Yazar "Herencsar, Norbert" seçeneğine göre listele

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    2DOF multi-objective optimal tuning of disturbance reject fractional order PIDA controllers according to improved consensus oriented random search method
    (Elsevier, 2020) Ozbey, Necati; Yeroglu, Celaleddin; Alagoz, Baris Baykant; Herencsar, Norbert; Kartci, Aslihan; Sotner, Roman
    This study presents a Fractional Order Proportional Integral Derivative Acceleration (FOPIDA) controller design methodology to improve set point and disturbance reject control performance. The proposed controller tuning method performs a multi-objective optimal fine-tuning strategy that implements a Consensus Oriented Random Search (CORS) algorithm to evaluate transient simulation results of a set point filter type Two Degree of Freedom (2DOF) FOPIDA control system. Contributions of this study have three folds: Firstly, it addresses tuning problem of FOPIDA controllers for first order time delay systems. Secondly, the study aims fine-tuning of 2DOF FOPIDA control structure for improved set point and disturbance rejection control according to transient simulations of implementation models. This enhances practical performance of theoretical tuning method according to implementation requirements. Thirdly, the paper presents a hybrid controller tuning methodology that increases effectiveness of the CORS algorithm by using stabilizing controller coefficients as an initial configuration. Accordingly, the CORS algorithm performs the fine-tuning of 2DOF FOPIDA controllers to achieve an improved set point and disturbance rejection control performances. This fine-tuning is carried out by considering transient simulation results of 2DOF FOPIDA controller implementation model. Moreover, Reference to Disturbance Ratio (RDR) formulation of the FOPIDA controller is derived and used for measurement of disturbance rejection control performance. Illustrative design examples are presented to demonstrate effectiveness of the proposed method. (C) 2020 The Authors. Published by Elsevier B.V. on behalf of Cairo University.
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    Analogue Implementation of a Fractional-Order PI? Controller for DC Motor Speed Control
    (Ieee, 2019) Herencsar, Norbert; Kartci, Aslihan; Koton, Jaroslav; Sotner, Roman; Alogoz, Baris Baykant; Yeroglu, Calaleddin
    In this paper, an approach to design a fractional-order integral operator s(lambda) where -1 < lambda <0, using an analogue technique, is presented. The integrator with a constant phase angle -80.1 degree (i.e. order lambda = -0.89), bandwidth greater than 3 decades, and maximum relative phase error 1.38% is designed by cascade connection of first-order bilinear transfer segments and first-order low-pass filter. The performance of suggested realization is demonstrated in a fractional-order proportional-integral (FOPI lambda) controller described with proportional constant 1.37 and integration constant 2.28. The design specification corresponds to a speed control system of an armature controlled DC motor, which is often used in mechatronic and other fields of control theory. The behavior of both proposed analogue circuits employing two-stage Op-Amps is confirmed by SPICE simulations using TSMC 0.18 mu m level-7 LA) EN SCN018 CMOS process parameters with +/- 0.9 V supply voltages.
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    Electronically reconfigurable two-path fractional-order PI/D controller employing constant phase blocks based on bilinear segments using CMOS modified current differencing unit
    (Elsevier Sci Ltd, 2019) Sotner, Roman; Jerabek, Jan; Kartci, Aslihan; Domansky, Ondrej; Herencsar, Norbert; Kledrowetz, Vilem; Alagoz, Baris Baykant
    This work introduces a versatile type of electronically controllable bilinear transfer segments, i.e. two ports allowing independent electronic control of zero and pole of transfer function, based on modified current differencing unit (MCDU) active element. These proposed bilinear transfer segments serve for construction of fractional-order constant phase block (phi(alpha) = +/- 15 degrees and +/- 36 degrees, i.e. orders alpha = +/- 1/6 and +/- 2/5, tested in our case) representing electronically controllable integrator or differentiator (in dependence on current demand) as a part of novel two-path system of the fractional-order proportional-integral or derivative (FOPI/D) controller. The example of design procedure employs four bilinear transfer segments, electronically controllable proportional path and summing stage. Cadence IC6 Spectre simulation results (TSMC 0.18 mu m CMOS process) in both frequency and time domain are performed in order to confirm expected behavior of the system. An application of the proposed FOPI controller in control of linear voltage regulator is also demonstrated and performance improvements of the proposed design are discussed.
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    Optimal F-domain stabilization technique for reduction of commensurate fractional-order SISO systems
    (Springernature, 2022) Mahata, Shibendu; Herencsar, Norbert; Alagoz, Baris Baykant; Yeroglu, Celaleddin
    This paper presents a new approach for reduction of commensurate fractional-order single-input-single-output systems. The minimization in the frequency response error of the reduced order model (ROM) relative to the original system is carried out in the F-plane. A constrained optimization technique is introduced to satisfy the angle criteria for F-domain stability of the proposed ROM. Significant improvements in both the time- and frequency-responses over the recently published literature are illustrated using several numerical examples.
