Abstract
In this study, a fuzzy sliding mode controller based on RBFNN is proposed for robot manipulator. Fuzzy logic is used to adjust the gain of the corrective control of the sliding mode controller. The weights of the RBFNN are adjusted according to some adaptive algorithm for the purpose of controlling the system states to hit the sliding surface and then slide along it. The paper is organized as follows: In section 2 model of robot manipulator is defined. Adaptive neural network based fuzzy sliding mode controller is presented in section 3. Robot parameters and simulation results obtained for the control of three link scara robot are presented in section 4. Section 5 concludes the paper.
Keywords
Artificial neural network
Robot manipulator
Computer science
Control theory (sociology)
Sliding mode control
Manipulator (device)
Mode (computer interface)
Neuro-fuzzy
Control engineering
Fuzzy logic
Control (management)
Artificial intelligence
Fuzzy control system
Robot
Engineering
Nonlinear system
Physics
Human–computer interaction
Subject Areas
Industrial Technology and Control Systems
·Control and Systems Engineering ·Physical Sciences
Advanced Algorithms and Applications
·Control and Systems Engineering ·Physical Sciences
Advanced Sensor and Control Systems
·Control and Systems Engineering ·Physical Sciences
Citations by Year
2013: 1
2014: 1
2020: 1
OpenAlex SDG Match
SDGs auto-classified by OpenAlex (score ≥ 0.4 shown).
Affordable and clean energy 68%
Loading…
Loading…