On-Line PID Parameters Optimization Control for Wind Power Generation System Based on Genetic Algorithm

Li, Jiasheng; Li, Wenguo

doi:10.1109/access.2020.3009240

Cited by 29 publications

(10 citation statements)

References 11 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…As a detection means, the examination should be serious and have special high requirements for security. Therefore, users are divided into two categories: administrators and candidates [17]. They have different levels.…”

Section: Experiments and Analysismentioning

confidence: 99%

Design and Implementation of Online Japanese Examination System Based on Genetic Algorithm

Dengqing

Zhangwei

2022

Wireless Communications and Mobile Computing

View full text Add to dashboard Cite

In order to solve the problem of online inspection of students’ theoretical knowledge of Japanese, this paper further optimizes and adjusts the design of the online Japanese examination system and presents an online Japanese examination system based on genetic algorithm. Taking the Japanese test as the research object, on the basis of comprehensively analyzing the problems of slow test paper composition, low success rate, and low quality of traditional online test systems, an intelligent test composition model based on genetic algorithm is proposed, and the implementation process of genetic algorithm and the key steps are described in detail. The results show that the online Japanese examination system based on genetic algorithm can meet the needs of test paper generation in more complex situations. After a long time of operation and continuous improvement, the online Japanese examination system has obtained the adaptability of the best solution. The value of the fitness is 99.666667; when the fitness is at this value, the error of the question type score of the test paper is 0, the average difficulty error on the test paper is 0, and the error of the section test point distribution is 0.666667. This fully illustrates the stability and effectiveness of the Japanese online examination system, which can meet the needs of daily Japanese majors and improve the efficiency of Japanese teaching.

show abstract

Section: Experiments and Analysismentioning

confidence: 99%

Design and Implementation of Online Japanese Examination System Based on Genetic Algorithm

Dengqing

Zhangwei

2022

Wireless Communications and Mobile Computing

View full text Add to dashboard Cite

show abstract

“…To control the converters in use, we adopted fundamental, simple, and widely applied techniques such as PID [15], 2DOFPID [16], and FOPID [17]. Furthermore, more advanced techniques, including fuzzy logic controllers [18], artificial neural networks [19], and genetic algorithms [20], have also been employed.…”

Section: Literature Reviewmentioning

confidence: 99%

Exploring solar energy systems: A comparative study of optimization algorithms, MPPTs, and controllers

Güven

2024

IET Control Theory & Appl

View full text Add to dashboard Cite

This study elucidates the use of optimization algorithms to identify the controller parameters employed in adjusting the current and voltage values of loads powered by solar energy systems and battery groups. Parameters for these controllers were independently derived using a combination of ant colony optimization with Levy flight, hybrid firefly‐particle swarm optimization, hybrid gravitation search algorithm‐particle swarm optimization, alongside the implementation of Jaya and whale optimization algorithms. The results from each method were juxtaposed for thorough analysis. In addition, three distinct Maximum Power Point Tracker (MPPT) algorithms were employed in the system: perturbation and observation, open circuit voltage, and incremental conductance (IC). To assess the system’s adaptability to real‐world conditions, it was tested against varying temperatures and sunlight levels. Moreover, potential changes in the loads were considered by varying the load. The efficacy of the controllers was examined by altering both the environment and load. The effectiveness of the controllers was examined by referring to the integral of time‐weighted absolute error value. The system was simulated using MATLAB/Simulink software. This study demonstrates that the fractional‐order PID controller achieves the most effective results, the Jaya algorithm provides the best controller parameters, and the IC technique exhibits the highest performance in MPPT.

show abstract

“…© The GA parameters used for this study are presented in Table 3. (Li & Li, 2020). These indices will be adopted as the objective functions to minimised by the optimisation algorithms.…”

Section: Genetic Algorithmmentioning

confidence: 99%

Optimisation of Internal Model Control Performance Indices for Autonomous Vehicle Suspension

Bala¹,

Karataev²,

Thomas³

et al. 2022

FUOYEJET

View full text Add to dashboard Cite

Autonomous vehicles (AVs) have grown in popularity and acceptability due to their unique capacity to reduce pollution, road accidents, human error, and traffic congestion. Vehicle suspension is an important component of a car chassis since it affects the performance of vehicle dynamics. As a result, enhancing suspension performance and stability is critical in order to achieve a more pleasant and safer car. Although there are several suspension control methods, they all suffer from fixed gain characteristics that are prone to nonlinearities, disturbances, and the inability to be tuned online. This research provides a comparison of Internal Model Control (IMC) performance metrics for vehicle suspension control. The IMC approach was tuned using the Genetic Algorithm and the Particle Swarm Optimisation algorithms. The performance of each of these schemes was analysed and compared in order to determine the approach with the best performance in terms of AV suspension control. The performance of the system response was compared to that of the traditional IMC. According to the comparison analysis, the optimized IMC systems had lower IAE, ITAE, ISE, rising time, and settling time values than the traditional IMC. Furthermore, there were no overshoots in any of the controllers.

show abstract

On-Line PID Parameters Optimization Control for Wind Power Generation System Based on Genetic Algorithm

Cited by 29 publications

References 11 publications

Design and Implementation of Online Japanese Examination System Based on Genetic Algorithm

Design and Implementation of Online Japanese Examination System Based on Genetic Algorithm

Exploring solar energy systems: A comparative study of optimization algorithms, MPPTs, and controllers

Optimisation of Internal Model Control Performance Indices for Autonomous Vehicle Suspension

Contact Info

Product

Resources

About