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    Reduced order infinite impulse response system identification using manta ray foraging optimization
    (Elsevier, 2024) Mahata, Shibendu; Herencsar, Norbert; Alagoz, Baris Baykant; Yeroglu, Celaleddin
    This article presents a useful application of the Manta Ray Foraging Optimization (MRFO) algorithm for solving the adaptive infinite impulse response (IIR) system identification problem. The effectiveness of the proposed technique is validated on four benchmark IIR models for reduced order system identification. The stability of the proposed estimated IIR system is assured by incorporating a pole-finding and initialization routine in the search procedure of the MRFO algorithm and this algorithmic modification contributes to the MRFO algorithm when seeking stable IIR filter solutions. The absence of such a scheme, which is primarily the case with the majority of the recently published literature, may lead to the generation of an unstable IIR filter for unknown real-world instances (particularly when the estimation order increases). Experiments conducted in this study highlight that the proposed technique helps to achieve a stable filter even though large bounds for the design variables are considered. The convergence rate, robustness, and computational speed of MRFO for all the considered problems are investigated. The influence of the control parameters of MRFO on the design performances is evaluated to gain insight into the interaction between the three foraging strategies of the algorithm. Extensive statistical performance analyses employing various non-parametric hypothesis tests concerning the design consistency and convergence are conducted for comparison of the proposed MRFO-based approach with six other metaheuristic search procedures to investigate the efficiency. The results on the mean square error metric also highlight the improved solution quality of the proposed approach compared to the various techniques published in the literature.
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    A Robust Frequency-Domain-Based Order Reduction Scheme for Linear Time-Invariant Systems
    (Ieee-Inst Electrical Electronics Engineers Inc, 2021) Mahata, Shibendu; Herencsar, Norbert; Alagoz, Baris Baykant; Yeroglu, Celaleddin
    This paper presents a robust model order reduction technique with guaranteed stability, minimum phase, and matched steady-state response for linear time-invariant single-input-single-output systems. The proposed approach is generalized, allowing the designer to select any desired order of the reduced-order model (ROM). In contrast to the published literature, which primarily uses the time-domain behavior, the proposed technique utilizes the frequency-domain information of the full-order system. The suggested strategy allows the determination of the optimal ROM in a single step, simpler than the various recently reported mixed methods. The robustness is demonstrated using convergence studies and statistical measures about the final solution quality and model coefficients. The superiority over the recent literature is illustrated through four numerical examples using various time-domain and frequency response performance metrics.
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    A theoretical demonstration for reinforcement learning of PI control dynamics for optimal speed control of DC motors by using Twin Delay Deep Deterministic Policy Gradient Algorithm
    (Pergamon-Elsevier Science Ltd, 2023) Tufenkci, Sevilay; Alagoz, Baris Baykant; Kavuran, Gurkan; Yeroglu, Celaleddin; Herencsar, Norbert; Mahata, Shibendu
    To benefit from the advantages of Reinforcement Learning (RL) in industrial control applications, RL methods can be used for optimal tuning of the classical controllers based on the simulation scenarios of operating con-ditions. In this study, the Twin Delay Deep Deterministic (TD3) policy gradient method, which is an effective actor-critic RL strategy, is implemented to learn optimal Proportional Integral (PI) controller dynamics from a Direct Current (DC) motor speed control simulation environment. For this purpose, the PI controller dynamics are introduced to the actor-network by using the PI-based observer states from the control simulation envi-ronment. A suitable Simulink simulation environment is adapted to perform the training process of the TD3 algorithm. The actor-network learns the optimal PI controller dynamics by using the reward mechanism that implements the minimization of the optimal control objective function. A setpoint filter is used to describe the desired setpoint response, and step disturbance signals with random amplitude are incorporated in the simu-lation environment to improve disturbance rejection control skills with the help of experience based learning in the designed control simulation environment. When the training task is completed, the optimal PI controller coefficients are obtained from the weight coefficients of the actor-network. The performance of the optimal PI dynamics, which were learned by using the TD3 algorithm and Deep Deterministic Policy Gradient algorithm, are compared. Moreover, control performance improvement of this RL based PI controller tuning method (RL-PI) is demonstrated relative to performances of both integer and fractional order PI controllers that were tuned by using several popular metaheuristic optimization algorithms such as Genetic Algorithm, Particle Swarm Opti-mization, Grey Wolf Optimization and Differential Evolution.