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Multiobjective Trajectory Optimization and Adaptive Backstepping Control for Rubber Unstacking Robot Based on RFWNN Method
- Source :
- Mathematical Problems in Engineering, Vol 2018 (2018)
- Publication Year :
- 2018
- Publisher :
- Hindawi Limited, 2018.
-
Abstract
- Multiobjective trajectory optimization and adaptive backstepping control method based on recursive fuzzy wavelet neural network (RFWNN) are proposed to solve the problem of dynamic modeling uncertainties and strong external disturbance of the rubber unstacking robot during recycling process. First, according to the rubber viscoelastic properties, the Hunt-Crossley nonlinear model is used to construct the robot dynamics model. Then, combined with the dynamic model and the recycling process characteristics, the multiobjective trajectory optimization of the rubber unstacking robot is carried out for the operational efficiency, the running trajectory smoothness, and the energy consumption. Based on the trajectory optimization results, the adaptive backstepping control method based on RFWNN is adopted. The RFWNN method is applied in the main controller to cope with time-varying uncertainties of the robot dynamic system. Simultaneously, an adaptive robust control law is developed to eliminate inevitable approximation errors and unknown disturbances and relax the requirement for prior knowledge of the controlled system. Finally, the validity of the proposed control strategy is verified by experiment.
- Subjects :
- 0209 industrial biotechnology
Article Subject
Computer science
General Mathematics
lcsh:Mathematics
General Engineering
Process (computing)
02 engineering and technology
Trajectory optimization
lcsh:QA1-939
Viscoelasticity
020901 industrial engineering & automation
Control theory
lcsh:TA1-2040
Backstepping
0202 electrical engineering, electronic engineering, information engineering
Trajectory
Robot
020201 artificial intelligence & image processing
lcsh:Engineering (General). Civil engineering (General)
Subjects
Details
- Language :
- English
- ISSN :
- 15635147
- Volume :
- 2018
- Database :
- OpenAIRE
- Journal :
- Mathematical Problems in Engineering
- Accession number :
- edsair.doi.dedup.....42a95bf47131cb6295bc3d5b0aabeae7