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Journal articles on the topic 'ISE Parameter Optimization'

Author: Grafiati

Published: 3 June 2025

Last updated: 20 July 2025

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1

Zahir, A. A. M., Syed Sahal Nazli Alhady, A. A. A. Wahab, and M. F. Ahmad. "Objective functions modification of GA optimized PID controller for brushed DC motor." International Journal of Electrical and Computer Engineering (IJECE) 10, no. 3 (2020): 2426. http://dx.doi.org/10.11591/ijece.v10i3.pp2426-2433.

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PID Optimization by Genetic Algorithm or any intelligent optimization method is widely being used recently. The main issue is to select a suitable objective function based on error criteria. Original error criteria that is widely being used such as ITAE, ISE, ITSE and IAE is insufficient in enhancing some of the performance parameter. Parameter such as settling time, rise time, percentage of overshoot, and steady state error is included in the objective function. Weightage is added into these parameters based on users’ performance requirement. Based on the results, modified error criteria show

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A., A. M. Zahir, S. N. Alhady S., A. F. W. Othman W., A. A. Wahab A., and F. Ahmad M. "Objective functions modification of GA optimized PID controller for brushed DC motor." International Journal of Electrical and Computer Engineering (IJECE) 10, no. 3 (2020): 2426–33. https://doi.org/10.11591/ijece.v10i3.pp2426-2433.

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PID Optimization by Genetic Algorithm or any intelligent optimization method is widely being used recently. The main issue is to select a suitable objective function based on error criteria. Original error criteria that is widely being used such as ITAE, ISE, ITSE and IAE is insufficient in enhancing some of the performance parameter. Parameter such as settling time, rise time, percentage of overshoot, and steady state error is included in the objective function. Weightage is added into these parameters based on users’ performance requirement. Based on the results, modified error criteri

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3

Nourelhouda, Fartas, and Khelassi Abdelmadjid. "Fractional PID controller based on biggest log modulus tuning method with MOPSO optimization for distillation column." Indonesian Journal of Electrical Engineering and Computer Science 28, no. 3 (2022): 1396. http://dx.doi.org/10.11591/ijeecs.v28.i3.pp1396-1404.

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The main contribution of this work is to design a fractional order proportional integral derivative (FO-PID) controller by combining the biggest log modulus tuning (BLT) method and multi-objective particle swarm optimization (PSO) algorithm for the control of the challenging multivariable systems. The parameters of the integer proportional integral (PI) controller are designed preliminary using BLT method. The derivation parameter, the fractional integrator and the fractional derivation parameters is formulated as an optimization problem with many objective functions as minimizing the integral

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Nourelhouda, Fartas, and Khelassi Abdelmadjid. "Fractional PID controller based on biggest log modulus tuning method with MOPSO optimization for distillation column." Indonesian Journal of Electrical Engineering and Computer Science 28, no. 3 (2022): 1396–404. https://doi.org/10.11591/ijeecs.v28.i3.pp1396-1404.

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The main contribution of this work is to design a fractional order proportional integral derivative (FO-PID) controller by combining the biggest log modulus tuning (BLT) method and multi-objective particle swarm optimization (PSO) algorithm for the control of the challenging multivariable systems. The parameters of the integer proportional integral (PI) controller are designed preliminary using BLT method. The derivation parameter, the fractional integrator and the fractional derivation parameters is formulated as an optimization problem with many objective functions as minimizing the integral

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Balasingh Moses, M., and S. Rajarajacholan. "A Novel Modified Adaptive Controller Design for Non Negative DC–DC Converter Using Meta-Heuristic Algorithms for Bio Medical Hybrid Application." Journal of Medical Imaging and Health Informatics 12, no. 1 (2022): 77–82. http://dx.doi.org/10.1166/jmihi.2022.3929.

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Purpose: Meta-heuristic (MH) methods are used to develop an adaptive sliding mode controller for a POEL converter. MH algorithms have been used to address a variety of engineering optimization problems. Which will use for Bio medical hybrid systems applications. Design/Methodology: Particle Swarm Optimization (PSO) approach is well known and it could expedite the convergence characteristic in numerous applications. By means of amending PSO parameters like, inertia mass, social and perceptive agents at every generation, Modern Parameter Improved Particle Swarm Optimization (MPIPSO) algorithm wh

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Gupta, Esha, and Akash Saxena. "Performance Evaluation of Antlion Optimizer Based Regulator in Automatic Generation Control of Interconnected Power System." Journal of Engineering 2016 (2016): 1–14. http://dx.doi.org/10.1155/2016/4570617.

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This paper presents an application of the recently introduced Antlion Optimizer (ALO) to find the parameters of primary governor loop of thermal generators for successful Automatic Generation Control (AGC) of two-area interconnected power system. Two standard objective functions, Integral Square Error (ISE) and Integral Time Absolute Error (ITAE), have been employed to carry out this parameter estimation process. The problem is transformed in optimization problem to obtain integral gains, speed regulation, and frequency sensitivity coefficient for both areas. The comparison of the regulator pe

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Saribas, Hasan, and Sinem Kahvecioglu. "PSO and GA tuned conventional and fractional order PID controllers for quadrotor control." Aircraft Engineering and Aerospace Technology 93, no. 7 (2021): 1243–53. http://dx.doi.org/10.1108/aeat-08-2020-0185.

