Iterative Learning Control: A Comparison Study

Ouyang, P. R.; Pipatpaibul, Pong-in

doi:10.1115/imece2010-37161

Cited by 11 publications

(8 citation statements)

References 24 publications

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“…Iterative learning control is an approach to minimize the difference between the desired value and the measured value in systems that operate in a repetitive mode (Longman, 2000). Control was based on the so-called previous cycle learning scheme (Ouyang & Pipatpaibul, 2010;Xu et al, 2004), since only the signals from the previous iteration are used to obtain the control signal for the next iteration (see Figure 5). A learning control law was used to update the control signal, as shown in Equation (2 (2)…”

Section: Loading Controlmentioning

confidence: 99%

An integrated continuous downstream process with real‐time control: A case study with periodic countercurrent chromatography and continuous virus inactivation

Löfgren

Gomis-Fons

Andersson

et al. 2021

Biotech & Bioengineering

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Integrated continuous downstream processes with process analytical technology offer a promising opportunity to reduce production costs and increase process flexibility and adaptability. In this case study, an integrated continuous process was used to purify a recombinant protein on laboratory scale in a two‐system setup that can be used as a general downstream setup offering multiproduct and multipurpose manufacturing capabilities. The process consisted of continuous solvent/detergent virus inactivation followed by periodic countercurrent chromatography in the capture step, and a final chromatographic polishing step. A real‐time controller was implemented to ensure stable operation by adapting the downstream process to external changes. A concentration disturbance was introduced to test the controller. After the disturbance was applied, the product output recovered within 6 h, showing the effectiveness of the controller. In a comparison of the process with and without the controller, the product output per cycle increased by 27%, the resin utilization increased from 71.4% to 87.9%, and the specific buffer consumption was decreased by 21% with the controller, while maintaining a similar yield and purity as in the process without the disturbance. In addition, the integrated continuous process outperformed the batch process, increasing the productivity by 95% and the yield by 28%.

show abstract

Section: Loading Controlmentioning

confidence: 99%

An integrated continuous downstream process with real‐time control: A case study with periodic countercurrent chromatography and continuous virus inactivation

Löfgren

Gomis-Fons

Andersson

et al. 2021

Biotech & Bioengineering

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show abstract

“…One of the key advantages of an ILC is that the system's dynamic model is not fully required, making it simple and widely applicable. Since a quadrotor UAV may perform some specific missions shown in [29].…”

Section: Iterative Learning Control (Ilc)mentioning

confidence: 99%

Quadrotor UAV control : online learning approach

Pipatpaibul¹

2021

Preprint

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Quadrotor unmanned aerial vehicles (UAVs) are recognized to be capable of various tasks including search and surveillance for their agilities and small sizes. This thesis proposes a simple and robust trajectory tracking controller for a quadrotor UAV utilizing online Iterative Learning Control (ILC) that is known to be effective for tasks performed repeatedly. Based on a nonlinear model which considers basic aerogynamic and gyroscopic effects, the quadrotor UAV model is simulated to perform a variety of maneuvering such as take-off, landing, smooth translation and horizontal and spatial circular trajectory motions, PD online ILCs wirh switching gain (SPD ILCs) are studies, tested and compared. Simulation results prove the ability of the online ILCs to successfully perform certain missions in the presence of considerably large disturbances and SPD ILCs can obtain faster convergence rates.

show abstract

“…Iterative learning control is an approach to minimize the difference between the desired value and the measured value in systems that operate in a repetitive mode (Longman, 2000). Control was based on the so-called previous cycle learning scheme (Ouyang & Pipatpaibul, 2010;Xu, Heng Lee, & Zhang, 2004), since only the signals from the previous iteration are used to obtain the control signal for the next iteration (see Figure 5). A learning control law was used to update the control signal, as shown in Eq.…”

Section: Loading Controlmentioning

confidence: 99%

An integrated continuous downstream process with real-time control: A case study with periodic countercurrent chromatography and continuous virus inactivation

Löfgren

Gomis-Fons

Andersson

et al. 2020

Preprint

View full text Add to dashboard Cite

Integrated continuous downstream processes with process analytical technology offer a promising opportunity to reduce production costs and increase process flexibility and adaptability. In this case study, an integrated continuous process was used to purify a recombinant protein on laboratory scale in a two-system setup that can be used as a general downstream setup offering multi-product and multi-purpose manufacturing capabilities. The process consisted of continuous solvent/detergent virus inactivation followed by periodic countercurrent chromatography in the capture step, and a final chromatographic polishing step. A real-time controller was implemented to ensure stable operation by adapting the downstream process to external changes. A concentration disturbance was introduced to test the controller. After the disturbance was applied, the product output recovered within 6 hours, showing the effectiveness of the controller. In a comparison of the process with and without the controller, the product output per cycle increased by 27%, the resin utilization increased from 71.4% to 87.9%, and the specific buffer consumption was decreased by 21% with the controller, while maintaining a similar yield and purity as in the process without the disturbance. In addition, the integrated continuous process outperformed the batch process, increasing the productivity by 95% and the yield by 28%.

show abstract

Iterative Learning Control: A Comparison Study

Cited by 11 publications

References 24 publications

An integrated continuous downstream process with real‐time control: A case study with periodic countercurrent chromatography and continuous virus inactivation

An integrated continuous downstream process with real‐time control: A case study with periodic countercurrent chromatography and continuous virus inactivation

Quadrotor UAV control : online learning approach

An integrated continuous downstream process with real-time control: A case study with periodic countercurrent chromatography and continuous virus inactivation

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