DocumentCode :
1577575
Title :
A deadband-control and prediction co-design approach for networked robotic systems
Author :
Gao, Zhengnan ; Xie, Ronghua ; Chen, Qingwei ; Hu, Weili
Author_Institution :
Sch. of Autom., Nanjing Univ. of Sci. & Technol., Nanjing, China
fYear :
2009
Firstpage :
2215
Lastpage :
2220
Abstract :
The cooperation of robotic systems over wireless network results in some challenges, finite network bandwidth, and limited node energy. A novel co-design approach is presented by means of combining deadband-control with dynamic prediction in this paper. To reduce the network traffic and energy consumption, the control packets of "Controlling" robots are only sent if the response error and error changes are larger than the given deadband threshold. Furthermore, the modified Brown third exponential smoothing prediction is introduced to reconstruct the untransmitted values in "Actuating" robots, where parameters are dynamically optimized by a modified Particle Swarm Optimization (PSO) algorithm. Finally, the comparative experimental results indicate that the effectiveness and applicability of the proposed approach are very well.
Keywords :
actuators; decentralised control; distributed control; exponential distribution; motion control; particle swarm optimisation; radio access networks; robots; smoothing methods; Brown third exponential smoothing prediction; actuating robots; co-design approach; deadband control; dynamic prediction; error changes; networked robotic systems; particle swarm optimization; response error; wireless network; Bandwidth; Communication system traffic control; Energy consumption; Error correction; Medical robotics; Robot control; Robotics and automation; Sampling methods; Smoothing methods; Wireless networks;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Robotics and Biomimetics (ROBIO), 2009 IEEE International Conference on
Conference_Location :
Guilin
Print_ISBN :
978-1-4244-4774-9
Electronic_ISBN :
978-1-4244-4775-6
Type :
conf
DOI :
10.1109/ROBIO.2009.5420473
Filename :
5420473
Link To Document :
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