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Purpose This study aims to compare the performance of the conventional and fractional order proportional-integral-derivative (PID and FOPID) controllers tuned with a particle swarm optimization (PSO) and genetic algorithm (GA) for quadrotor control. Design/methodology/approach In this study, the gains of the controllers were tuned using PSO and GA, which are included in the heuristic optimization methods. The tuning processes of the controller’s gains were formulated as optimization problems. While generating the objective functions (cost functions), four different decision criteria were consi

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Peraza, Cinthia, Fevrier Valdez, Juan R. Castro, and Oscar Castillo. "Fuzzy Dynamic Parameter Adaptation in the Harmony Search Algorithm for the Optimization of the Ball and Beam Controller." Advances in Operations Research 2018 (August 14, 2018): 1–16. http://dx.doi.org/10.1155/2018/3092872.

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This paper presents a method for dynamic parameter adaptation in the harmony search algorithm (HS) based on fuzzy logic. The adaptation is performed using Type 1 (FHS), interval Type 2 (IT2FHS), and generalized Type 2 (GT2FHS) fuzzy systems as the number of improvisations or iterations advances, achieving a better intensification and diversification. The main contribution of this work is the dynamic parameter adaptation using different types of fuzzy systems in the harmony search algorithm applied to optimization of the membership functions for a benchmark control problem; in this case it is f

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Kamala, N., T. Thyagarajan, and S. Renganathan. "Fuzzy Gain Scheduled Multivariable Control of Nonlinear System Using PSO Based PID." Advanced Materials Research 403-408 (November 2011): 3892–99. http://dx.doi.org/10.4028/www.scientific.net/amr.403-408.3892.

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In this paper, Particle swarm optimization (PSO) is utilized to optimize the coefficients of decoupling controllers for a nonlinear process. The optimization criteria considered is the Integral Square Error (ISE) to minimize the tracking error. The controller is tuned at chosen operating points, which are selected to cover the nonlinear range of the process. The optimal PID controller parameters are gain scheduled using Sugeno Fuzzy Gain scheduler. Fuzzy gain scheduling is a special form of model-based fuzzy control that uses linguistic rule fuzzy reasoning to determine the controller paramete

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Rajinikanth, V., and K. Latha. "Tuning and Retuning of PID Controller for Unstable Systems Using Evolutionary Algorithm." ISRN Chemical Engineering 2012 (May 10, 2012): 1–11. http://dx.doi.org/10.5402/2012/693545.

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Proportional + integral + derivative (PID) controllers are widely used in industrial applications to provide optimal and robust performance for stable, unstable, and nonlinear processes. In this paper, particle swarm optimization (PSO) algorithm is proposed to tune and retune the PID controller parameter for a class of time-delayed unstable systems. The proposal is to search the optimal controller parameters like , , and by minimising the cost function. The integral of squared error (ISE) criterion is considered as the cost function, which guides the PSO algorithm to get the optimised controll

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Choubey, Ashish, Sachin Kumar Jain, and Prabin Kumar Padhy. "Comprehensive tuning of Frequency shifted IMC-PID controller for boost converter using Harris Hawk optimization." Engineering Research Express 7, no. 2 (2025): 025352. https://doi.org/10.1088/2631-8695/add4be.

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Abstract The proportional integral derivative (PID) controller has been widely adopted in different applications because of its easy implementation compared to other existing control techniques. In most of the cases, PID controller’s tuning has been focussed on three main parameters: proportional gain K P , integral gain K I , derivative gain K D . Other than the classical approaches, the internal model control (IMC) approach is an established approach to design a PID controller. In the IMC framework, the controller’s performance, viz., stability, robustness and transient response, depends upo

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Zafar, Farhan, Suheel Abdullah Malik, Tayyab Ali, et al. "Stabilization and tracking control of underactuated ball and beam system using metaheuristic optimization based TID-F and PIDD2–PI control schemes." PLOS ONE 19, no. 2 (2024): e0298624. http://dx.doi.org/10.1371/journal.pone.0298624.

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In this paper, we propose two different control strategies for the position control of the ball of the ball and beam system (BBS). The first control strategy uses the proportional integral derivative-second derivative with a proportional integrator PIDD2-PI. The second control strategy uses the tilt integral derivative with filter (TID-F). The designed controllers employ two distinct metaheuristic computation techniques: grey wolf optimization (GWO) and whale optimization algorithm (WOA) for the parameter tuning. We evaluated the dynamic and steady-state performance of the proposed control str

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Noaman, Mohanad N., Abdurahman Basil Ayoub, and Saif S. Mahmood. "Nonlinear Model Predictive Control of a Magnetic Levitation System Using Artificial Protozoa Optimizer." International Journal of Robotics and Control Systems 4, no. 4 (2024): 1947–66. https://doi.org/10.31763/ijrcs.v4i4.1668.

