ieee, 2019) Ates, A.; Alagoz, B. B.; Chen, Y. Q.; Yeroglu, C.; HosseinNia, S. HassanThis paper modifies Stochastic Multi Parameter Divergence Optimization Method (SMDO) by using some types of random distribution functions in order to show effects of different random distribution functions on optimization performance. SMDO is a parameter wise random search algorithm in random walk class. A prominent feature of SMDO method lies in using random number with standard uniform distribution while diverging a parameter of solution point in backward and forward directions to reach an optimal solution. SMDO method benefits from the success of random backward and forward divergences. This study investigates effects of four types of random distribution functions on performance of SMDO algorithm for controller tuning problem. These distributions are Chi-Square Distribution (CSD), Rayleigh Distribution (RD), Log Normal Distribution (LND) and Uniform random (LTD) distribution. To illustrate effects of these random distribution functions, SMDO is employed to fractional order PID (FOPID) controller tuning problems for fractional order model (FOM) and results obtained for different distribution functions are demonstrated.