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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 | Size | Format | |
---|---|---|---|
7961243.pdf | 710.37 kB | Adobe 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 | Size | Format | |
---|---|---|---|
7961243.pdf | 710.37 kB | Adobe 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 | Size | Format | |
---|---|---|---|
7961243.pdf | 710.37 kB | Adobe PDF |