Synchronization of Dual Servo Motor Using CMAC Neural Network-based Lugre Friction Model
Suprapto Suprapto, Taufik Taufik, Aris Nasuha, Edy Riyanto
- 发表年份
- 2021
- 引用次数
- 4
摘要
Synchronization of dual servo motor control has become an important issue due to many applications in engineering fields, such as electric vehicle, robotics, electronics production machines, and others. This paper studies cerebellar model articulation controller (CMAC) neural network (NN) controller to synchronize two servo motors with dynamic LuGre friction model. CMAC is kind of NN method represented by associative memory with more powerful properties. Cross-coupling control structure is employed to synchronize two servo motors in this study. To investigates the performance, MATLAB Simulink is applied to simulate the control design of dual servo motor. The simulation results exhibit that CMAC controller has better output trajectory and works well for two servo motors with different parameters of LuGre friction model.
关键词
相关论文
Statistical Learning Theory
Yuhai Wu, Vladimir Vapnik
1999
Artificial intelligence: a modern approach
1995
Applied Nonlinear Control
Jean-Jacques Slotine, Weiping Li
1991
A new optimizer using particle swarm theory
R.C. Eberhart, James Kennedy
2002