2DOF multi-objective optimal tuning of disturbance reject fractional order PIDA controllers according to improved consensus oriented random search method

Özbey, Necati; Yeroğlu, Celaleddin; Alagöz, Barış Baykant; Herencsár, Norbert; Kartci, Aslihan; Šotner, Roman

doi:10.1016/j.jare.2020.03.008

Cited by 13 publications

(7 citation statements)

References 30 publications

(56 reference statements)

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“…The majority of them are made for proportional-integrative-derivative-accelerative (PIDA) controllers (PID 2 n ). The controller structure is either 1 degree of freedom (1-DOF) [5][6][7][8][9][10][11][12][13][14][15][16][17][18][19][20] or 2 degrees of freedom (2-DOF) [21][22][23] which can optimise the tracking and control performance.…”

Section: Introductionmentioning

confidence: 99%

High-Order Filtered PID Controller Tuning Based on Magnitude Optimum

Vrančić

Huba

2021

Mathematics

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The paper presents a tuning method for PID controllers with higher-order derivatives and higher-order controller filters (HO-PID), where the controller and filter orders can be arbitrarily chosen by the user. The controller and filter parameters are tuned according to the magnitude optimum criteria and the specified noise gain of the controller. The advantages of the proposed approach are twofold. First, all parameters can be obtained from the process transfer function or from the measured input and output time responses of the process as the steady-state changes. Second, the a priori defined controller noise gain limits the amount of HO-PID output noise. Therefore, the method can be successfully applied in practice. The work shows that the HO-PID controllers can significantly improve the control performance of various process models compared to the standard PID controllers. Of course, the increased efficiency is limited by the selected noise gain. The proposed tuning method is illustrated on several process models and compared with two other tuning methods for higher-order controllers.

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Section: Introductionmentioning

confidence: 99%

High-Order Filtered PID Controller Tuning Based on Magnitude Optimum

Vrančić

Huba

2021

Mathematics

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“…The authors of [37] tune a Fractional-Order Proportional Integral Derivative Acceleration (FOPIDA) through a proposed Consensus-Oriented Random Search (CORS) algorithm that implements a consensus curve that shows the design tradeoff between the reference and disturbance values. RDR is used as one of the multiple factors that contribute to the numerical optimization leading to the FOPIDA controller.…”

Section: Disturbance Rejection In Control Engineeringmentioning

confidence: 99%

Fractional-Order PI Controller Design Based on Reference–to–Disturbance Ratio

et al. 2022

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The presence of disturbances in practical control engineering applications is unavoidable. At the same time, they drive the closed-loop system’s response away from the desired behavior. For this reason, the attenuation of disturbance effects is a primary goal of the control loop. Fractional-order controllers have now been researched intensively in terms of improving the closed-loop results and robustness of the control system, compared to the standard integer-order controllers. In this study, a novel tuning method for fractional-order controllers is developed. The tuning is based on improving the disturbance attenuation of periodic disturbances with an estimated frequency. For this, the reference–to–disturbance ratio is used as a quantitative measure of the control system’s ability to reject disturbances. Numerical examples are included to justify the approach, quantify the advantages and demonstrate the robustness. The simulation results provide for a validation of the proposed tuning method.

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“…A 2DOF control structure with a setpoint filter is also a common method to achieve the trade-off. 34,37,38 Some studies addressed the trade-off for a one-degree-of-freedom PID controller. Alcańtara et al 39 proposed a γ-tuning procedure based on the model matching approach.…”

Section: Introductionmentioning

confidence: 99%

“…Recently, the multiobjective optimization strategy is also used to solve this trade-off. Ozbey et al 38 presented a multiobjective tuning method to use the mean squared control error (MSCE) to measure the tracking performance and use RDR to measure the disturbance rejection. Tufenkci et al 42 presented a multiobjective controller design strategy considering the optimal placement of the minimum angle system pole and a predefined RDR design specification.…”

Section: Introductionmentioning

confidence: 99%

“…Tepljakov et al proposed a multiloop MRAC-FOPID control structure to improve the disturbance rejection and tracking performance. A 2DOF control structure with a setpoint filter is also a common method to achieve the trade-off. ,, Some studies addressed the trade-off for a one-degree-of-freedom PID controller. Alcántara et al proposed a γ-tuning procedure based on the model matching approach.…”

Section: Introductionmentioning

confidence: 99%

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Multiobjective Tuning and Performance Assessment of PID Using Teaching–Learning-Based Optimization

Zhang

Dong

et al. 2021

ACS Omega

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There have been many studies on the optimal tuning and control performance assessment (CPA) of the PID controller. In the optimal tuning, the trade-off between the setpoint tracking and the disturbance rejection performance is a challenge. Minimum output variance (MOV) is very widely used as a benchmark for CPA of PID, but it is difficult to be observed due to the non-convex optimization problem. In this paper, a new multiobjective function, considering both the OV in the CPA problem and integral of absolute error, is proposed to tune PID for this trade-off. The CPA-related non-convex problem and tuning-related multiobjective problem are solved by teaching–learning-based optimization, which guarantees a tighter lower bound for MOV due to the excellent capability of local optima avoidance and has higher computational efficiency due to the low complexity. The numerical examples of CPA problems show that the algorithm can generate better MOV than existing methods with less calculation time. The relationship between the weight of the multiobjective function and the performance, including setpoint tracking, stochastic and step disturbance rejection, is revealed by simulation results of the tuning method applied to two temperature control systems. The proper adjustment of the weight with a multistage strategy can achieve the trade-off to obtain excellent setpoint tracking performance in the initial stage and satisfying disturbance rejection performance in the steady stage.

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2DOF multi-objective optimal tuning of disturbance reject fractional order PIDA controllers according to improved consensus oriented random search method

Cited by 13 publications

References 30 publications

High-Order Filtered PID Controller Tuning Based on Magnitude Optimum

High-Order Filtered PID Controller Tuning Based on Magnitude Optimum

Fractional-Order PI Controller Design Based on Reference–to–Disturbance Ratio

Multiobjective Tuning and Performance Assessment of PID Using Teaching–Learning-Based Optimization

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