Disturbance rejection FOPID controller design in v-domain

Tufenkci, Sevilay; Senol, Bilal; Alagöz, Barış Baykant; Matušů, Radek

doi:10.1016/j.jare.2020.03.002

Cited by 21 publications

(9 citation statements)

References 46 publications

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“…Adjusting places of minimum argument roots within the stability region w strated in [17,45]. Optimal FOPI and FOPID controller tuning in the v-domain trated in [46][47][48]. The current study extended this approach to solve the optim stabilization problem of FOPID control systems.…”

Section: Methodology For Robust Stabilization Of Fopid Control Systemmentioning

confidence: 99%

“…Stabilization of fractional order controllers based on minimum angle characteristic root placement within the first Riemann sheet of the v-plane has been shown [16,17,45]. Optimal FOPID controller design has been demonstrated in the v-plane [46,47]. Effects of pole placements on a fractional order proportional integral (FOPI) controller performance were discussed in [48].…”

Section: Introductionmentioning

confidence: 99%

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Optimal V-Plane Robust Stabilization Method for Interval Uncertain Fractional Order PID Control Systems

et al. 2021

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Robust stability is a major concern for real-world control applications. Realization of optimal robust stability requires a stabilization scheme, which ensures that the control system is stable and presents robust performance for a predefined range of system perturbations. This study presented an optimal robust stabilization approach for closed-loop fractional order proportional integral derivative (FOPID) control systems with interval parametric uncertainty and uncertain time delay. This stabilization approach, which is carried out in a v-plane, relies on the placement of the minimum angle system pole to a predefined target angle within the stability region of the first Riemann sheet. For this purpose, tuning of FOPID controller coefficients was performed to minimize a root angle error that is defined as the squared difference of minimum angle root of interval characteristic polynomials and the desired target angle within the stability region of the v-plane. To solve this optimization problem, a particle swarm optimization (PSO) algorithm was implemented. Findings of the study reveal that tuning of the target angle can also be used to improve the robust control performance of interval uncertain FOPID control systems. Illustrative examples demonstrated the effectiveness of the proposed v-domain, optimal, robust stabilization of FOPID control systems.

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Section: Methodology For Robust Stabilization Of Fopid Control Systemmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Optimal V-Plane Robust Stabilization Method for Interval Uncertain Fractional Order PID Control Systems

et al. 2021

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“…Fractional-order offers a completely unique modelling approach for systems with astonishing dynamical properties by introducing the notion of a derivative of non-integer (fractional) order. An evaluation of tuning methods for FOPID controllers are often categorized into analytic, rule-based, and numerical depends on the approach to the tuning problem (Tufenkci et al 2020). If a process reveals such dynamics, the model-based control design procedure might be administered using the corresponding tools.…”

Section: Fractional Order Proportional Integral Derivative Controller (Fopid Controller)mentioning

confidence: 99%

Design, implementation, control and optimization of single stage pilot scale reverse osmosis process

Guna¹,

Prabhakaran²,

Thirumarimurugan³

2021

Water Science and Technology

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In this paper, a single-stage pilot-scale RO (Reverse Osmosis) process is considered. The process is mainly used in various chemical industries such as dye, pharmaceutical, Beverage, and so on. Initially, mathematical modeling of the process is to be done followed by linearization of the system. Here a dual loop construction with a master and a slave is used. The slave uses the conventional PID (Proportional Integral Derivative) with a reference model of the RO process and the master uses the FOPID (Fractional Order Proportional Integral Derivative) with a real time RO process. The slave's output is compared with output of the real time RO process to obtain the error which is in turn used to tune the master. The slave controller is tuned using Ziegler Nicholas method and the error criterion such as IAE (Integral Absolute Error), ISE (Integral Squared Error), ITSE (Integral Time Squared Error), ITAE (Integral Time Absolute Error) are calculated and the minimum among them was chosen as the objective function for the master loop tuning. Hence the tuning of the controller becomes a whole. Therefore two optimization techniques such as PSO (Particle Swarm Optimization) and Bacterial Foraging Optimization Algorithm (BFO) are used for the tuning of the master loop. From the calculations the ITSE was having the minimum value among the performance indices hence it was used as the objective function for the BFO and PSO. The best-tuned values will be obtained with the use of these techniques and the best among all can be considered for various industrial applications. Finally, the performance of the process is compared with both techniques and BFO outperforms the PSO from the simulations.

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“…According to Figure 2 and equations ( 5), ( 6), ( 9), (10), and ( 11), the closed-loop structure diagram is shown in Figure 7.where…”

Section: E Analysis Of Stabilitymentioning

confidence: 99%

“…When the model error increases, the control quality decreases, and even the system is unstable. Subsequently, many intelligent controls and composite controls that are composed of several kinds of control appeared, such as adaptive control [3,4], model-free control [5], neural networks control [6], predictive control [7], Smith + PID [8], PI + multimodel dynamic matrix control [9], and Fractional Order Proportional-Integral-Derivative [10].…”

Section: Introductionmentioning

confidence: 99%

A Novel Smith Predictive Linear Active Disturbance Rejection Control Strategy for the First-Order Time-Delay Inertial System

Chen

Liu

et al. 2021

Mathematical Problems in Engineering

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The control strategy research of the time-delay system is a focused issue in the control field. In order to furthermore improve the performance of the first-order time-delay inertial system, firstly, a new Smith predictor structure is proposed, which solves the constraint that the conventional Smith predictor needs to match the actual object model. Secondly, the performance and parameter function of the new Smith predictor are discussed in theory to provide the basis for parameter tuning. Finally, a new Smith predictor combined with linear active disturbance rejection control (LADRC) is proposed to solve the problem that the two input signals of the linear extended state observer (LESO) are not synchronized on the time scale, and the stability of the new Smith + LADRC time-delay control system is proved theoretically for known and unknown controlled complex objects. Simulation analysis is conducted to verify the robustness of the proposed strategy under the condition of the different parameters. The results indicate that the proposed strategy has better performance than the conventional method in response speed, overshoot, adjustment time, and stability.

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Disturbance rejection FOPID controller design in v-domain

Abstract: Graphical abstract

Cited by 21 publications

References 46 publications

Optimal V-Plane Robust Stabilization Method for Interval Uncertain Fractional Order PID Control Systems

Optimal V-Plane Robust Stabilization Method for Interval Uncertain Fractional Order PID Control Systems

Design, implementation, control and optimization of single stage pilot scale reverse osmosis process

A Novel Smith Predictive Linear Active Disturbance Rejection Control Strategy for the First-Order Time-Delay Inertial System

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