Search Results - (( parameter optimization method algorithm ) OR ( motion optimization swarm algorithm ))

SLOW DRIFT MOTIONS IDENTIFICATION OF FLOATING STRUCTURES USING TIME-VARYING INPUT -OUTPUT MODELS by YAZID, EDWAR

“…The first step is presenting the backward estimator and combined forward-backward estimator instead of the only forward estimator in the original input-output models; the second step is reformulating the input-output models into a state-space model so that the Kalman Smoother (KS) adaptive filter can be used to estimate the model coefficients; the third step is optimization of KS parameters using evolutionary computing algorithms such as Particle Swarm Optimization (PSO), Genetic Algorithm (GA) and Artificial Bee Colony (ABC) to form the PSO-KS, GA-KS and ABC-KS as estimation methods.…”
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Hub Angle Control of Double Link Flexible Robotic Arm Manipulator Using PID Controller Tuned by Bacterial Foraging Optimization Algorithm by Amiera Aqilah, M. Rosnani, Muhamad Sukri, Hadi, Annisa, Jamali, Intan Zaurah, Mat Darus, Hanim, Mohd Yatim, Mat Hussin, Ab Talib

“…BFOA is a new swarm intelligence optimization algorithm based on E. …”
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An enhanced motion planning method for industrial robots based on the digital twin concept by Rui, Fan

“…By integrating an improved Artificial potential field method, A* algorithm, and a synergistic approach combining 3-5-3 polynomial interpolation with particle swarm optimization, we effectively address the challenges of dynamic obstacle avoidance and trajectory optimization. …”
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3D virtual modelling and stabilization control of triple links inverted pendulum on two-wheeled system using enhanced interval type-2 fuzzy logic control by Muhammad Firdaus, Masrom

“…Two optimization algorithms are presented in this work which are Spiral Dynamic Algorithm (SDA) and Particle Swarm Optimization (PSO). …”
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Liquid Slosh Control By Implementing Model-Free PID Controller With Derivative Filter Based On PSO by Mohd Tumari, Mohd Zaidi, Zainal Abidin, Amar Faiz, A Subki, A Shamsul Rahimi, Ab Aziz, Ab Wafi, Saealal, Muhammad Salihin, Ahmad, Mohd Ashraf

“…PSO algorithm is responsible to find the optimal values for PIDF parameters based on fitness functions which are Sum Squared Error (SSE) and Sum Absolute Error (SAE) of the cart position and liquid slosh angle response. …”
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Liquid slosh control by implementing model-free PID controller with derivative filter based on PSO by Mohd Zaidi, Mohd Tumari, Amar Faiz, Zainal Abidin, A. Shamsul Rahimi, A. Subki, Ab Wafi, Ab Aziz, Muhammad Salihin, Saealal, Mohd Ashraf, Ahmad

“…PSO algorithm is responsible to find the optimal values for PIDF parameters based on fitness functions which are Sum Squared Error (SSE) and Sum Absolute Error (SAE) of the cart position and liquid slosh angle response. …”
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Bio-inspired snake robot locomotion: a CPG-based control approach by Billah, Md. Masum, Khan, Md. Raisuddin

“…To optimize the CPG parameters, for the optimum output signals, particle swarm optimization (PSO) is applied in this paper. …”
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Marine Predator Algorithm and Related Variants: A Systematic Review by Philibus, Emmanuel, Mohd Zain, Azlan, Prasetya, Didik Dwi, Bahari, Mahadi, Yusup, Norfadzlan, Abdul Jalil, Rozita, Abdul Majid, Mazlina, A Samah, Azurah

“…The Marine Predators Algorithm (MPA) is classified under swarm intelligence methods based on its type of inspiration. …”
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Marine Predator Algorithm and Related Variants: A Systematic Review by Emmanuel, Philibus, Azlan, Mohd Zain, Didik Dwi, Prasetya, Mahadi, Bahari, Norfadzlan, Yusup, Rozita, Abdul Jalil, Mazlina, Abdul Majid, Azurah, A Samah

“…—The Marine Predators Algorithm (MPA) is classified under swarm intelligence methods based on its type of inspiration. …”
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MARKERLESS ARTICULATED HUMAN MOTION TRACKING USING HIERARCHICAL MULTI-SWARM COOPERATIVE PARTICLE SWARM OPTIMIZATION by SAINI, SANJA Y

