Indian Journal of Science and Technology
Year: 2016, Volume: 9, Issue: 7, Pages: 1-5
*Author for Correspondence
E. Khoobjou Department of Electrical Engineering, Islamic Azad University, South Tehran Branch, Tehran, Iran; [email protected]
Background/Objectives: The combination of fuzzy logic and neural networks enables the system to have the capability of learning and adapting to the environment, as well as tolerating the imprecise circumstances which is an advantage of fuzzy logic methods. The objective is to control robot’s claw with two movable arms. Methods/Statistical Analysis: A new hybrid approach is proposed to control the arm of flexible robots by using neural networks, fuzzy algorithms and particle swarm optimization algorithm. Findings: As a result of the recommended network, the values of 91.353e-5 and 0.030255 have been recorded for MSE and RMSE, respectively. Applications/Improvements: It was simulated to control the movement of a robot with two arms in a completely flexible manner in which the network can be momentarily trained by moving the rotation ring
Keywords: Controlling the Flexible Arm, Fuzzy Neural Networks, Particle Swarm Optimization Algorithm, Soft Computing
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