2007•Journal of Systems Engineering and ElectronicsRequires access

Robust tuning method for modified smith predictor

Guanghui Zhang, Qian Feng, Shao Hui-he

Open publisher page 12 citations

Abstract

A robust tuning method for Åström's two-degree of Freedom Modified Smith Predictor (MSP) is proposed, and it can achieve the fast setpoint and load disturbance responses independently. The tuning rules may meet the requirements within a certain delay margin according to the robustness theory. The simulation results illustrate that the tuning method is efficient compared with other controllers. Finally, the MSP controller is applied to the 15L batch fermentation system for controlling the temperature in bioreactor, and the experiment results further verify that the robust tuning rules may achieve good performance.

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What this paper is about

A robust tuning method for Åström's two-degree of Freedom Modified Smith Predictor (MSP) is proposed, and it can achieve the fast setpoint and load disturbance responses independently. The tuning rules may meet the requirements within a certain delay margin according to the robustness theory. The simulation results illustrate that the tuning method is efficient compared with other controllers. Finally, the MSP controller is applied to the 15L batch fermentation system for controlling the temperature in bioreactor, and the experiment results further verify that the robust tuning rules may achieve good performance.

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OpenAlex reports 12 citations for this work. Citation counts describe recorded attention and do not establish research quality.

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Available abstract

A robust tuning method for Åström's two-degree of Freedom Modified Smith Predictor (MSP) is proposed, and it can achieve the fast setpoint and load disturbance responses independently. The tuning rules may meet the requirements within a certain delay margin according to the robustness theory. The simulation results illustrate that the tuning method is efficient compared with other controllers. Finally, the MSP controller is applied to the 15L batch fermentation system for controlling the temperature in bioreactor, and the experiment results further verify that the robust tuning rules may achieve good performance.

Key concepts: Setpoint, Robustness (evolution), Control theory (sociology), Computer science, Smith predictor, Robust control, Margin (machine learning), Control engineering

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