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FUZZY CONTROL ROBOT ENERGY SAVING METHOD BASED ON PARTICLE SWARM OPTIMISATION ALGORITHM
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AI
DOI：10.2316/J.2024.206-1043.png)
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Abstract
En 中文
To obtain a long running time for battery-powered mobile robots, implementing energy-efficient control over their motion process is important. In this study, a fuzzy logic control (FLC) optimisation method is proposed to diminish the energy expenditure of a differential drive wheeled mobile robot (WMR) during its movement by using the particle swarm optimisation (PSO) algorithm. Unlike conventional energy-saving methods, such as reducing the robot acceleration, this study designs a fuzzy logic controller based on a planned optimal path to control the left- and right-wheel angular velocities of the differential drive WMR to enable it to navigate from its initial position to the target location. The membership function of the fuzzy logic controller is optimised based on the PSO algorithm, and an optimal fuzzy logic controller can be obtained to decrease the energy loss of the battery. Compared with other methods, the proposed method can save over 85% in energy consumption.
Keywords:
Differential drive wheeled mobile robot
fuzzy logic control
particle swarm optimisation
optimal control
Journal
IF:
1
Papers:
8
Citations:
507