Continuous Optimal Infeed Control for Cylindrical Plunge Grinding, Part 2: Controller Design and Implementation

2004 ◽  
Vol 126 (2) ◽  
pp. 334-340 ◽  
Author(s):  
Shaoqiang Dong ◽  
Kourosh Danai ◽  
Stephen Malkin

This is the second of two papers concerned with on-line optimization of cylindrical plunge grinding cycles with continuously varying infeed control. In the first paper [1], dynamic programming was applied to a simulation of the cylindrical grinding process in order to explore the characteristics of optimal grinding cycles. Optimal cycles were found to consist of distinct segments each with predominant constraints. An optimal control policy was formulated with the infeed rate within each segment determined according to the prevailing constraint. The present paper is concerned with the design of the controller and its implementation. The control system to implement the optimization policy is described together with provisions to enhance robustness to modeling uncertainty and measurement noise. Robustness provisions include model adaptation by parameter estimation from on-line measurements of size and power, and incorporation of safety margins in the optimization process. Problems associated with practical implementation of the control system, stemming from power limitations and wheel wear, are also discussed. The controller performance is demonstrated on an instrumented internal cylindrical grinding machine.

2004 ◽  
Vol 126 (2) ◽  
pp. 327-333 ◽  
Author(s):  
Shaoqiang Dong ◽  
Kourosh Danai ◽  
Stephen Malkin ◽  
Abhijit Deshmukh

A new methodology is developed for optimal infeed control of cylindrical plunge grinding cycles. Unlike conventional cycles having a few sequential stages with discrete infeed rates, the new methodology allows for continuous variation of the infeed rate to further reduce the cycle time. Distinctive characteristics of optimal grinding cycles with variable infeed rates were investigated by applying dynamic programming to a simulation of the grinding cycle. The simulated optimal cycles were found to consist of distinct segments with predominant constraints. This provided the basis for an optimal control policy whereby the infeed rate is determined according to the active constraint at each segment of the cycle. Accordingly, the controller is designed to identify the state of the cycle at each sampling instant from on-line measurements of power and size, and to then compute the infeed rate according to the optimal policy associated with that state. The optimization policy is described in this paper, and the controller design and its implementation are presented in the following paper [1].


Author(s):  
X. Wu ◽  
Y. Yang

This paper presents a new design of omnidirectional automatic guided vehicle based on a hub motor, and proposes a joint controller for path tracking. The proposed controller includes two parts: a fuzzy controller and a multi-step predictive optimal controller. Firstly, based on various steering conditions, the kinematics model of the whole vehicle and the pose (position, angle) model in the global coordinate system are introduced. Secondly, based on the modeling, the joint controller is designed. Lateral deviation and course deviation are used as the input variables of the control system, and the threshold value is switched according to the value of the input variable to realise the correction of the large range of posture deviation. Finally, the joint controller is implemented by using the industrial PC and the self-developed control system based on the Freescale minimum system. Path tracking experiments were made under the straight and circular paths to test the ability of the joint controller for reducing the pose deviation. The experimental results show that the designed guided vehicle has excellent ability to path tracking, which meets the design goals.


2013 ◽  
Vol 133 (4) ◽  
pp. 313-323 ◽  
Author(s):  
Kuniaki Anzai ◽  
Kimihiko Shimomura ◽  
Soshi Yoshiyama ◽  
Hiroyuki Taguchi ◽  
Masaru Takeishi ◽  
...  

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