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A magnetic levitation system (Maglev) is a sensitive, multi-parameter, nonlinear, and unstable system that is utilized to levitate a ferromagnetic object in free space. Due to its vast applications, various research studies in the field of control strategy have become extremely important and challenging. This work proposes the design of a nonlinear model predictive (NMPC) control scheme for the object position control against the nonlinearities and uncertainties of a Maglev system. A novel bio-inspired Artificial Protozoa Optimization (APO) algorithm is used to fine-tune the NMPC parameters, w

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Mohammed, Reham H., Mohamed E. Aboelmorsy, and Basem E. Elnaghi. "Path tracking control of differential drive mobile robot based on chaotic-billiards optimization algorithm." International Journal of Electrical and Computer Engineering (IJECE) 13, no. 2 (2023): 1449. http://dx.doi.org/10.11591/ijece.v13i2.pp1449-1462.

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<span lang="EN-US">Mobile robots are typically depending only on robot kinematics control. However, when high-speed motions and highly loaded transfer are considered, it is necessary to analyze dynamics of the robot to limit tracking error. The goal of this paper is to present a new algorithm, chaotic-billiards optimizer (C-BO) to optimize internal controller parameters of a differential-drive mobile robot (DDMR)-based dynamic model. The C-BO algorithm is notable for its ease of implementation, minimal number of design parameters, high convergence speed, and low computing burden. In addi

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Reham, H. Mohammed, E. Dessouki Mohamed, and E. Elnaghi Basem. "Path tracking control of differential drive mobile robot based on chaotic-billiards optimization algorithm." International Journal of Electrical and Computer Engineering (IJECE) 13, no. 2 (2023): 1449–62. https://doi.org/10.11591/ijece.v13i2.pp1449-1462.

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Mobile robots are typically depending only on robot kinematics control. However, when high-speed motions and highly loaded transfer are considered, it is necessary to analyze dynamics of the robot to limit tracking error. The goal of this paper is to present a new algorithm, chaotic-billiards optimizer (C-BO) to optimize internal controller parameters of a differentialdrive mobile robot (DDMR)-based dynamic model. The C-BO algorithm is notable for its ease of implementation, minimal number of design parameters, high convergence speed, and low computing burden. In addition, a comparison between

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Choubey, Ashish, Sachin Kumar Jain, and Prabin Kumar Padhy. "A GWO-Based Indirect IMC-PID Controller for DC-DC Boost Converter." Energies 17, no. 23 (2024): 5954. http://dx.doi.org/10.3390/en17235954.

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A PID controller design using an internal model control (IMC) approach is a well-established method for controller tuning in a DC-DC boost converter. This study introduces an innovative implementation of a novel indirect Internal Model Control (IMC) strategy for PID controller design, tailored specifically for a DC-DC boost converter. While the indirect IMC approach has been documented in prior research, its application to boost converters signifies a substantial contribution to the field. The proposed method simplifies the tuning process by focusing exclusively on the plant shifting parameter

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Wang, Zhiwen, Amirul Syafiq Sadun, Nor Anija Jalaludin, et al. "Particle Swarm Optimization-Based Model-Free Adaptive Control for Time-Varying Batch Processes." International Journal of Automotive and Mechanical Engineering 21, no. 2 (2024): 11263–75. http://dx.doi.org/10.15282/ijame.21.2.2024.7.0870.

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The batch process is a production process with strong nonlinearity, which usually suffers from time-varying parameters and uncertainty of disturbances. Concerning the mentioned problems, this study proposes to investigate the application of the particle swarm optimization-based model-free adaptive control (PSO-MFAC) method for time-varying batch processes. Model-Free Adaptive Control (MFAC) is a data-driven control method, which is one of the promising methods to solve the nonlinear process. Firstly, a Full Form Dynamic Linearization Model-Free Adaptive Control method has been adopted for the

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Chacón, Juan, Jairo Soriano, and Omar Salazar. "Sistema de Inferencia Difusa basado en Relaciones Booleanas y Kleeneanas con Combinador Convexo." Ingeniería 23, no. 1 (2018): 7. http://dx.doi.org/10.14483/23448393.11138.

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Context: In the design process of Fuzzy Inference Systems based on Boolean and Kleenean Relations (FIS-BKR) there is a dilemma choosing the regular kleenean extensions of a given boolean function. The set of possible kleenean extensions of a boolean function has a lattice structure under the usual partial order of functions. The fuzzy convex combination proposed by Zadeh guarantees some properties related to this order.Method: The addition of a convex combiner just before the defuzzifier offers a solution to the above situation. The ISE (Integral Squared Error) and ITSE (Integral Time-weighted

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Daraz, Amil, Suheel Abdullah Malik, Ihsan Ul Haq, Khan Bahadar Khan, Ghulam Fareed Laghari, and Farhan Zafar. "Modified PID controller for automatic generation control of multi-source interconnected power system using fitness dependent optimizer algorithm." PLOS ONE 15, no. 11 (2020): e0242428. http://dx.doi.org/10.1371/journal.pone.0242428.

