Mathematical models used for adaptive control of machine tools

Ralston, Patricia A. S.; Ward, Thomas L.

doi:10.1016/0895-7177(88)90675-9

Cited by 3 publications

(2 citation statements)

References 23 publications

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“…This technique was used in [22] and [23]. In the late 1980s, the development of artificial intelligence provided new supervisor possibilities, resulting in proposals such as in [24], where fuzzy logic is used, or in [25], which is based on neural networks. Those kinds of supervisors were also used in recent works such as [26], [27], [28] and [29].…”

Section: Introductionmentioning

confidence: 99%

Iso-m Based Adaptive Fractional Order Control With Application to a Soft Robotic Neck

et al. 2020

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This paper proposes an adaptive fractional feedback control using recursive least squares algorithm for plant identification and a recent real-time method (iso-m) for fractional controller tuning. The combination of both methods allows keeping the same original performance specifications invariant, combining adaptability and robustness in a single scheme. Thanks to the robust controller, the system performance is maintained around a specified operating point, and due to the adaptive scheme, this operating point is adjusted depending on plant changes. Extensive experimentation of the proposal is carried out in a real platform with non-linear time varying properties, a soft robotic neck made of 3D printer soft materials. The experiments proposed consist in the neck inclination control using tilt sensors installed on the tip. According to expectations, an invariant performance despite plant parameter changes was observed throughout the experiments. The good results obtained in the proposed test platform suggest that the benefits of this control scheme are suitable for other nonlinear time varying applications.

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Section: Introductionmentioning

confidence: 99%

Iso-m Based Adaptive Fractional Order Control With Application to a Soft Robotic Neck

et al. 2020

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“…When planning the experiment and in its course, each factor (listed in Table 1) was assigned three levels: the lower level (-1), the middle level (0), and the upper level (+1). Technological modes of semi-finishing turning were selected in accordance with the data given in the references [4], [5], [6], [7].…”

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confidence: 99%

Experimental research method when developing a mathematical model for calculating cutting speed in the course of turning steels with a coated tool

et al. 2019

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The article is devoted to the description of the experimental research method when developing a mathematical model for calculating the cutting speed based on information from the cutting zone obtained during the test run in the process of turning using steel coated tools as an example. This paper also presents the results of an experimental study which prove the effectiveness of applying the obtained mathematical dependence.

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Investigation on performance of Model Reference Adaptive Control (MRAC) and PI controller for machine tool application

Junoh

Abdullah

Anang

et al. 2016

2016 IEEE Conference on Systems, Process and Control (ICSPC)

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Mathematical models used for adaptive control of machine tools

Cited by 3 publications

References 23 publications

Iso-m Based Adaptive Fractional Order Control With Application to a Soft Robotic Neck

Iso-m Based Adaptive Fractional Order Control With Application to a Soft Robotic Neck

Experimental research method when developing a mathematical model for calculating cutting speed in the course of turning steels with a coated tool

Investigation on performance of Model Reference Adaptive Control (MRAC) and PI controller for machine tool application

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