Please use this identifier to cite or link to this item: http://localhost/handle/Hannan/207665
Title: A Model Compensation-Prediction Scheme for Control of Micromanipulation Systems With a Single Feedback Loop
Authors: Weize Zhang;Juntian Qu;Xuping Zhang;Xinyu Liu
Year: 2017
Publisher: IEEE
Abstract: Many micromanipulation systems employ sensorless actuators and possess unknown modeling errors, feedback measurement noises, and time delays. Conventional model-based control schemes ignore some of these uncertainties, and thus sacrifice the control system performance. This paper presents a new model compensation-prediction scheme for micromanipulation systems that can be described by two-dimensional state-space models, estimate the unknown modeling errors from noisy single feedback measurement, and predict and compensate the system time delay. This approach combines two modeling errors into a single equivalent modeling error through mathematical transformation, and estimates the combined term using a noise-insensitive extended high-gain observer. After removing the unknown term, the system is then transformed into a time-invariant form, and a Smith predictor is implemented to predict and compensate the time delay. The effectiveness of the proposed compensation-prediction scheme is demonstrated by both numerical simulations and experiments on two typical micromanipulation systems, namely a robotic biosample stimulator and a material characterization microgripper. The results show that this method can significantly improve the control performance of a conventional proportional-integral-derivative controller, by simultaneously reducing the settling time and overshoot of the micromanipulation systems.
URI: http://localhost/handle/Hannan/207665
volume: 22
issue: 5
More Information: 1973,
1982
Appears in Collections:2017

Files in This Item:
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7961243.pdf710.37 kBAdobe PDF
Title: A Model Compensation-Prediction Scheme for Control of Micromanipulation Systems With a Single Feedback Loop
Authors: Weize Zhang;Juntian Qu;Xuping Zhang;Xinyu Liu
Year: 2017
Publisher: IEEE
Abstract: Many micromanipulation systems employ sensorless actuators and possess unknown modeling errors, feedback measurement noises, and time delays. Conventional model-based control schemes ignore some of these uncertainties, and thus sacrifice the control system performance. This paper presents a new model compensation-prediction scheme for micromanipulation systems that can be described by two-dimensional state-space models, estimate the unknown modeling errors from noisy single feedback measurement, and predict and compensate the system time delay. This approach combines two modeling errors into a single equivalent modeling error through mathematical transformation, and estimates the combined term using a noise-insensitive extended high-gain observer. After removing the unknown term, the system is then transformed into a time-invariant form, and a Smith predictor is implemented to predict and compensate the time delay. The effectiveness of the proposed compensation-prediction scheme is demonstrated by both numerical simulations and experiments on two typical micromanipulation systems, namely a robotic biosample stimulator and a material characterization microgripper. The results show that this method can significantly improve the control performance of a conventional proportional-integral-derivative controller, by simultaneously reducing the settling time and overshoot of the micromanipulation systems.
URI: http://localhost/handle/Hannan/207665
volume: 22
issue: 5
More Information: 1973,
1982
Appears in Collections:2017

Files in This Item:
File SizeFormat 
7961243.pdf710.37 kBAdobe PDF
Title: A Model Compensation-Prediction Scheme for Control of Micromanipulation Systems With a Single Feedback Loop
Authors: Weize Zhang;Juntian Qu;Xuping Zhang;Xinyu Liu
Year: 2017
Publisher: IEEE
Abstract: Many micromanipulation systems employ sensorless actuators and possess unknown modeling errors, feedback measurement noises, and time delays. Conventional model-based control schemes ignore some of these uncertainties, and thus sacrifice the control system performance. This paper presents a new model compensation-prediction scheme for micromanipulation systems that can be described by two-dimensional state-space models, estimate the unknown modeling errors from noisy single feedback measurement, and predict and compensate the system time delay. This approach combines two modeling errors into a single equivalent modeling error through mathematical transformation, and estimates the combined term using a noise-insensitive extended high-gain observer. After removing the unknown term, the system is then transformed into a time-invariant form, and a Smith predictor is implemented to predict and compensate the time delay. The effectiveness of the proposed compensation-prediction scheme is demonstrated by both numerical simulations and experiments on two typical micromanipulation systems, namely a robotic biosample stimulator and a material characterization microgripper. The results show that this method can significantly improve the control performance of a conventional proportional-integral-derivative controller, by simultaneously reducing the settling time and overshoot of the micromanipulation systems.
URI: http://localhost/handle/Hannan/207665
volume: 22
issue: 5
More Information: 1973,
1982
Appears in Collections:2017

Files in This Item:
File SizeFormat 
7961243.pdf710.37 kBAdobe PDF