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In this paper, a modified form of the Proportional Integral Derivative (PID) controller known as the Integral- Proportional Derivative (I-PD) controller is developed for Automatic Generation Control (AGC) of the two-area multi-source Interconnected Power System (IPS). Fitness Dependent Optimizer (FDO) algorithm is employed for the optimization of proposed controller with various performance criteria including Integral of Absolute Error (IAE), Integral of Time multiplied Absolute Error (ITAE), Integral of Time multiplied Square Error (ITSE), and Integral Square Error (ISE). The effectiveness of

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Mohamed, Emad A., Mokhtar Aly, and Masayuki Watanabe. "New Tilt Fractional-Order Integral Derivative with Fractional Filter (TFOIDFF) Controller with Artificial Hummingbird Optimizer for LFC in Renewable Energy Power Grids." Mathematics 10, no. 16 (2022): 3006. http://dx.doi.org/10.3390/math10163006.

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Recent advancements in renewable generation resources and their vast implementation in power sectors have posed serious challenges regarding their operation, protection, and control. Maintaining operating frequency at its nominal value and reducing tie-line power deviations represent crucial factors for these advancements due to continuous reduction of power system inertia. In this paper, a new modified load frequency controller (LFC) method is proposed based on fractional calculus combinations. The tilt fractional-order integral-derivative with fractional-filter (TFOIDFF) is proposed in this

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Camcıoğlu, Ş., B. Özyurt, İ. C. Doğan, and H. Hapoğlu. "Application of response surface methodology as a new PID tuning method in an electrocoagulation process control case." Water Science and Technology 76, no. 12 (2017): 3410–27. http://dx.doi.org/10.2166/wst.2017.506.

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Abstract In this work the application of response surface methodology (RSM) to proportional-integral-derivative (PID) controller parameter tuning for electrocoagulation (EC) treatment of pulp and paper mill wastewater was researched. Dynamic data for two controlled variables (pH and electrical conductivity) were obtained under pseudo random binary sequence (PRBS) input signals applied to manipulated variables (acid and supporting electrolyte flow rates). Third order plus time delay model parameters were evaluated through System Identification Toolbox™ in MATLAB®. Four level full factorial desi

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Mohammed, A. S., and A. Dodo. "Load Frequency Control of One and Two Areas Power System Using Grasshopper Optimization Based Fractional Order PID Controller." Control Systems and Optimization Letters 1, no. 1 (2023): 32–40. http://dx.doi.org/10.59247/csol.v1i1.12.

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In this paper, grasshopper optimization based fractional order PID controller for load frequency control of single and multi-area power system is presented. It is paramount to minimize large frequency deviation in power system control. Large frequency deviation occurs when the parameter values of the various generating units of the power system like generators, turbine and governors keeps changing due to numerous on/off witching in the load side. As such, for a more realistic study, nonlinearities and boiler dynamics has been introduced into the power system design and measures also put in pla

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Slama, Sahar, Yousri Slaoui, and Hamdi Fathallah. "Statistical Inference for Multivariate Conditional Cumulative Distribution Function Estimation By Stochastic Approximation Method." Statistics, Optimization & Information Computing 10, no. 3 (2022): 789–814. http://dx.doi.org/10.19139/soic-2310-5070-1416.

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This paper handles non-parametric estimation of a conditional cumulative distribution function (CCDF). Using a recursive approach, we set forward a multivariate recursive estimator defifined by stochastic approximation algorithm. Our basic objective is to investigate the statistical inference of our estimator and compare it with that of non-recursive Nadaraya-Watson’s estimator. From this perspective, we fifirst derive the asymptotic properties of the proposed estimator which highly depend on the choice of two parameters, the stepsize (γn) as well as the bandwidth (hn). The second generation p

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Patil, Diptee, and Sharad Jadhav. "Design and Analysis of IO and FO Controllers to Investigate the Effects of Process Parameter Perturbations on Lag-Dominant Time Delay Systems." Journal of Robotics and Control (JRC) 5, no. 2 (2024): 509–24. https://doi.org/10.18196/jrc.v5i2.21101.

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This paper focuses on the design, analysis and implementation of Integer-order (IO) and Fractional-order (FO) controllers for systems characterized by lag-dominant time delays. The existing literature has been examined to analyze the methodology employed in tuning IO and FO controllers for first-order time delay system for perturbations in process parameters. It is observed that there is scope to investigate better controllers for lag-dominant time delay systems. The five different structures of controllers are chosen. The paper proposes IO and FO controllers tailored for a test group comprisi

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Sumata, Hiroshi, Frank Kauker, Michael Karcher, and Rüdiger Gerdes. "Covariance of Optimal Parameters of an Arctic Sea Ice–Ocean Model." Monthly Weather Review 147, no. 7 (2019): 2579–602. http://dx.doi.org/10.1175/mwr-d-18-0375.1.

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Abstract The uniqueness of optimal parameter sets of an Arctic sea ice simulation is investigated. A set of parameter optimization experiments is performed using an automatic parameter optimization system, which simultaneously optimizes 15 dynamic and thermodynamic process parameters. The system employs a stochastic approach (genetic algorithm) to find the global minimum of a cost function. The cost function is defined by the model–observation misfit and observational uncertainties of three sea ice properties (concentration, thickness, drift) covering the entire Arctic Ocean over more than two

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Sumata, H., F. Kauker, R. Gerdes, C. Köberle, and M. Karcher. "A comparison between gradient descent and stochastic approaches for parameter optimization of a sea ice model." Ocean Science 9, no. 4 (2013): 609–30. http://dx.doi.org/10.5194/os-9-609-2013.

