Fuzzy logic for large mining bucket wheel reclaimer motion control—from an engineer's perspective

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,iron-steel 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 logic-based control built on a model-based 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.

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, iron-steel 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 logic-based control built on a model-based control loop. The investigation provides engineers with an example of applying fuzzy logic in a model based approach to properly control the nlotion of a large BWR following defined trajectories, as well as to show possible ways of further improving the eontroller performance. The result indicates that fuzzy logic can be applied easily by engineers to overcome most motion control issues involving a large BWR.