Control of Airflow Speed in Laboratory Model of Hot-air Tunnel

Matušů, Radek; Prokop, Roman

doi:10.1016/j.proeng.2015.01.403

Cited by 2 publications

(3 citation statements)

References 5 publications

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“…24. Analogously to the previous similar figures, 19 • 41 = 779 blue curves correspond to the samples of the normalized perturbations and one black curve represents the weight function (60). Moreover, Fig.…”

Section: Control Of Airflow Speed In a Hot-air Tunnelmentioning

confidence: 74%

“…The scheme of the hot-air tunnel and its connection with the whole control system is shown in Fig. 23 [59][60][61][62]. Note that due to better visibility, the secondary ventilator is displayed on the opposite side than it is placed in the real plant.…”

Section: Control Of Airflow Speed In a Hot-air Tunnelmentioning

confidence: 99%

“…In [59][60][61], the mathematical model with parametric uncertainty was obtained by means of performing identification experiments at various operational points. More specifically, the controlled plant was identified as the second-order system with a double time constant:…”

Section: Control Of Airflow Speed In a Hot-air Tunnelmentioning

confidence: 99%

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Section: Control Of Airflow Speed In a Hot-air Tunnelmentioning

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Experimental Investigation and Control of a Hot-Air Tunnel with Improved Performance and Energy Saving

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The paper is focused on the identification, control design, and experimental verification of a two-input two-output hot-air laboratory apparatus representing a small-scale version of appliances widely used in the industry. A decentralized multivariable controller design is proposed, satisfying control-loop decoupling and measurable disturbance rejection. The proposed inverted or equivalent noninverted decoupling controllers serve for the rejection of cross-interactions in controlled loops, whereas open-loop antidisturbance members satisfy the absolute invariance to the disturbances. Explicit controller-structure design formulae are derived, and their equivalence to other decoupling schemes is proven. Three tuning rules are used to set primary controller parameters, which are further discretized. All the control responses are simulated in the Matlab/Simulink environment. In the experimental part, two data-acquisition, communication, and control interfaces are set up. Namely, a programmable logic controller and a computer equipped with the peripheral component interconnect card commonly used in industrial practice are implemented. A simple supervisory control and data acquisition human−machine interface via the Control Web environment is developed. The laboratory experiments prove better temperature control performance measured by integral criteria by 35.3%, less energy consumption by up to 6%, and control effort of mechanical actuator parts by up to 17.1% for our method compared to the coupled or disturbance-ignoring design in practice. It was also observed that the use of a programmable logic controller gives better performance measures for both temperature and air-flow control.

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Control of Airflow Speed in Laboratory Model of Hot-air Tunnel

Cited by 2 publications

References 5 publications

Calculation of robustly relatively stabilizing PID controllers for linear time-invariant systems with unstructured uncertainty

Calculation of robustly relatively stabilizing PID controllers for linear time-invariant systems with unstructured uncertainty

Experimental Investigation and Control of a Hot-Air Tunnel with Improved Performance and Energy Saving

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