[1]LU Tienfu.Fuzzy logic for large mining bucket wheel reclaimer motion control—from an engineer’s perspective[J].智能系统学报,2011,6(1):85-94.
LU Tienfu.Fuzzy logic for large mining bucket wheel reclaimer motion control—from an engineer’s perspective[J].CAAI Transactions on Intelligent Systems,2011,6(1):85-94.
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LU Tienfu.Fuzzy logic for large mining bucket wheel reclaimer motion control—from an engineer’s perspective[J].CAAI Transactions on Intelligent Systems,2011,6(1):85-94.
Fuzzy logic for large mining bucket wheel reclaimer motion control—from an engineer’s perspective
《智能系统学报》[ISSN 1673-4785/CN 23-1538/TP] 卷:
6
期数:
2011年第1期
页码:
85-94
栏目:
学术论文—人工智能基础
出版日期:
2011-02-25
- Title:
- Fuzzy logic for large mining bucket wheel reclaimer motion control—from an engineer’s perspective
- 文章编号:
- 1673-4785(2011)01-0085-10
- Keywords:
- bucket wheel reclaimer; modeling; simulation; motion control; fuzzy logic
- 分类号:
- TP273.4
- 文献标志码:
- A
- 摘要:
- The bucket wheel reclaimer (BWR) is a key piece of equipment which has been widely used for stacking and reclaiming bulk materials (i.e. iron ore and coal) in places such as ports, ironsteel plants, coal storage areas, and power stations from stockpiles. BWRs are very large in size, heavy in weight, expensive in price, and slow in motion. There are many challenges in attempting to automatically control their motion to accurately follow the required trajectories involving uncertain parameters from factors such as friction, turbulent wind, its own dynamics, and encoder limitations. As BWRs are always heavily engaged in production and cannot be spared very long for motion control studies and associated developments, a BWR model and simulation environment closely resembling real life conditions would be beneficial. The following research focused mainly on the implementation of fuzzy logic to a BWR motion control from an engineer’s perspective. First, the modeling of a BWR including partially known parameters such as friction force and turbulence to the system was presented. This was then followed by the design of a fuzzy logicbased control built on a modelbased control loop. The investigation provides engineers with an example of applying fuzzy logic in a model based approach to properly control the motion of a large BWR following defined trajectories, as well as to show possible ways of further improving the controller performance. The result indicates that fuzzy logic can be applied easily by engineers to overcome most motion control issues involving a large BWR.
- Abstract:
- The bucket wheel reclaimer (BWR) is a key piece of equipment which has been widely used for stacking and reclaiming bulk materials (i.e. iron ore and coal) in places such as ports, ironsteel plants, coal storage areas, and power stations from stockpiles. BWRs are very large in size, heavy in weight, expensive in price, and slow in motion. There are many challenges in attempting to automatically control their motion to accurately follow the required trajectories involving uncertain parameters from factors such as friction, turbulent wind, its own dynamics, and encoder limitations. As BWRs are always heavily engaged in production and cannot be spared very long for motion control studies and associated developments, a BWR model and simulation environment closely resembling real life conditions would be beneficial. The following research focused mainly on the implementation of fuzzy logic to a BWR motion control from an engineer’s perspective. First, the modeling of a BWR including partially known parameters such as friction force and turbulence to the system was presented. This was then followed by the design of a fuzzy logicbased control built on a modelbased control loop. The investigation provides engineers with an example of applying fuzzy logic in a model based approach to properly control the motion of a large BWR following defined trajectories, as well as to show possible ways of further improving the controller performance. The result indicates that fuzzy logic can be applied easily by engineers to overcome most motion control issues involving a large BWR.
- 参考文献/References:
-
［1］LU Tienfu, XU Shihong. SPSim: a stockpile simulator for analyzing material quality distribution in mining［C］//International Conference on Mechatronics and Automation (ICMA 2010). Xi’an, China, 2010: 299304.
［2］CHOI C, LEE K, SHIN K, et al. Inverse kinematics of a reclaimer: redundancy and solution［C］//IEEE International Conference on Systems, Man, and Cybernetics. Orlando, USA, 1997: 28832887.
［3］CHOI C, LEE K, SHIN K, et al. Automatic landing method of a reclaimer on the stockpile［J］. IEEE Transactions on Systems, Man, and Cybernetics—Part C: Applications and Reviews, 1999, 29(1): 308314.
［4］HONG K S, CHOI C. Taskoriented approaches to the inverse kinematics problem for a reclaimer excavating and transporting raw material［J］. Advanced Robotics, 2000, 14(3): 185204.
［5］LU Tienfu. Bucket wheel reclaimer modelling as a robotic arm［C］//IEEE International Conference on Robotics and Biomimetics. Guilin, China, 2009: 263268.
［6］LU Tienfu. Preparation for turning a bucket wheel reclaimer into a robotic arm［C］//IEEE International Conference on Robotics and Biomimetics. Bangkok, Thailand, 2008: 17101715.
［7］LU Tienfu, LIN G C. Intelligent systems techniques and their application in manufacturing systems［M］//LEONDES C T. Expert systems: the technology of knowledge management and decision making for the 21st century. San Diego, USA: Academic Press, 2002: 381410.
［8］LU Tienfu, MYO M T R. Optimization of reclaiming voxels for quality grade target with reclaimer minimum movement［C］//The Eleventh International Conference on Control, Automation, Robotics and Vision(ICARCV 2010). Singapore, 2010: 13501410.
备注/Memo
Received Date:2010-09-25.
Corresponding Author:LU Tienfu.
E-mail:tienfu.lu@adelaide.edu.au.
About the author:
?LU Tienfu received his PhD in Manufacturing and Mechanical Engineering from the University of South Australia in 1997. He was a postdoctoral researcher at the University of South Australia between 1997 and 2000. He is the leader of the robotics research lab at the University of Adelaide and his current research interests include intelligent mobile robotics (modelling, trajectory planning, localisation, and navigation), underwater robotics (modelling, localisation, and navigation), insect robotics (chemical plume source localisation), mechatronic technologies in mining, and micromotion robotic systems (pzt actuator modelling and control, and micromotion stages).
更新日期/Last Update:
2011-04-13