<i>k</i>
            <sub>P</sub>
            ‐stable regions in the space of PID controller coefficients

Almodaresi, Elham; Bozorg, Mohammad

doi:10.1049/iet-cta.2016.0685

Cited by 15 publications

(8 citation statements)

References 14 publications

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“…The PID controller and the parameters involved with this controller are discussed in many research papers in the literature [43][44][45]. Many methods provide PID controller tuning in [46,47].…”

Section: Controllers Validation and Implementationmentioning

confidence: 99%

Controller design for DFIG‐based WT using gravitational search algorithm for wind power generation

Bharti

Sarita

Vardhan³

et al. 2021

IET Renewable Power Gen

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This paper describes the controller design aspects of DFIG-based wind turbine system (WTS) using gravitational search algorithm (GSA). The appropriate control schemes are required for efficient and reliable functioning of the DFIG-based wind energy conversion system (WECS). The control algorithms are implemented in converters which are placed in the rotor end and grid side of the WECS. The controller design schemes are optimized for accurate, reliable and stable operations of WECS using GSA. The most commonly used other design techniques are bacterial foraging optimization (BFO), and particle swarm optimization (PSO). Moreover, the transfer function modeling of DFIG is also described in this paper. The results show that the proposed GSA technique with sixths order transfer function model of DFIG improves the transient performance including time of rising the response to 90%, settling time, and amplitude of peak overshoot. The proposed GSA technique is compared with the techniques already implemented in the previous research works including PSO and BFO. The DFIG-based WTS's output waveforms of voltage at dc-link, reactive power, and active power are improved using GSA based design technique. Finally, it is concluded that the GSA technique gives better results as compared with the PSO and BFO techniques.This is an open access article under the terms of the Creative Commons Attribution License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited.

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Section: Controllers Validation and Implementationmentioning

confidence: 99%

Controller design for DFIG‐based WT using gravitational search algorithm for wind power generation

Bharti

Sarita

Vardhan³

et al. 2021

IET Renewable Power Gen

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“…23 The popularity of this controller is due to several factors like its simple structure, robustness to system's inertia matrix, understandable principles, simple implementation, specific physical meaning and adjustable frequency response measure such as the gain margin, phase margin and bandwidth frequencies. Moreover, multiple simple and complicated tuning algorithms have been proposed to design the optimal PID controller, 24 or to improve the closed loop performance of the system such as the Ziegler-Nichols 25 and Åström-Hägglund phase margin 26 methods. However, implementing such tuning algorithms may not lead to an acceptable closed-loop response, particularly for dynamical systems with time varying coefficients.…”

Section: Pid Controllermentioning

confidence: 99%

Linear controllers for free-flying and controlledfloating space robots: a new perspective

Mohamed¹,

Saaj²,

Seddaoui³

2020

AAOAJ

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Autonomous space robots are crucial for performing future in-orbit operations including servicing of a spacecraft, assembly of large structures, maintenance of other space assets and debris removal. Such orbital missions require servicer spacecraft equipped with one or more dexterous manipulators. However, unlike its terrestrial counterpart, the base of the robotic manipulator is not fixed in inertial space, instead, it is mounted on the basespacecraft, which itself possess both translational and rotational motions. Additionally, the system will be subjected to extreme environmental perturbations, parametric uncertainties as well as system constraints due to the dynamic coupling between the manipulator and the base-spacecraft. This paper presents the dynamic model of the space robot and a three-stage control algorithm to control such a highly dynamic non-linear system. In this approach, Feed-Forward compensation and Feed-Forward Linearization techniques are used to decouple and linearize the highly non-linear system respectively, therefore, allowing the use of the linear Proportional-Integral-Derivative (PID) controller and Linear Quadratic Regulator (LQR)as final stages. Moreover, a simulation-based trade-off analysis was conducted to assess the efficacy of both proposed controllers. This assessment considered the requirements on precise trajectory tracking, minimizing power consumption and robustness during the close-range operation with the target spacecraft.Research highlights: orbital space robotic missions, control of space robots, freeflying and controlled-floating modes of operation, application of linear controllers

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“…The computation of all stabilizing PI(D) controllers by using the Kronecker summation method was presented in [10]. A Nyquist plotbased technique for calculation of KP-stable regions was developed in [11] (for time delay and PI controller parameters) and [12] (for PID controller parameters). A Lyapunov equation-based stability mapping approach can be found in [13], [14].…”

Section: Introductionmentioning

confidence: 99%

Robust PI Control of Interval Plants With Gain and Phase Margin Specifications: Application to a Continuous Stirred Tank Reactor

2020

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The paper is focused on robust Proportional-Integral (PI) control of interval plants with gain and phase margin specifications and on the application of this approach to a Continuous Stirred Tank Reactor (CSTR). More specifically, the work aims at the determination of PI controller parameter regions, for which not only robust stability but also some level of robust performance of the closed-loop control system is guaranteed, and this robust performance is represented by the required gain and phase margin that has to be ensured for all potential members of the interval family of controlled plants, even for the worst case. The applied technique is based on the combination of the previously published generalization of stability boundary locus method (for specified gain and phase margin under the assumption of fixedparameter plants) with the sixteen plant theorem. This extension enables the direct application of the method to design the robustly performing PI controllers for interval plants. The effectiveness of the improved method is demonstrated on a CSTR, modeled as the interval plant, for which the robust stability and robust performance regions are obtained.

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k _P ‐stable regions in the space of PID controller coefficients

Cited by 15 publications

References 14 publications

Controller design for DFIG‐based WT using gravitational search algorithm for wind power generation

Controller design for DFIG‐based WT using gravitational search algorithm for wind power generation

Linear controllers for free-flying and controlledfloating space robots: a new perspective

Robust PI Control of Interval Plants With Gain and Phase Margin Specifications: Application to a Continuous Stirred Tank Reactor

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k P ‐stable regions in the space of PID controller coefficients

Cited by 15 publications

References 14 publications

Controller design for DFIG‐based WT using gravitational search algorithm for wind power generation

Controller design for DFIG‐based WT using gravitational search algorithm for wind power generation

Linear controllers for free-flying and controlledfloating space robots: a new perspective

Robust PI Control of Interval Plants With Gain and Phase Margin Specifications: Application to a Continuous Stirred Tank Reactor

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Product

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k _P ‐stable regions in the space of PID controller coefficients