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

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  1. 1

    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
  2. 2

    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
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    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
  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

    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
  8. 8

    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
    “…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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    Article
  9. 9

    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
  10. 10

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

    “…At the same time, it is also worthy to consider an optimization tool for the model-free approach that is simple to understand for engineers and can optimize a large number of control parameters in a fast manner. …”
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    Research Report
  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
    “…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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    Article
  12. 12

    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
    “…We have shown that the proposed data-driven tuning tool has a good ability in producing better results for the majority of the performance criteria as compared to other recent metaheuristic optimization algorithms.…”
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    Conference or Workshop Item
  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
  14. 14

    Liquid slosh suppression by implementing data-driven fractional order PID controller based on marine predators algorithm by Mohd Zaidi, Mohd Tumari, Mohd Ashraf, Ahmad, Mohd Riduwan, Ghazali, Nik Mohd Zaitul Akmal, Mustapha, Shahrizal, Saat

    Published 2023
    “…We have shown that the proposed data-driven tuning tool has a good ability in producing better results for the majority of the performance criteria as compared to other recent metaheuristic optimization algorithms.…”
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    Conference or Workshop Item
  15. 15

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

    Published 2015
    “…To optimize the CPG parameters, for the optimum output signals, particle swarm optimization (PSO) is applied in this paper. …”
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    Proceeding Paper
  16. 16

    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
  17. 17

    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
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    Performance of hybrid learning control with input shaping for input tracking and vibration suppression of a flexible manipulator by Md. Zain, M. Z., Tokhi, M. O., Mohamed, 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
  20. 20

    Improving sliding mode control by using model predictive, fuzzy logic, and integral augmented techniques for aerial vehicle model by Zaeri, Amirhossein

    Published 2011
    “…One important suggested method, which can update some SMC parameters online, is model predictive sliding mode control (MPSMC) achieved by merging SMC and model predictive control (MPC). …”
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    Thesis