Successfully reported this slideshow.
We use your LinkedIn profile and activity data to personalize ads and to show you more relevant ads. You can change your ad preferences anytime.

Motor Control

222 views

Published on

A robot arm is tasked to apply the liquid glue on an object with constant tension. There are a number of ways to convert motor’s torque to linear tension.

Published in: Devices & Hardware
  • Be the first to comment

  • Be the first to like this

Motor Control

  1. 1. Robotic Liquid Tension Identification with Particle Swarm Optimized Neural Network By Hong Xuan Qian, Jian Bing Wu, Yu Hui Shi and Jun Steed Huang 23 – 26 September 2012 Bandung, Indonesia
  2. 2. 2Power Matters. About the authors and the university The authors: • Hong was among the key engineers who set up the first automation line in China for Purina (now part of Nestle), her major is industry automation and its applications, she is co-founder of GenieView Inc. • Dr. Wu is a full time professor at Jiangsu University, who pioneered the research in mathematical models for sensor less motor, she collaborates well with industry partners. • Prof. Shi is the adjunct professor at Jiangsu University, who co-authored the early books of Computational Intelligence ISBN9781558607590 and Swarm Intelligence ISBN9781558605954. • Prof. Huang is the distinguished professor at Jiangsu University, who has initiated a number of multi-national industry-academic collaborations, he is co-founder of GenieView Inc. The university • Up to 8 digits 3.1415926 made by Wenyuan at AD461 remained the most accurate for following 900+ years, was from Jiangsu where our University is exactly located! 22012 IEEE Symposium on Industrial Electronics and Applications 祖冲之祖冲之祖冲之祖冲之
  3. 3. 3Power Matters. Agenda 1. INTRODUCTION 2. TENSION MODEL FOR ROBOT MOTOR 3. SWARM NEURON OPTIMIZATION 4. MATLAB SIMULATION 5. CONCLUSION AND FUTURE WORK 32012 IEEE Symposium on Industrial Electronics and Applications
  4. 4. 4Power Matters. 1. Problem: maintain a constant liquid tension 42012 IEEE Symposium on Industrial Electronics and Applications A robot arm is tasked to apply the liquid glue on an object with constant tension. There are a number of ways to convert motor’s torque to linear tension: Single Sensor less Motor is simple and cheap, but the tension may fluctuate. Single Motor with Sensors, the tension is under control by the sensors but could be expensive. Dual Motor System without Sensors is relatively simple, smooth and not too expensive.
  5. 5. Power Matters. 1. Solutions that we tried and failed 52012 IEEE Symposium on Industrial Electronics and Applications a) The direct motor model calculation cannot follow the liquid variation from the random interference and measurement errors occurred in our factory; b) Kalman filter can deal with random noise and measurement errors, but it can not follow the variation of individual motor parameter and its related aging factor; c) The complicated adaptive model method can partially deal with the individual variation, but it does not treat the random noise and measurement error, as it may not converge properly due to real time computation burden. d) The error Back-Propagation (BP) algorithm is a popular training method for feed-forward Neural Network (NN), but we found the parameter trained for one motor does not fit the other.
  6. 6. Power Matters. 2. Liquid tension = Right tension – Left tension 62012 IEEE Symposium on Industrial Electronics and Applications M1M0 kl kr f1f2 f0 M2 ARM 2r 1r r r lf rf object glue motor inertia is analogous to mass, etc: Motor belt Mass flow Inertia Mass Torque Disturbance Rotation Line Speed Tension Force
  7. 7. Power Matters. 2. Nonlinear map: current -> speed -> tension 72012 IEEE Symposium on Industrial Electronics and Applications IsL IeL “s” means starting, “e” means ending, “L” means left, “R” means right; we want the liquid tension or tension difference between left belt and right belt remains constant, from starting to the ending position during the glue brushing process. fsL = feL current arm tension rotation speed - fsR - feR LEFT RIGHT IsR IeR
  8. 8. Power Matters. 2. Nonlinear liquid boundary condition 82012 IEEE Symposium on Industrial Electronics and Applications s “s” means starting, “e” means ending, “o” means object; we want the liquid tension has minimum variation, it means optimum brushing speed. feo position linear speed fso Object in between e liquid tension
  9. 9. Power Matters. 3. Neurons to learn nonlinear relationships 92012 IEEE Symposium on Industrial Electronics and Applications 1 z )(ˆ kF )2(1 kis 1 z 1 z 1 z )1(1 kis )(1 kis )1(1 kis )2(2 kis 1 z 1 z )2(2 kis 1 z 1 z )(1 kis )2(1 kis )(2 kis )1(2 kis )(2 kis )1(2 kis Tension Control Model NN Neural network s-Sigmoid function Captures nonlinear from both liquid and motor: 浦东 浦东
  10. 10. Power Matters. 4. PSO is smooth and quick! 1 0 2012 IEEE Symposium on Industrial Electronics and Applications Merits Optimized STD of Epoch Average Epoch STD of Target Value BP 89 71 0.04 PSO 40 41 0.02
  11. 11. Power Matters. 5. Conclusion and future work The equation of liquid tension difference for robot motor driven arm system controlled by current is obtained. A neural network trained by PSO identifies the liquid tension from dual-motor system using laboratory data. The simulation shows the approach is a viable solution for high volume and precise tooling robot arms. New algorithm doubles the speed and the smoothness at the same cost. The disadvantage is that the amount of statistics needed could be huge to reduce mechanical vibration noise. 1 1 2012 IEEE Symposium on Industrial Electronics and Applications
  12. 12. 12Power Matters. Thank you! Questions are welcome: 1 2 2012 IEEE Symposium on Industrial Electronics and Applications hong.qian@genieview.com; wjbb0140@163.com shi@ieee.org steedhuang@ujs.edu.cn

×