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Abstract. Two types of optimization methods were applied to a parameter optimization problem in a coupled ocean–sea ice model of the Arctic, and applicability and efficiency of the respective methods were examined. One optimization utilizes a finite difference (FD) method based on a traditional gradient descent approach, while the other adopts a micro-genetic algorithm (μGA) as an example of a stochastic approach. The optimizations were performed by minimizing a cost function composed of model–data misfit of ice concentration, ice drift velocity and ice thickness. A series of optimizations wer

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Sumata, Hiroshi, Frank Kauker, Michael Karcher, and Rüdiger Gerdes. "Simultaneous Parameter Optimization of an Arctic Sea Ice–Ocean Model by a Genetic Algorithm." Monthly Weather Review 147, no. 6 (2019): 1899–926. http://dx.doi.org/10.1175/mwr-d-18-0360.1.

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AbstractImprovement and optimization of numerical sea ice models are of great relevance for understanding the role of sea ice in the climate system. They are also a prerequisite for meaningful prediction. To improve the simulated sea ice properties, we develop an objective parameter optimization system for a coupled sea ice–ocean model based on a genetic algorithm. To take the interrelation of dynamic and thermodynamic model parameters into account, the system is set up to optimize 15 model parameters simultaneously. The optimization is minimizing a cost function composed of the model–observat

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Zeng, Lifang, Jianxin Hu, Dingyi Pan, and Xueming Shao. "Automated Design Optimization of a Mono Tiltrotor in Hovering and Cruising States." Energies 13, no. 5 (2020): 1155. http://dx.doi.org/10.3390/en13051155.

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A mono tiltrotor (MTR) design which combines concepts of a tiltrotor and coaxial rotor is presented. The aerodynamic modeling of the MTR based on blade element momentum theory (BEMT) is conducted, and the method is fully validated with previous experimental data. An automated optimization approach integrating BEMT modeling and optimization algorithms is developed. Parameters such as inter-rotor spacing, blade twist, taper ratio and aspect ratio are chosen as design variables. Single-objective (in hovering or in cruising state) optimizations and multi-objective (both in hovering and cruising st

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Sumata, H., F. Kauker, R. Gerdes, C. Köberle, and M. Karcher. "A comparison between gradient descent and stochastic approaches for parameter optimization of a coupled ocean–sea ice model." Ocean Science Discussions 9, no. 6 (2012): 3593–642. http://dx.doi.org/10.5194/osd-9-3593-2012.

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Abstract. Two types of optimization methods were applied to a parameter optimization problem in a coupled ocean–sea ice model, and applicability and efficiency of the respective methods were examined. One is a finite difference method based on a traditional gradient descent approach, while the other adopts genetic algorithms as an example of stochastic approaches. Several series of parameter optimization experiments were performed by minimizing a cost function composed of model–data misfit of ice concentration, ice drift velocity and ice thickness. The finite difference method fails to estimat

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Kumar, Ramesh, Ashwani Kumar, Laxmikant Laxmikant, Nitesh Dutt, and Varun Pratap Singh. "Cutting Parameters Optimization in Turning Operation using Taguschi Method." International Journal of Materials Manufacturing and Sustainable Technologies 1, no. 2 (2022): 22–30. http://dx.doi.org/10.56896/ijmmst.2022.1.2.009.

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The objective of this study is to optimise the cutting parameters in Turning Operation. For this objective Taguchi Method was used. S/N ratio, ANNOVA was used to investigate the cutting force components & Material removal rate (MRR). In results optimal cutting parameters were obtained and the factors affecting cutting performance were analysed. It was concluded that cutting parameters i.e. depth of cut has influence on cutting force and material removal rate.

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Ebissa, G. K. Dr. K. S. Hari Prasad. "Estimation of open channel flow parameters by using optimization techniques." INTERNATIONAL JOURNAL OF ENGINEERING DEVELOPMENT AND RESEARCH Volume 5 | Issue 2 | May 2017, Volume 5 | Issue 2 | May 2017 (2017): Page Number(s) — 1049–1073. https://doi.org/10.5281/zenodo.583720.

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Open channel flow parameter estimation is an inverse problem, which involves the prediction of a function within a domain, given an error criterion with respect to a set of observed data. Various numerical methods have been developed to estimate open channel flow parameters. For this study, Genetic Algorithm optimization technique is selected. Because of its inherent characteristics, Genetic Algorithm optimization technique avoids the subjectivity, long computation time and ill-posedness often associated with conventional optimization techniques. The present study involves estimation of open c

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Shrestha, Rabin, Zhong Bo Zhan, Ning He, and Liang Li. "Optimization of the Grinding Parameters for CVD Diamond Micro-Tools." Materials Science Forum 800-801 (July 2014): 633–38. http://dx.doi.org/10.4028/www.scientific.net/msf.800-801.633.

