Search Results - (( using optimization model algorithm ) OR ( control optimization path algorithm ))
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1
A Novel Integrating Between Tool Path Optimization Using An ACO Algorithm And Interpreter For Open Architecture CNC System
Published 2021“…Furthermore, high-performing Ant Colony Optimization (ACO) algorithms were used to optimize the travel path time. …”
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Article -
2
A hybrid sampling-based path planning algorithm for mobile robot navigation in unknown environments
Published 2013“…Finally, an adaptive neuro-fuzzy inference system (ANFIS) was designed which constructs and optimizes a fuzzy logic controller using a given dataset of input/output variables in order to increase the optimality and stability rates of the proposed path planning algorithm. …”
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Thesis -
3
Modelling Autonomous Evacuation Navigation System (AENS) for optimal route using Dijkstra's algorithm
Published 2016“…Through ST adaptation, all subsystems were integrated and using the “Dijkstra’s algorithm” (DA) by modifying its function from shortest path algorithm to safest and shortest algorithm, to the nearest exit. …”
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4
Comparative analysis of spiral dynamic algorithm and artificial bee colony optimization for position control of flexible link manipulators
Published 2024“…By integrating the ABC algorithm into the manipulator's control system, the goal is to enhance its ability to plan paths and optimize trajectories. …”
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5
Improvement and application of particle swarm optimization algorithm
Published 2025“…This method combines CPTD with the Genetic Algorithm and PSO (GAPSO), resulting in an effective strategy for dynamic formation reconfiguration and path optimization. …”
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6
Transmission path optimization Based on Efficiency Communication System
Published 2022“…This paper points out the research focus of the wireless sensor network transmission path and discusses the optimization problem of the transmission based on grid model. …”
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Conference or Workshop Item -
7
Optimal Control of Directional Drilling Process
Published 2014“…In order to develop an optimal control strategy in guiding the bit movement, the kinematic and dynamic model of the drill string and bit movement has been derived at the first stage. …”
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Final Year Project -
8
Modeling and multi-objective optimal sizing of standalone photovoltaic system based on evolutionary algorithms
Published 2020“…The IEM algorithm uses the attraction-repulsion mechanism to change the positions of solutions towards the optimality. …”
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9
A safe overtaking control scheme for autonomous vehicles using rapid-exploration random tree
Published 2022“…The improved algorithm is used to obtain the rough obstacle avoidance of the vehicle. …”
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Proceedings -
10
Path Following Using A Learning Neural Network
Published 2004“…This thesis is a development ofprevious works done by [2} on capability of neural controller to efficiently track prescribed paths. Equipped with knowledge on optimal preview control obtained from [1], the initial weights of linear and nonlinear neural controller are initialized to the optimal gains. …”
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Final Year Project -
11
Modeling and control of a Pico-satellite attitude using Fuzzy Logic Controller
Published 2010“…The contribution of this work is to optimize the base of Fuzzy membership function of the APFLC by using GA technique. …”
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Thesis -
12
Development of a motion planning and obstacle avoidance algorithm using adaptive neuro fuzzy inference system for mobile robot navigation
Published 2017“…The present algorithm exhibits attractive features such as high optimality, high stability, low running cost and zero failure rates. …”
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13
Design and modelling of an autonomous robotic airship with soft computing control
Published 2012“…The result shows a feasible means of UAV control. Along with the prototype airship, a path planner was also proposed for the UAV for the purpose of obstacle avoidance and path optimization using genetic algorithm to minimize on the distance travelled and to generate the shortest path to cover the specified waypoints. …”
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Thesis -
14
Composite nonlinear feedback control with multi-objective particle swarm optimization for active front steering system
Published 2024journal::journal article -
15
Adaptive model predictive control based on wavelet network and online sequential extreme learning machine for nonlinear systems
Published 2015“…The WNMPC is developed by a proposed algorithm named adaptive updating rule (AUR) used with gradient descent optimization method to minimize a constrained cost function over the prediction and control horizons and to offer a robust control performances. …”
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16
A novel swarm-based optimisation algorithm inspired by artificial neural glial network for autonomous robots
Published 2019“…Artificial neuro-glial networks is proposed to be combined in the swarm-based communication algorithm to provide a human-like model for the robot's communication and optimization.…”
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Monograph -
17
Estimation of Transformers Health Index Based on Condition Parameter Factor and Hidden Markov Model
Published 2023“…Electric transformers; Health; Hidden Markov models; Nonlinear programming; Probability distributions; Quality control; Viterbi algorithm; Condition parameters; Dissolved gas analysis; Distribution transformer; Emission probabilities; Health indices; Non-linear optimization; Remaining useful lives; Transition probabilities; Parameter estimation…”
Conference Paper -
18
Adaptive manet OLSR routing protocol for optimal route selection in high dynamic network
Published 2020“…The proposed Quality of Path QoP metric is incorporated into the modified relay selection algorithm, which improves the efficiency of relay selection mechanism to find optimal path with high link quality. …”
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Thesis -
19
Development of a State-Space Observer for Active Noise Control Systems
Published 2009“…The secondary path of the ANC system is modeled by using the LMS algorithm to complete the design of the Filtered-X Least Mean Square (FXLMS) controller. …”
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20
Examining the round trip time and packet length effect on window size by using the Cuckoo search algorithm
Published 2016“…This signifies that the training was successful based on the fitted values of the window size. Thus the proposed model trained with the CS algorithm provides a high convergence rate to the true global minimum and a better optimal solution. …”
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