Vibration control of semi-active suspension system using PID controller with advanced firefly algorithm and particle swarm optimization

Talib, Mat Hussin Ab; Darus, Intan Zaurah Mat; Samin, Pakharuddin Mohd; Yatim, Hanim Mohd; Ardani, Mohd Ibthisham; Shaharuddin, Nik Mohd Ridzuan; Hadi, Muhamad Sukri

doi:10.1007/s12652-020-02158-w

Cited by 60 publications

(23 citation statements)

References 31 publications

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“…According to his paper, two PID controllers take care of two different objects, including displacement and acceleration of the sprung mass. Besides, the PID control method can also be combined with many other control methods to improve the stability efficiency [14][15][16]. Assuming that the vehicle is a MIMO system, the LQR control method is proposed to control the output parameters of the object [17].…”

Section: Literature Reviewmentioning

confidence: 99%

LQR Control with the New Triple In-Loops Algorithm for Optimization of the Tuning Parameters

Nguyen¹,

Nguyen²,

Dang³

et al. 2022

MMEP

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The suspension system plays a role in ensuring the stability of the vehicle when traveling on the road. On many modern vehicles, the active suspension system has been proposed to replace the conventional passive suspension system. The performance of the controller for the active suspension system depends on its control method. In this paper, a half dynamics model of the vehicle is established. Besides, the LQR control method is also used. The parameters of the control matrix are calculated through the triple in-loop optimization algorithm, which has been shown in the research. This is a completely novel algorithm. This algorithm helps to choose the most optimal parameters. Thus, it ensures the efficiency and stability of the controller. The calculation and comparison process are done automatically. When the loop ends, the optimal parameters are explicitly indicated. The simulation process is done in the MATLAB-Simulink environment. The results of the research showed that when the LQR controller, which was optimized through the triple in-loop algorithm used, the vehicle's oscillation was significantly reduced. In the three survey situations, the values of the roll angle and the angular acceleration of the sprung mass are guaranteed to be stable. Besides, when using this controller, the phenomenon of “chattering” after the excitation ends does not appear. This topic can be further developed in the future.

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Section: Literature Reviewmentioning

confidence: 99%

LQR Control with the New Triple In-Loops Algorithm for Optimization of the Tuning Parameters

Nguyen¹,

Nguyen²,

Dang³

et al. 2022

MMEP

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show abstract

“…Numerous complex control algorithms used in robotics, such as adaptive control theory and/or robust control theory, have been projected and executed for natural systems. However, these complex and delicate control algorithms present a less complicated PID system than the popularly utilized controller in robotics and process industries [34]. Such a category of algorithms has already been shown to provide adequate functioning in controlling various linear and nonlinear processes.…”

Section: Related Workmentioning

confidence: 99%

Metaheuristics Algorithm for Tuning of PID Controller of Mobile Robot System

Goud¹,

Sharma²,

Nisar³

et al. 2022

Computers, Materials &Amp; Continua

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Robots in the medical industry are becoming more common in daily life because of various advantages such as quick response, less human interference, high dependability, improved hygiene, and reduced aging effects. That is why, in recent years, robotic aid has emerged as a blossoming solution to many challenges in the medical industry. In this manuscript, meta-heuristics (MH) algorithms, specifically the Firefly Algorithm (FF) and Genetic Algorithm (GA), are applied to tune PID controller constraints such as Proportional gain Kp Integral gain Ki and Derivative gain Kd. The controller is used to control Mobile Robot System (MRS) at the required set point. The FF arrangements are made based on various pre-analysis. A detailed simulation study indicates that the proposed PID controller tuned with Firefly Algorithm (FF-PID) for MRS is beneficial and suitable to achieve desired closed-loop system response. The FF is touted as providing an easy, reliable, and efficient tuning technique for PID controllers. The most suitable ideal performance is accomplished with FF-PID, according to the display in the time response. Further, the observed response is compared to those received by applying GA and conventional off-line tuning techniques. The comparison of all tuning methods exhibits supremacy of FF-PID tuning of the given nonlinear Mobile Robot System than GA-PID tuning and conventional controller.

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“…They had shown an improvement of 1.2–6 dB with respect to other compression methods. Talib et al [ 46 ] had investigated an intelligent optimizer named as advanced firefly algorithm to calculate the proportional-integral-derivative (PID) controller in case of semi-active suspension things. Notable improvisation was observed in their technique because it had the reducibility of amplitude of the sprung acceleration to 56.5% and body acceleration to 67.1%.…”

Section: Related Workmentioning

confidence: 99%

Episode of Dual Neural Genetic Firefly (DNGF) Transmission Key Generation in New Normal Mode of COVID-19 Second Wave Telepsychiatry

Dey¹,

Karforma

Chowdhury

2022

J. Inst. Eng. India Ser. B

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The volume of E-commerce transactions had accelerated on huge scale due to COVID-19. Telemedicine comes under the segment of E-commerce, where the patients can get their treatments from isolates. Patients’ information security is a basic challenge in this COVID-19 telemedicine segment. The majority of the non-obtrusive and non-emergency patients are encouraged and treated distantly from their secludes without the inclusion of COVID-19 transmission. Anxiety, depressive disorders, stress, dementia, mood disorder, OCD, aggression, etc. are the critical mental challenges that have abruptly occurred during this COVID period. The present work focused on “New Normal Mode” of COVID-19 telepsychiatry so that the patients’ mental illness can be treated remotely in a secure way. An episode of dual neural-genetic firefly (DNGF) has been proposed on COVID-19 "New Normal Mode" 2nd wave telepsychiatry. The pool of transmission keys was generated with the help of firefly algorithm, neural perceptron, and genetic operations. Besides these, the proposed DNGF keys are effective to be used for different online psychiatric transactions. The objectivity of this paper is to generate a robust pool of transmission keys in order to nullify different types of intruding. It has effectively cleared Avalanche test and Strict Avalanche test. The outcome of parameterized functional security test has been recorded with adequacy. These were: 0.327933, 0.350467, 0.332533, 0.317867, and 0.350267 on the generated pool of DNGF. The correlation coefficient between the key generation time and parameterized functional security has been found to be Distinctive mathematical arranged examinations were directed on the proposed key pool. It has shown better reasonability on the part of the COVID-19 2nd wave telepsychiatry, which is a component of E-commerce.

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Vibration control of semi-active suspension system using PID controller with advanced firefly algorithm and particle swarm optimization

Cited by 60 publications

References 31 publications

LQR Control with the New Triple In-Loops Algorithm for Optimization of the Tuning Parameters

LQR Control with the New Triple In-Loops Algorithm for Optimization of the Tuning Parameters

Metaheuristics Algorithm for Tuning of PID Controller of Mobile Robot System

Episode of Dual Neural Genetic Firefly (DNGF) Transmission Key Generation in New Normal Mode of COVID-19 Second Wave Telepsychiatry

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