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This study is focused on the optimization of the grinding process parameters for the grinding of the CVD diamond micro-milling tool. Two types of CVD diamond i.e. CDM and CDE are used for the study. Feed rate and the grinding velocity are used as the grinding parameters. The optimizations of the parameters are done by studying the two results i.e. grinding force and cutting edge radius. Highest grinding velocity and medium feed rate is found to have the best result for the grinding of the CVD diamond. Keywords: CVD diamond, Grinding, Micro-tool

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YAKUT, Cem, and Sezer ULUKAYA. "PARAMETER OPTIMIZATION FOR UNSUPERVISED RETINAL VESSEL SEGMENTATION WITH IMAGE FILTERING." Mühendislik Bilimleri ve Tasarım Dergisi 10, no. 3 (2022): 844–55. http://dx.doi.org/10.21923/jesd.1033339.

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For the detection and evaluation of eye disorders, retinal pictures are obtained in a digital environment with a customized camera system called the fundus. Due to various noises and unsharp contrast, it is difficult to detect the vessels in the eye by specialists, and this can make it difficult for specialists to diagnose. In this study, unsupervised image processing-based mathematical morphology and Coye filtering, and connected component analysis approaches were used to increase the success of retinal vascular segmentation from fundus images. In addition, retinal images are preprocessed for

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Chen, Yunfei, Jijian Lian, Xin Zhao, and Deming Yang. "Parameter Optimization of Frazil Ice Evolution Model Based on NSGA-II Genetic Algorithm." Water 16, no. 9 (2024): 1232. http://dx.doi.org/10.3390/w16091232.

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This study is based on the research results of frazil ice evolution in recent years and proposes an improved frazil ice evolution mathematical model. Based on the NSGA-II genetic algorithm, seven key parameters were used as optimization design variables, the minimum average difference between the number of frazil ice, the mean and the standard deviation of particle diameter of the simulation results, and the observed data were used as the optimization objective, the Pareto optimal solution set was optimized, and the importance of each objective function was analyzed and discussed. The results

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Das, Biswajit, Susmita Roy, RN Rai, and SC Saha. "Multiobjective optimization of in situ process parameters in preparation of Al-4.5%Cu–TiC MMC using a grey relation based teaching–learning-based optimization algorithm." Proceedings of the Institution of Mechanical Engineers, Part E: Journal of Process Mechanical Engineering 232, no. 4 (2017): 393–407. http://dx.doi.org/10.1177/0954408917710555.

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In modern in situ composite fabrication processes, the selection of optimal process parameters is greatly important for the preparation of best quality metal matrix composite. For achieving high-quality composite, an efficient optimization technique is essential. The present study explores the potential of a new robust algorithm named teaching–learning-based optimization algorithm for in situ process parameter optimization problems in fabrication of Al-4.5%Cu–TiC metal matrix composite fabricated by stir casting technique. Optimization process is carried out for optimizing the in situ processi

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Ay, Mustafa, Selim Hartomacıoğlu, Mühendisi Murat Manav, and Şaban Saraç. "ÇELİK DİRSEK ÜRETİMİNİN SONLU ELEMANLAR ANALİZİ YÖNTEMİ İLE MODELLENMESİ VE ÜRETİM PARAMETRELERİNİN OPTİMİZASYONU." Euroasia Journal of Mathematics, Engineering, Natural & Medical Sciences 8, no. 16 (2021): 49–67. http://dx.doi.org/10.38065/euroasiaorg.582.

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With the advancement of today's technologies, parts of pipe and elbow elements, natural gas pipelines, petrochemicals, machinery manufacturing industry, water distribution and flow systems, sewage systems, foundation piles, shipbuilding industry, nurse containers, aviation, space and defense industry, pipe networks, refineries , steel structures, tube and pipe engineering, etc. widely used in areas. In this study, extrusion method, which is one of the cold forming methods of elbow pipes, has been investigated. When the literature is examined, the production conditions of steel pipes and the pr

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Panteleev, Gleb, Max Yaremchuk, Jacob N. Stroh, Oceana P. Francis, and Richard Allard. "Parameter optimization in sea ice models with elastic–viscoplastic rheology." Cryosphere 14, no. 12 (2020): 4427–51. http://dx.doi.org/10.5194/tc-14-4427-2020.

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Abstract. The modern sea ice models include multiple parameters which strongly affect model solution. As an example, in the CICE6 community model, rheology and landfast grounding/arching effects are simulated by functions of the sea ice thickness and concentration with a set of fixed parameters empirically adjusted to optimize the model performance. In this study, we consider the extension of a two-dimensional elastic–viscoplastic (EVP) sea ice model using a spatially variable representation of these parameters. The feasibility of optimization of the landfast sea ice parameters and rheological

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Rasool, Haaris, Aazim Rasool, Ataul Aziz Ikram, Urfa Rasool, Mohsin Jamil, and Haaziq Rasool. "Compatibility of objective functions with simplex algorithm for controller tuning of HVDC system." Ingeniería e Investigación 39, no. 3 (2020): 34–43. http://dx.doi.org/10.15446/ing.investig.v39n3.70221.

