Repetitive control approach towards automatic tuning of Smith predictor controllers

Tan, Kok Kiong; Chua, Kok Yong; Zhao, Shengyuan; Yang, Seung-Han; Tham, M.T.

doi:10.1016/j.isatra.2008.10.002

Cited by 9 publications

(6 citation statements)

References 24 publications

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“…Due to the industrial-scale application of the TES installation, high stability and reliability of the controller is required. For this reason, Smith's predictor [66][67][68][69] has been selected, as a simple and well-established solution.…”

Section: Implementation Of Annmentioning

confidence: 99%

Application of Phase Change Material and Artificial Neural Networks for Smoothing of Heat Flux Fluctuations

et al. 2021

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The paper presents an innovative method for smoothing fluctuations of heat flux, using the thermal energy storage unit (TES Unit) with phase change material and Artificial Neural Networks (ANN) control. The research was carried out on a pilot large-scale installation, of which the main component was the TES Unit with a heat capacity of 500 MJ. The main challenge was to smooth the heat flux fluctuations, resulting from variable heat source operation. For this purpose, a molten salt phase change material was used, for which melting occurs at nearly constant temperature. To enhance the smoothing effect, a classical control system based on PID controllers was supported by ANN. The TES Unit was supplied with steam at a constant temperature and variable mass flow rate, while a discharging side was cooled with water at constant mass flow rate. It was indicated that the operation of the TES Unit in the phase change temperature range allows to smooth the heat flux fluctuations by 56%. The tests have also shown that the application of artificial neural networks increases the smoothing effect by 84%.

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Section: Implementation Of Annmentioning

confidence: 99%

Application of Phase Change Material and Artificial Neural Networks for Smoothing of Heat Flux Fluctuations

et al. 2021

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“…In recent years, acceleration feedback control is recommended to enhance the robust of the FSM system; however, it almost has little effect on the closed loop bandwidth but only the disturbance attenuation [9]. The Smith predictor, which is famous for its delayfree characteristic and suitable for regulating systems with an excessively long time delay, has been widely used in many systems [10][11][12][13]. The classical Smith predictor is so sensitive to plant parameter variations that a little parameter mismatch could deteriorates the stability of the control system [14] .…”

Section: Introductionmentioning

confidence: 99%

Improved Smith predictor control for fast steering mirror system

Cao

Chen

Deng

et al. 2017

IOP Conf. Ser.: Earth Environ. Sci.

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“…Alvarez et al 29 developed a repetitive controller for tubular heat exchangers with delayed resonance dynamics. Tan et al 30, 31 extended the principle of repetitive control to time‐delay systems. In 31, an additional delay was introduced to improve the performance of an iterative learning controller, and a relay feedback experiment and nonlinear least squares algorithm were employed in 30 to obtain the control parameters.…”

Section: Introductionmentioning

confidence: 99%

“…Tan et al 30, 31 extended the principle of repetitive control to time‐delay systems. In 31, an additional delay was introduced to improve the performance of an iterative learning controller, and a relay feedback experiment and nonlinear least squares algorithm were employed in 30 to obtain the control parameters. In the latest work 32, we have developed a novel continuous controller for time‐delay systems with periodic references and disturbances which is based on the repetitive control design and synthesis methodology.…”

Section: Introductionmentioning

confidence: 99%

Discrete‐time repetitive controller for time‐delay systems with disturbance observer

Costa‐Castelló

Griñó

et al. 2011

Asian Journal of Control

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A novel discrete-time repetitive controller design for time-delay systems subject to a periodic reference and exogenous periodic disturbances is presented. The main idea behind the proposed approach is to take advantage of the plant delay in the controller design, and not to compensate for the effect of this delay. To facilitate this concept, we introduce an appropriate time-delay and a compensator in a positive feedback connection with the plant, such that a generator for periodic signals is constructed. Then a proportional controller is used to stabilize the closed-loop system. The tracking control capability is thus guaranteed according to the internal model principle (IMP). In addition, to attenuate external periodic disturbances, a disturbance observer (DO) is developed to simultaneously achieve reference tracking and disturbance rejection. The possible fractional delay due to the digital discretization is handled by using a fractional delay filter approximation. The proposed controller has a simple structure, in which only a proportional parameter and a low-pass filter are required to be chosen. The closed-loop stability conditions and a robustness analysis under model uncertainties are studied. Numerical simulations and practical experiments on a servo motor system are conducted to verify the feasibility and simplicity of the proposed controller.

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Repetitive control approach towards automatic tuning of Smith predictor controllers

Cited by 9 publications

References 24 publications

Application of Phase Change Material and Artificial Neural Networks for Smoothing of Heat Flux Fluctuations

Application of Phase Change Material and Artificial Neural Networks for Smoothing of Heat Flux Fluctuations

Improved Smith predictor control for fast steering mirror system

Discrete‐time repetitive controller for time‐delay systems with disturbance observer

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