Optimal parameter identification of PEMFC stacks using Adaptive Sparrow Search Algorithm

2021 ◽  
Author(s):  
Yanlong Zhu ◽  
Nasser Yousefi
Keyword(s):  
Parameter Identification ◽  
Search Algorithm ◽  
Optimal Parameter

Optimal parameter identification of triple-junction photovoltaic panel based on enhanced moth search algorithm

Energy ◽  
2019 ◽  
Vol 188 ◽  
pp. 116025 ◽  
Author(s):  
Ahmed Fathy ◽  
Mohamed Abd Elaziz ◽  
Enas Taha Sayed ◽  
A.G. Olabi ◽  
Hegazy Rezk
Keyword(s):  
Parameter Identification ◽  
Triple Junction ◽  
Search Algorithm ◽  
Optimal Parameter ◽  
Photovoltaic Panel

Optimal parameter identification strategy applied to lithium‐ion battery model

2021 ◽  
Author(s):  
Seydali Ferahtia ◽  
Ali Djeroui ◽  
Hegazy Rezk ◽  
Aissa Chouder ◽  
Azeddine Houari ◽  
...  
Keyword(s):  
Parameter Identification ◽  
Lithium Ion Battery ◽  
Optimal Parameter ◽  
Lithium Ion ◽  
Battery Model ◽  
Identification Strategy

Optimal parameter identification of SOFC model using modified gray wolf optimization algorithm

Energy ◽  
2022 ◽  
Vol 240 ◽  
pp. 122800
Author(s):  
Jian Wang ◽  
Yi-Peng Xu ◽  
Chen She ◽  
Ping Xu ◽  
Hamid Asadi Bagal
Keyword(s):  
Parameter Identification ◽  
Optimization Algorithm ◽  
Optimal Parameter ◽  
Gray Wolf

Design and Implementation of Tuning PID Controller using Modern Optimization Techniques for Micro-Robotics System

2021 ◽  
Vol 10 (11) ◽  
pp. 51-68
Author(s):  
Ehab S. Ghith ◽  
◽  
Mohamed Sallam ◽  
Islam S. M. Khalil ◽  
Mohamed Youssef Serry ◽  
...  
Keyword(s):  
Steady State ◽  
Optimization Problems ◽  
Model Simulation ◽  
Search Algorithm ◽  
Optimal Parameter ◽  
Fitness Function ◽  
Optimization Techniques ◽  
Control Technique ◽  
Pid Controllers ◽  
Flower Pollination Algorithm

One of the main difficult tasks in the field of micro-robotics is the process of the selection of the optimal parameters for the PID controllers. Some methods existed to solve this task and the common method used was the Ziegler and Nichols. The former method require an accurate mathematical model. This method is beneficial in linear systems, however, if the system becomes more complex or non-linear the method cannot produce accurate values to the parameters of the system. A solution proposed for this problem recently is the application of optimization techniques. There are various optimization techniques can be used to solve various optimization problems. In this paper, several optimization methods are applied to compute the optimal parameter of PID controllers. These methods are flower pollination algorithm (FPA), grey wolf optimization (GWO), sin cosine algorithm (SCA), slime mould algorithm (SMA), and sparrow search algorithm (SSA). The fitness function applied in the former optimization techniques is the integral square Time multiplied square Error (ISTES) as the performance index measure. The fitness function provides minimal rise time, minimal settling time, fast response, and no overshoot, Steady state error equal to zero, a very low transient response and a non-oscillating steady state response with excellent stabilization. The effectiveness of the proposed SSA-based controller was verified by comparisons made with FPA, GWO, SCA, SMA controllers in terms of time and frequency response. Each control technique will be applied to the identified model (simulation results) using MATLAB Simulink and the laboratory setup (experimental results) using LABVIEW software. Finally, the SSA showed the highest performance in time and frequency responses.

scholarly journals Parameter Identification for Photovoltaic Models Using an Improved Learning Search Algorithm

IEEE Access ◽  
2020 ◽  
Vol 8 ◽  
pp. 116292-116309
Author(s):  
Ting Huang ◽  
Chunliang Zhang ◽  
Haibin Ouyang ◽  
Guangshun Luo ◽  
Steven Li ◽  
...  
Keyword(s):  
Parameter Identification ◽  
Search Algorithm ◽  
Improved Learning

Parameter Identification of Nonlinear Muskingum Model with Backtracking Search Algorithm

2016 ◽  
Vol 30 (8) ◽  
pp. 2767-2783 ◽  
Author(s):  
Xiaohui Yuan ◽  
Xiaotao Wu ◽  
Hao Tian ◽  
Yanbin Yuan ◽  
Rana Muhammad Adnan
Keyword(s):  
Parameter Identification ◽  
Search Algorithm ◽  
Backtracking Search ◽  
Backtracking Search Algorithm ◽  
Muskingum Model ◽  
Nonlinear Muskingum Model
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