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This work aims to tune multiple controllers at the same time for a HVDC system by using a self-generated (SG) simulation-based optimization technique. Online optimization is a powerful tool to improve performance of the system. Proportion integral (PI) controllers of Multi-infeed HVDC systems are optimized by the evaluation of objective functions in time simulation design (TSD). Model based simulation setup is applied for rapid selection of optimal PI control parameters, designed in PSCAD software. A multiple objective function (OF), i.e. Integral absolute error (IAE), integral square error (I

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Ali, Misbah, Muhammad Sohaib Azam, and Tariq Shahzad. "Random Search-Based Parameter Optimization on Binary Classifiers for Software Defect Prediction." Jurnal Ilmiah Teknik Elektro Komputer dan Informatika 10, no. 2 (2024): 476–88. https://doi.org/10.26555/jiteki.v10i2.28973.

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Machine learning classifiers consist of a set of parameters. The efficiency of these classifiers in the context of software defect prediction is greatly impacted by the parameters chosen to execute the classifiers. These parameters can be optimized to achieve more accurate results. In this research, the efficiency of binary classifiers for software defect prediction is analyzed through parameter optimization using random search technique. Three heterogeneous binary classifiers i.e., Decision tree, Support vector machine, and Naïve Bayes are selected to examine the results of parameter optimiza

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Marcano, Mariano, Hun-Mo Yang, Aniel Nieves-González, Chris Clausen, and Leon C. Moore. "Parameter estimation for mathematical models of NKCC2 cotransporter isoforms." American Journal of Physiology-Renal Physiology 296, no. 2 (2009): F369—F381. http://dx.doi.org/10.1152/ajprenal.00096.2008.

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An optimization problem, formulated using a nonlinear least-squares approach, was used to estimate parameters for kinetic models of the three isoforms of the kidney-specific Na-K-2Cl (NKCC2) cotransporter. Specifically, the optimization problem estimates the magnitude of model parameters (i.e., off-binding and translocation rate constants) by minimizing the distance between model unidirectional fluxes and published unidirectional 86Rb+ uptake curves for the A, B, and F isoforms of the NKCC2 cotransporter obtained in transfected Xenopus oocytes. By using different symmetry assumptions, NKCC2 mo

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Miller, Paul A., Seymour W. Laxon, Daniel L. Feltham, and Douglas J. Cresswell. "Optimization of a Sea Ice Model Using Basinwide Observations of Arctic Sea Ice Thickness, Extent, and Velocity." Journal of Climate 19, no. 7 (2006): 1089–108. http://dx.doi.org/10.1175/jcli3648.1.

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Abstract A stand-alone sea ice model is tuned and validated using satellite-derived, basinwide observations of sea ice thickness, extent, and velocity from the years 1993 to 2001. This is the first time that basin-scale measurements of sea ice thickness have been used for this purpose. The model is based on the CICE sea ice model code developed at the Los Alamos National Laboratory, with some minor modifications, and forcing consists of 40-yr ECMWF Re-Analysis (ERA-40) and Polar Exchange at the Sea Surface (POLES) data. Three parameters are varied in the tuning process: Ca, the air–ice drag co

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Hawary, A. F., and M. I. Ramdan. "Hybrid Hydraulic Vehicle Parameter Optimization using Multi-Objective Genetic Algorithm." International Journal of Automotive and Mechanical Engineering 16, no. 3 (2019): 7007–18. http://dx.doi.org/10.15282/ijame.16.3.2019.13.0525.

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Parameter optimizations of HHV torque distribution must deal with conflicting objectives between the engine torque and fuel economy without compromising the vehicle driving quality. The torque generation from an internal combustion engine (ICE) is directly influenced by the amount of fuel burnt, hence cannot be solved using a classical single-objective optimization method. In this paper, multi-objective genetic algorithm (MOGA) is used to optimize the power split of a parallel hybrid hydraulic vehicle (HHV) that utilizes an ICE and a hydraulic motor. The simulation runs on three operating mode

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Zhang, Yongjie, Xiaofeng Deng, and Xiaohu Zhang. "Constitutive Parameter Optimization Method of Obliquely Incident Reflectivity for Conformal PML." Applied Computational Electromagnetics Society 35, no. 12 (2021): 1463–70. http://dx.doi.org/10.47037/2020.aces.j.351202.

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The conformal perfectly matched layer (PML), i.e., an efficient absorbing boundary condition, is commonly employed to address the open-field scattering problem of electromagnetic wave. To develope a conformal PML exhibiting a significant absorption effect and small reflection error, the present study proposes the constitutive parameter optimization method of obliquely incident reflectivity in terms of the conformal PML. First, the recurrence formula of obliquely incident reflectivity is desired. Subsequently, by the sensitivity analysis of constitutive parameters, the major optimal design vari

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Eltayeb, Ahmed, Gamil Ahmed, Imil Hamda Imran, Nezar M. Alyazidi, and Ahmed Abubaker. "Comparative Analysis: Fractional PID vs. PID Controllers for Robotic Arm Using Genetic Algorithm Optimization." Automation 5, no. 3 (2024): 230–45. http://dx.doi.org/10.3390/automation5030014.

