Fuzzy control strategy for an adaptive force control in end-milling

Župerl, Uroš; Čuš, F.; Milfelner, M.

doi:10.1016/j.jmatprotec.2005.02.143

Cited by 78 publications

(29 citation statements)

References 5 publications

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“…This last output gives information about the true output of the system since the milling system is presented as continuous system. Multi-model schemes are intended to lead to automatically switch the value of β in order to achieve better performance in the output continuous time responses attending to some signal performances through the performance index of the equation (13) and switching rules associated to control schemes 1 and 2. In the analysis of multi-model scheme 1 it can be observed that the β-value of the control tends to different values of β before reaching the stationary state.…”

Section: Analysis Of the Outputsmentioning

confidence: 99%

“…10 Other control schemes applied to milling problem are model based approaches, 11 neural networks 12 and fuzzy logic. 13 Recently, model based adaptive control schemes are still widely applied to the milling system for controlling forces 14 and for achieving better surface finish. 15 To address the milling control problem, designers have traditionally used zero order holds (ZOH).…”

Section: Introductionmentioning

confidence: 99%

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Analysis of discrete time schemes for milling forces control under fractional order holds

Rubio

Sen

Longstaff

et al. 2013

Int. J. Precis. Eng. Manuf.

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In this paper, discrete time model reference control schemes for practical milling using different discretization of the continuous-time plant are presented. First, a basic controller scheme is addressed where a fractional order hold with pre-fixed value of the gain is used. Secondly, a multi-model scheme, which outputs different discretization in parallel with the continuous-time milling system transfer function under a fractional order hold (FROH) of correcting β ∈ [−1, 1], is dealt with. Then, an intelligent design framework is designed as a supervisory scheme with two hierarchical levels in order to find the most appropriate value for the gain β. For choosing the value of β, a tracking performance index is designed. It evaluates each pre-defined discretization of the continuous time milling transfer function and the scheme chooses the one with the smallest value of the index in order to generate the real control input to the plant. Two different methods of adjusting this value are presented and discussed. The first one selects a β-value among a fixed pre-defined set of possible values, while the second one the value of β is updated by adding or subtracting a small quantity.

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Section: Analysis Of the Outputsmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Analysis of discrete time schemes for milling forces control under fractional order holds

Rubio

Sen

Longstaff

et al. 2013

Int. J. Precis. Eng. Manuf.

View full text Add to dashboard Cite

show abstract

“…As a result, many CNC systems are inefficient to run under the operating conditions that are far from optimal one. To ensure the quality of machining products, reduce the machining costs and increase the machining efficiency, it is necessary to adjust the machining parameters in real time to satisfy the optimal machining condition at any given time as per modern condition monitoring strategy [4] . The control of CNC machining processes is presently receivManuscript received August 9, 2012; revised December 25, 2012 ing significant attention due to potential economic benefits associated with automated machining.…”

Section: Introductionmentioning

confidence: 99%

Condition Monitoring of CNC Machining Using Adaptive Control

Prasad

Dora

Sandeep

et al. 2013

Int. J. Autom. Comput.

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In this work, an adaptive control constraint system has been developed for computer numerical control (CNC) turning based on the feedback control and adaptive control/self-tuning control. In an adaptive controlled system, the signals from the online measurement have to be processed and fed back to the machine tool controller to adjust the cutting parameters so that the machining can be stopped once a certain threshold is crossed. The main focus of the present work is to develop a reliable adaptive control system, and the objective of the control system is to control the cutting parameters and maintain the displacement and tool flank wear under constraint valves for a particular workpiece and tool combination as per ISO standard. Using Matlab Simulink, the digital adaption of the cutting parameters for experiment has confirmed the efficiency of the adaptively controlled condition monitoring system, which is reflected in different machining processes at varying machining conditions. This work describes the state of the art of the adaptive control constraint (ACC) machining systems for turning. AISI4140 steel of 150 BHN hardness is used as the workpiece material, and carbide inserts are used as cutting tool material throughout the experiment. With the developed approach, it is possible to predict the tool condition pretty accurately, if the feed and surface roughness are measured at identical conditions. As part of the present research work, the relationship between displacement due to vibration, cutting force, flank wear, and surface roughness has been examined.

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“…The proper selection of machining parameters is an important step towards meeting these goals and thus gaining a competitive advantage in the market [4]. Many researchers have studied the effects of optimal selection of machining parameters of end milling [5].…”

Section: Introductionmentioning

confidence: 99%