Control of industrial robot using neural network compensator | Zendy

Vesna Ranković | Zendy; Ilija Nikolić | Zendy

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Control of industrial robot using neural network compensator

Author(s) -

Vesna Ranković,

Ilija Nikolić

Publication year - 2005

Publication title -

theoretical and applied mechanics

Language(s) - English

Resource type - Journals

SCImago Journal Rank - 0.279

H-Index - 6

eISSN - 2406-0925

pISSN - 1450-5584

DOI - 10.2298/tam0502147r

Subject(s) - control theory (sociology) , artificial neural network , computer science , compensation (psychology) , torque , controller (irrigation) , robot , acceleration , trajectory , matlab , control engineering , feed forward , industrial robot , control (management) , engineering , artificial intelligence , psychology , physics , classical mechanics , astronomy , biology , psychoanalysis , agronomy , thermodynamics , operating system

In the paper is considered synthesis of the controller with tachometric feedback with feed forward compensation of disturbance torque, velocity and acceleration errors. It is difficult to obtain the desired control performance when the control algorithm is only based on the robot dynamic model. We use the neural network to generate auxiliary joint control torque to compensate these uncertainties. The two-layer neural network is used as the compensator. The main task of control system here is to track the required trajectory. Simulations are done in MATLAB for RzRyRy robot minimal configuration

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