Particle swarm-based and neuro-based FOPID controllers for a Twin Rotor System with improved tracking performance and energy reduction

Norsahperi, Nor Mohd Haziq; Danapalasingam, Kumeresan A.

doi:10.1016/j.isatra.2020.03.001

Cited by 39 publications

(18 citation statements)

References 44 publications

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“…Since then, fractional‐order controllers are widely used by many engineers and researchers to obtain better and robust performance of different systems 83‐85 . Recently, Norsapheri and Danapalasingam 86 used fractional order PID controller in Twin Rotor Aerodynamic System for controlling the pitch. Modeling of the Micro Turbine Generation system is carried out with FOPID controller in research paper, 87 and overall performance of the Micro Turbine Generation system has improved considerably.…”

Section: Motivation and Brief Overview Of Proposed Controllermentioning

confidence: 99%

Equilibrium optimizer tuned novel FOPID‐DN controller for automatic voltage regulator system

Paliwal

Srivastava

Pandit

2021

Int Trans Electr Energ Syst

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Summary This paper presents a novel fractional‐order PID plus derivative with filter coefficient (FOPID‐DN) controller for automatic voltage regulator (AVR) system using the MATLAB/Simulink environment. An AVR system is employed in the power system to maintain the terminal voltage at the desired level. Parameters of the proposed FOPID‐DN controller are optimally tuned by the recently developed Equilibrium Optimizer (EO) algorithm. Performance of the designed FOPID‐DN controller for an AVR system is compared with various controllers which are optimally tuned by different optimization algorithms. Comparative transient response analysis of the proposed technique has been carried out by considering vital transient response indicators like maximum overshoot, rise time, and settling time. Performance analysis of the proposed technique for an AVR system has been done by considering several input conditions. Robustness analysis of the EO algorithm tuned FOPID‐DN controller has been performed by varying the time constants of different components in an AVR system. The capability of the FOPID‐DN controller to handle nonlinearities of an AVR system has been investigated. The stability of the FOPID‐DN controlled AVR system has been analyzed. In addition, the disturbance rejection capability of the FOPID‐DN controlled AVR system has also been investigated. From the various simulation results obtained using the MATLAB/Simulink environment, it has been observed that the proposed FOPID‐DN‐based AVR system provided better performance as compared to different existing controllers.

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Section: Motivation and Brief Overview Of Proposed Controllermentioning

confidence: 99%

Equilibrium optimizer tuned novel FOPID‐DN controller for automatic voltage regulator system

Paliwal

Srivastava

Pandit

2021

Int Trans Electr Energ Syst

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“…[14] proposed a state transition algorithm to address the optimization challenges in the design of the FOPID controller for the pH neutralization process. Recent literature shows a wide application of the fractional PID controller for myriad engineering fields [15][16][17][18][19][20][21][22][23]. All these prove undoubtedly that the FOPID controller is superior to its integer counterparts in terms of performance.…”

Section: Introductionmentioning

confidence: 99%

“…The design and tuning procedures of the FOPID controller are complex compared to the conventional PID controller as two additional design parameters are involved. However, it is evident from recent pieces of literature that the use of an optimization algorithm is a perfect solution for the design problem [17,18,27,[31][32][33][34][35][36][37][38]. Even though there has been a lot of bioinspired algorithms, Particle Swarm Optimization (PSO) algorithms are widely used because of their simplicity, flexibility for modification, and a smaller number of parameters for adjustment.…”

Section: Introductionmentioning

confidence: 99%

pH control in sodium chlorate cell for energy efficiency using PSO-FOPID controller

Sreekumar

Kallingal

Lakshmanan

2022

CI&CEQ

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Industrial sodium chlorate production is a highly energy-intensive electro-chemical process. If the pH of the chlorate cell is not controlled, the current efficiency drops from 99% to as low as 66.66%. Hence control of chlorate cell pH is very significant for energy-efficient sodium chlorate production. This study puts forward a fractional order PID controller for controlling the pH of the sodium chlorate cell. The tuning of FOPID controller variables is affected by employing particle swarm optimization. The highlight of the controller is that it is flexible, easy to deploy and the time of computation is significantly low as few parameters are needed to be adjusted in PSO. The performance analysis of the suggested FOPID-PSO controller was studied and compared with the traditional PI controller and PID controller using time-domain provisions like settling time, rise time and peak overshoot and error indicators like integral square error (ISE), integral absolute error (IAE), and integral time absolute error (ITAE). FOPID controller employing PSO proved to perform well compared to conventional controllers with 0.5 sec settling time and 0.1 sec rise time. This demonstrates that the FOPID-PSO controller has better setpoint tracking, which is very essential for the process under consideration.

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“…These features are making TRAS very challenging for designing an appropriate control algorithm. Over the years, many different strategies for TRAS control have been developed, ranging from classical [11] to advanced [12], and intelligent [13], [14].…”

Section: Introductionmentioning

confidence: 99%

Model Predictive Control of Nonlinear MIMO Systems Based on Adaptive Orthogonal Polynomial Networks

Milojković

Djordjevic

Perić

et al. 2021

ELEKTRON ELEKTROTECH

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This paper considers a new design of model predictive control based on specific models in the form of adaptive orthogonal polynomial networks, built around a specially tailored basis of generalized orthogonal functions. Polynomial model has a single layer structure and a smaller number of model parameters than classical neural networks, usually used for model predictive control design, leading to lower complexity and shorter calculation time. Desired property of adaptability of the model is achieved by using additional variable factors inside the orthogonal basis. The designed controller was applied in control of twin-rotor aero-dynamic system as a representative of nonlinear multiple input-multiple output systems and compared to the other state-of-the-art control algorithms.

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Particle swarm-based and neuro-based FOPID controllers for a Twin Rotor System with improved tracking performance and energy reduction

Cited by 39 publications

References 44 publications

Equilibrium optimizer tuned novel FOPID‐DN controller for automatic voltage regulator system

Equilibrium optimizer tuned novel FOPID‐DN controller for automatic voltage regulator system

pH control in sodium chlorate cell for energy efficiency using PSO-FOPID controller

Model Predictive Control of Nonlinear MIMO Systems Based on Adaptive Orthogonal Polynomial Networks

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