Search Results - (( motion optimization method algorithm ) OR ( motion optimization model algorithm ))

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  1. 1

    Multilevel optimization for dense motion estimation by Saaban, Azizan, Kalmoun, El Mostafa, Ibrahim, Haslinda, Ramli, Razamin, Omar, Zurni

    Published 2011
    “…We evaluated the performance of different optimization techniques developed in the context of optical flow computation with different variational models.In particular, based on truncated Newton methods (TN) that have been an effective approach for large-scale unconstrained optimization, we developed the use of efficient multilevel schemes for computing the optical flow.More precisely, we evaluated the performance of a standard unidirectional multilevel algorithm - called multiresolution optimization (MR/Opt), to a bidrectional multilevel algorithm - called full multigrid optimization (FMG/Opt).The FMG/Opt algorithm treats the coarse grid correction as an optimization search direction and eventually scales it using a line search. …”
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    Monograph
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    A Metaheuristic Optimization Using Explosion Method On A Hybrid Pd2-Lqr Quadcopter Controller by Raihan, Mohamad Norherman Shauqie Mohamed

    Published 2021
    “…Therefore, an optimization algorithm based on the explosion method called REA was proposed and implemented on the proposed Hybrid PD2-LQR control structure. …”
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    Thesis
  4. 4

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

    Published 2015
    “…Three steps of improvements had been made to increase the modeling capacity of input-output models. 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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    Thesis
  5. 5

    Enhancement of ant colony optimization in multi-robot source seeking coordination by Jun Wei Lee, Nyiak Tien Tang, Kit Guan Lim, Min Keng Tan, Baojian Yang

    Published 2019
    “…In hardware platform, the speed of rotation of the wheel is controlled for various movement such as direct motion and rotation in place. Optimization method is focused on ant colony optimization. …”
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    Proceedings
  6. 6

    Block based motion vector estimation using fuhs16 uhds16 and uhds8 algorithms for video sequence by S. S. S. , Ranjit

    Published 2011
    “…This chapter proposes modelling of fast unrestricted hexagon search (FUHS16) and unrestricted hexagon-diamond search (UHDS16) algorithms for motion vector estimation, which is based on the theory and application of block-based motion estimation. …”
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    Book Chapter
  7. 7

    PID-based control of a single-link flexible manipulator in vertical motion with genetic optimisation by Md Zain, Badrul Aisham, Tokhi, M. Osman, Toha, Siti Fauziah

    Published 2009
    “…This paper presents an investigation into dynamic simulation and controller optimization based on genetic algorithms (GAs) for a single-link flexible manipulator system in vertical plane motion. …”
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    Proceeding Paper
  8. 8

    An enhanced motion planning method for industrial robots based on the digital twin concept by Rui, Fan

    Published 2025
    “…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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    Thesis
  9. 9

    A study on model-free approach for liquid slosh suppression based on stochastic approximation by Ahmad, Mohd Ashraf

    “…For the past decades, various control strategies of liquid slosh motion are based on model-based control schemes. Nevertheless, these methods are difficult to apply in practice. …”
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    Research Report
  10. 10

    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

    Published 2020
    “…Based on the simulation results, the suggested tuning method is capable to reduce the liquid slosh level in the same time produces fast input tracking of the tank without precisely model the chaotic motion of the fluid.…”
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    Article
  11. 11

    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

    Published 2020
    “…Based on the simulation results, the suggested tuning method is capable to reduce the liquid slosh level in the same time produces fast input tracking of the tank without precisely model the chaotic motion of the fluid.…”
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    Article
  12. 12

    Bio-inspired snake robot locomotion: a CPG-based control approach by Billah, Md. Masum, Khan, Md. Raisuddin

    Published 2015
    “…This research shows a novel algorithm to generate online sinusoidal motion generation using CPG for planar space. …”
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    Proceeding Paper
  13. 13

    Development of data-driven controller for slosh suppression in liquid cargo vehicles by Mohd Falfazli, Mat Jusof, Ahmad, Mohd Ashraf, Raja Ismail, R. M.T., Suid, Mohd Helmi, Saari, Mohd Mawardi

    “…For the past decades, various control strategies of liquid slosh motion are based on model-based control schemes. Nevertheless, these methods are difficult to apply in practice. …”
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    Research Report
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    Liquid slosh suppression by implementing data-driven fractional order pid controller based on marine predators algorithm by Mohd Tumari, Mohd Zaidi Mohd, Mustapha, Nik Mohd Zaitul Akmal, Ahmad, Mohd Ashraf, Saat, Shahrizal, Ghazali, Mohd Riduwan

    Published 2023
    “…Traditionally, the control system development of liquid slosh problems usually employed a model-based approach which is difficult to utilize practically since the fluid motion in the container is very chaotic and hard to model perfectly. …”
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    Conference or Workshop Item
  16. 16

    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

    Published 2020
    “…Two optimization algorithms are presented in this work which are Spiral Dynamic Algorithm (SDA) and Particle Swarm Optimization (PSO). …”
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    Thesis
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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

    Published 2022
    “…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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    Conference or Workshop Item
  19. 19

    Parameter estimation of stochastic differential equation by Haliza Abd. Rahman, Arifah Bahar, Norhayati Rosli, Madihah Md. Salleh

    Published 2012
    “…The results showed that the Mean Square Errors (MSE) for stochastic model with parameters estimated using optimal knot for 1,000, 5,000 and 10,000 runs of Brownian motions are smaller than the SDE models with estimated parameters using knot selected heuristically. …”
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    Article
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    Vision based automatic steering control using a PID controller by Abdullah, A.S., Hai, L.K., Osman, N.A.A., Zainon, M.Z.

    Published 2006
    “…Initially, a collocated proportional-derivative (PD) controller utilizing hub-angle and hub-velocity feedback is developed for control of rigid-body motion of the system. This is then extended to incorporate iterative learning control with genetic algorithm (GA) to optimize the learning parameters and a feedforward controller based on input shaping techniques for control of vibration (flexible motion) of the system. …”
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    Article