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This paper presents a comparative analysis of a fractional-order proportional–integral–derivative (FO-PID) controller against the standard proportional–integral–derivative (PID) controller, applied to a nonlinear robotic arm manipulator systems. The genetic algorithm (GA) optimization method was implemented to tune the gain parameters of the FO-PID and PID controllers. The performance of the FO-PID and PID controllers were evaluated though different cost functions, including integral of squared error (ISE), integral of absolute error (IAE), integral of time-weighted absolute error (ITAE), and

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Maijama'a, Inusa Sani, Yuhanis Yusof, and Mohamad Farhan Mohsin. "Determination of support vector regression parameters using African buffalo optimization algorithm." Indonesian Journal of Electrical Engineering and Computer Science 28, no. 2 (2022): 1088–95. https://doi.org/10.11591/ijeecs.v28.i2.pp1088-1095.

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The use of support vector regression (SVR) for regression tasks has been on increase over the past few years. Unfortunately, the practical application of SVR for regression task is limited due to its dependence on proper setting of its hyper-parameters and associated kernel parameter. Therefore, it become imperative to device a reliable and fast mechanism of determining the value of these parameters that could guarantee lowest generalization error. This paper presents SVR parameter optimization approaches using African buffalo optimisation (ABO) algorithm, i.e. SVR-ABO. The SVR parameters are

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Singla, Manish Kumar, Jyoti Gupta, Beant Singh, Parag Nijhawan, Almoataz Y. Abdelaziz, and Adel El-Shahat. "Parameter Estimation of Fuel Cells Using a Hybrid Optimization Algorithm." Sustainability 15, no. 8 (2023): 6676. http://dx.doi.org/10.3390/su15086676.

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Because of the current increase in energy requirement, reduction in fossil fuels, and global warming, as well as pollution, a suitable and promising alternative to the non-renewable energy sources is proton exchange membrane fuel cells. Hence, the efficiency of the renewable energy source can be increased by extracting the precise values for each of the parameters of the renewable mathematical model. Various optimization algorithms have been proposed and developed in order to estimate the parameters of proton exchange membrane fuel cells. In this manuscript, a novel hybrid algorithm, i.e., Hyb

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Koziel, Slawomir, and Adrian Bekasiewicz. "A framework for accelerated optimization of antennas using design database and initial parameter set estimation." Engineering Computations 37, no. 7 (2020): 2487–500. http://dx.doi.org/10.1108/ec-06-2019-0267.

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Purpose The purpose of this paper is to exploit a database of pre-existing designs to accelerate parametric optimization of antenna structures is investigated. Design/methodology/approach The usefulness of pre-existing designs for rapid design of antennas is investigated. The proposed approach exploits the database existing antenna base designs to determine a good starting point for structure optimization and its response sensitivities. The considered method is suitable for handling computationally expensive models, which are evaluated using full-wave electromagnetic (EM) simulations. Numerica

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Al-Shamma’a, Abdullrahman A., Fekri Abdulraqeb Ahmed Ali, Mansour S. Alhoshan, et al. "Proton Exchange Membrane Fuel Cell Parameter Extraction Using a Supply–Demand-Based Optimization Algorithm." Processes 9, no. 8 (2021): 1416. http://dx.doi.org/10.3390/pr9081416.

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For proton exchange membrane fuel cells (PEMFCs), the parameter extraction issue is among the most widely studied problems in the field of energy storage systems, since the precise identification of such parameters plays an important role in increasing the PEMFC performance and life span. The optimization process is intended to adjust the performance of PEMFCs by appraising the optimal parameters that produce a good estimation of the current–voltage (I–V) curve. In order to build an accurate equivalent circuit model for PEMFCs, a reliable and effective parameter extraction algorithm, termed a

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P, Vaishnavi, Sneha K, Chandra Mohan G, and Nirmal Narayan M. "Optimization of PID Controller Parameters for First Order plus Time Delay Process." International Journal of Engineering and Advanced Technology (IJEAT) 9, no. 4 (2020): 903–7. https://doi.org/10.35940/ijeat.D7678.049420.

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Pressure control could be a key process variable in industrial sector because pressure provides an important condition for air-conditioning, chemical reaction, boiling, extrusion, vacuuming, and distillation. Worse pressure control will cause critical quality, productivity and safety issues at the same time excessive pressure within a closed container will result in dangerous explosion. Hence, it is highly important to maintain the pressure at desirable range even in the presence of disturbance and the change in set point. Usually the pressure is controlled by Proportional Integral Derivative

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WANG, Qiang, Chenming ZHU, Su PAN, and Yuxi QIN. "IDE-SVM algorithm and it's usage in physical layer security method for IoT." Xibei Gongye Daxue Xuebao/Journal of Northwestern Polytechnical University 42, no. 5 (2024): 882–90. https://doi.org/10.1051/jnwpu/20244250882.

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To address the problem that there is no standard for the parameter selection of support vector machine (SVM) algorithm, a parameter optimization selection method based on the integrated improved differential evolution (IDE) algorithm is proposed, which uses the minimization of the classification error rate as the optimization criterion and the improved differential evolution algorithm to optimize the combination of SVM parameters to obtain an SVM algorithm with higher classification accuracy. At the same time, to avoid the basic DE algorithm from falling into local optimum when solving the SVM

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