<abstract xmlns="http://www.w3.org/1999/xhtml">

<p>Effective nonlinear control of manipulators with dynamically coupled arms, like those with direct drives, is the subject of the paper. Model-based predictive control (MPC) algorithms with nonlinear state-space models and most recent disturbance attenuation technique are proposed. This technique makes controller design and online calculations simpler, avoiding necessity of dynamic modeling of disturbances or resorting to additional techniques like SMC. The core of the paper are computationally effective MPC-NPL (Nonlinear Prediction and Linearization) algorithms, where computations at every sample are divided into two parts: prediction of initial trajectories using nonlinear model, then optimization using simplified linearized model. For a comparison, a known CTC-PID algorithm, which is also model-based, is considered. It is applied in standard form and also proposed in more advanced CTC-PID2dof version. For all algorithms a comprehensive comparative simulation study is performed, for a direct drive manipulator under disturbances. Additional contribution of the paper is investigation of influence of sampling period and of computational delay time on performance of the algorithms, which is practically important when using model-based algorithms with fast sampling.</p>
</abstract>

Effective nonlinear control of manipulators with dynamically coupled arms, like those with direct drives, is the subject of the paper. Model-based predictive control (MPC) algorithms with nonlinear state-space models and most recent disturbance attenuation technique are proposed. This technique makes controller design and online calculations simpler, avoiding necessity of dynamic modeling of disturbances or resorting to additional techniques like SMC. The core of the paper are computationally effective MPC-NPL (Nonlinear Prediction and Linearization) algorithms, where computations at every sample are divided into two parts: prediction of initial trajectories using nonlinear model, then optimization using simplified linearized model. For a comparison, a known CTC-PID algorithm, which is also model-based, is considered. It is applied in standard form and also proposed in more advanced CTC-PID2dof version. For all algorithms a comprehensive comparative simulation study is performed, for a direct drive manipulator under disturbances. Additional contribution of the paper is investigation of influence of sampling period and of computational delay time on performance of the algorithms, which is practically important when using model-based algorithms with fast sampling.

Effective nonlinear Predictive and CTC-PID Control of Rigid Manipulators

Journal of Automation, Mobile Robotics and Intelligent Systems

This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.

{"article-title":"Effective nonlinear Predictive and CTC-PID Control of Rigid Manipulators"}

Effective nonlinear control of manipulators with dynamically coupled arms, like those with direct drives, is the subject of the paper. Model-based predictive...

Effective nonlinear Predictive and CTC-PID Control of Rigid Manipulators

Online veröffentlicht: 23. Juni 2024

Seitenbereich: 1 - 16

Eingereicht: 24. Okt. 2023

Akzeptiert: 14. Dez. 2023

DOI: https://doi.org/10.14313/jamris/2-2024/8

Schlüsselwörter
manipulator control, nonlinear control, model predictive control, CTC-PID control, fast sampling, delays

© 2024 Piotr Tatjewski., published by Sciendo

This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.

Effective nonlinear Predictive and CTC-PID Control of Rigid Manipulators

Online veröffentlicht: 23. Juni 2024

Seitenbereich: 1 - 16

Eingereicht: 24. Okt. 2023

Akzeptiert: 14. Dez. 2023

DOI: https://doi.org/10.14313/jamris/2-2024/8

Schlüsselwörtermanipulator control, nonlinear control, model predictive control, CTC-PID control, fast sampling, delays

© 2024 Piotr Tatjewski., published by Sciendo

This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.

Schlüsselwörter
manipulator control, nonlinear control, model predictive control, CTC-PID control, fast sampling, delays