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Comparative analysis of the model-free tuning techniques for integral state feedback controller of a liquid slosh suppression system by Nurul Najihah, Zulkifli, Mohd Syakirin, Ramli

“…Data-driven Pole Placement (DPP) and Fictitious-Reference-Iterative-Tuning with Particle Swarm Optimization (FRIT-PSO) are the two algorithms proposed as the tuning methods for the selected controller structure. …”
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Hexagon pattern particle swarm optimization based block matching algorithm for motion estimation / Siti Eshah Che Osman by Che Osman, Siti Eshah

“…In this study, a pattern based using Particle Swarm Optimization (PSO) is proposed named as Hexagon PSO (HPSO). …”
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PID Control and Input Shaping for Quadrotor UAV Stabilization and Payload Swing Reduction by Liyana Ramli, Noor Hanis Izzuddin Mat Lazim, Amalin Aisya Mohd Awi, Aina Syazwin Mohd Shukor

Performance evaluation of Black Hole Algorithm, Gravitational Search Algorithm and Particle Swarm Optimization by Zuwairie, Ibrahim, Mohamad Nizam, Aliman, Fardila, Naim, Sophan Wahyudi, Nawawi, Shahdan, Sudin

“…Particle Swarm Optimization (PSO) and Gravitational Search Algorithm are a well known population-based heuristic optimization techniques. …”
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A review on particle swarm optimization algorithm and its variants to human motion tracking by Saini, S., Rambli, D.R.B.A., Zakaria, M.N.B., Sulaiman, S.B.

“…Several approaches have been proposed in the literature using different techniques.However, conventional approaches such as stochastic particle filtering have shortcomings in computational cost, slowness of convergence, suffers from the curse of dimensionality and demand a high number of evaluations to achieve accurate results. Particle swarm optimization (PSO) is a population-based globalized search algorithm which has been successfully applied to address human motion tracking problem and produced better results in high-dimensional search space.This paper presents a systematic literature survey on the PSO algorithm and its variants to human motion tracking. …”
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Optimization Of Sliding Mode Control Using Particle Swarm Algorithm For An Electro-Hydraulic Actuator System by Rozaimi, Ghazali

“…The dynamic parts of electro-hydraulic actuator(EHA) system are widely applied in the industrial field for the process that exposed to the motion control.In order to achieve accurate motion produced by these dynamic parts,an appropriate controller will be needed.However,the EHA system is well known to be nonlinear in nature.A great challenge is carried out in the EHA system modelling and the controller development due to its nonlinear characteristic and system complexity.An appropriate controller with proper controller parameters will be needed in order to maintain or enhance the performance of the utilized controller.This paper presents the optimization on the variables of sliding mode control (SMC) by using Particle Swarm Optimization (PSO) algorithm.The control scheme is established from the derived dynamic equation which stability is proven through Lyapunov theorem.From the obtained simulation results,it can be clearly inferred that the SMC controller variables tuning through PSO algorithm performed better compared with the conventional proportionalintegral-derivative (PID) controller.…”
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A New Approach of Optimal Search Solution in Particle Swarm Optimization (PSO) Algorithm for Object Detection Method by Zalili, Musa, Mohd Hafiz, Mohd Hassin, Nurul Izzatie Husna, Fauzi, Rohani, Abu Bakar, Watada, Junzo

“…Therefore, to overcome the several problems associated with the object detection method, a new approach in Particle Swarm Optimization (PSO) algorithm for optimal search solution as an alternative method to detect of object tracking quickly, precisely and accurately. …”
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A Navigation Strategy for Swarm Robotics Based on Bat Algorithm Optimization Technique by Nur Aisyah Syafinaz, Suarin, Pebrianti, Dwi, Bayuaji, Luhur, Muhammad, Syafrullah, Zulkifli, Musa

“…This paper aims to adapt Bat Algorithm (BA) optimization techniques to the swarm robotics system. …”
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Efficient control of a nonlinear double-pendulum overhead crane with sensorless payload motion using an improved PSO-tuned PID controller by H. I. Jaafar, Z. Mohamed, N. A. Mohd Subha, A. R. Husain, F. S. Ismail, Liyana Ramli, M. O. Tokhi, M. A. Shamsudin

Multi-state PSO GSA for solving discrete combinatorial optimization problems by Ismail, Ibrahim

“…Two examples of meta-heuristics are Particle swarm optimization (PSO) and gravitational search algorithm (GSA), which are based on the social behavior of bird flocks and the Newton's law of gravity and the law of motion, respectively. …”
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