Model Predictive Control for Cable-Driven Parallel Robots Using Moving Horizon State Estimation

Yue Hou; Xiaodong Song; Zhiquan Kong; Tong Chen; Huan Zhang

doi:10.1007/978-981-99-8048-2_203

Model Predictive Control for Cable-Driven Parallel Robots Using Moving Horizon State Estimation

Yue Hou, Xiaodong Song^*, Zhiquan Kong, Tong Chen, Huan Zhang

^*Corresponding author for this work

School of Aerospace Engineering

Beijing Institute of Technology

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

Abstract

Taking advantage of fast motion, strong load capacity, and large working space of cable-driven parallel robots (CDPRs), it is newly developed and applied as the capture system for reusable rockets to improve the success of recovery. However, it is a challenge to precisely control the end-effector of CDPRs to catch the landing rocket under the disturbances of the impinging exhaust jet and plume distribution and undergo the inherent unidirectional force characteristic of CDPRs. To deal with this challenge, the combination of the model predictive control (MPC) algorithm and the moving horizon estimation (MHE) method is employed in the capturing process of CDPRs. These two methods are based on the optimization method. The pseudo-drag problem due to the unidirectional force characteristic is solved by MPC, and the disturbances such as process noise and measurement noise on the state feedback loop can be filtered by MHE method. The precision and performance of the combination control scheme are verified and compared by some benchmark simulations.

Original language	English
Title of host publication	Proceedings of the 2nd International Conference on Mechanical System Dynamics - ICMSD 2023
Editors	Xiaoting Rui, Caishan Liu
Publisher	Springer Science and Business Media Deutschland GmbH
Pages	2975-2986
Number of pages	12
ISBN (Print)	9789819980475
DOIs	https://doi.org/10.1007/978-981-99-8048-2_203
Publication status	Published - 2024
Event	2nd International Conference of Mechanical System Dynamics, ICMSD 2023 - Beijing, China Duration: 1 Sept 2023 → 5 Sept 2023

Publication series

Name	Lecture Notes in Mechanical Engineering
ISSN (Print)	2195-4356
ISSN (Electronic)	2195-4364

Conference

Conference	2nd International Conference of Mechanical System Dynamics, ICMSD 2023
Country/Territory	China
City	Beijing
Period	1/09/23 → 5/09/23

Keywords

Cable-driven parallel robots (CDPRs)
Model predictive control (MPC)
Moving horizon estimation (MHE)

Access to Document

10.1007/978-981-99-8048-2_203

Cite this

Hou, Y., Song, X., Kong, Z., Chen, T., & Zhang, H. (2024). Model Predictive Control for Cable-Driven Parallel Robots Using Moving Horizon State Estimation. In X. Rui, & C. Liu (Eds.), Proceedings of the 2nd International Conference on Mechanical System Dynamics - ICMSD 2023 (pp. 2975-2986). (Lecture Notes in Mechanical Engineering). Springer Science and Business Media Deutschland GmbH. https://doi.org/10.1007/978-981-99-8048-2_203

Hou, Yue ; Song, Xiaodong ; Kong, Zhiquan et al. / Model Predictive Control for Cable-Driven Parallel Robots Using Moving Horizon State Estimation. Proceedings of the 2nd International Conference on Mechanical System Dynamics - ICMSD 2023. editor / Xiaoting Rui ; Caishan Liu. Springer Science and Business Media Deutschland GmbH, 2024. pp. 2975-2986 (Lecture Notes in Mechanical Engineering).

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title = "Model Predictive Control for Cable-Driven Parallel Robots Using Moving Horizon State Estimation",

abstract = "Taking advantage of fast motion, strong load capacity, and large working space of cable-driven parallel robots (CDPRs), it is newly developed and applied as the capture system for reusable rockets to improve the success of recovery. However, it is a challenge to precisely control the end-effector of CDPRs to catch the landing rocket under the disturbances of the impinging exhaust jet and plume distribution and undergo the inherent unidirectional force characteristic of CDPRs. To deal with this challenge, the combination of the model predictive control (MPC) algorithm and the moving horizon estimation (MHE) method is employed in the capturing process of CDPRs. These two methods are based on the optimization method. The pseudo-drag problem due to the unidirectional force characteristic is solved by MPC, and the disturbances such as process noise and measurement noise on the state feedback loop can be filtered by MHE method. The precision and performance of the combination control scheme are verified and compared by some benchmark simulations.",

keywords = "Cable-driven parallel robots (CDPRs), Model predictive control (MPC), Moving horizon estimation (MHE)",

author = "Yue Hou and Xiaodong Song and Zhiquan Kong and Tong Chen and Huan Zhang",

note = "Publisher Copyright: {\textcopyright} The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2024.; 2nd International Conference of Mechanical System Dynamics, ICMSD 2023 ; Conference date: 01-09-2023 Through 05-09-2023",

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language = "English",

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Hou, Y, Song, X, Kong, Z, Chen, T & Zhang, H 2024, Model Predictive Control for Cable-Driven Parallel Robots Using Moving Horizon State Estimation. in X Rui & C Liu (eds), Proceedings of the 2nd International Conference on Mechanical System Dynamics - ICMSD 2023. Lecture Notes in Mechanical Engineering, Springer Science and Business Media Deutschland GmbH, pp. 2975-2986, 2nd International Conference of Mechanical System Dynamics, ICMSD 2023, Beijing, China, 1/09/23. https://doi.org/10.1007/978-981-99-8048-2_203

Model Predictive Control for Cable-Driven Parallel Robots Using Moving Horizon State Estimation. / Hou, Yue; Song, Xiaodong; Kong, Zhiquan et al.
Proceedings of the 2nd International Conference on Mechanical System Dynamics - ICMSD 2023. ed. / Xiaoting Rui; Caishan Liu. Springer Science and Business Media Deutschland GmbH, 2024. p. 2975-2986 (Lecture Notes in Mechanical Engineering).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

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AU - Hou, Yue

AU - Song, Xiaodong

AU - Kong, Zhiquan

AU - Chen, Tong

AU - Zhang, Huan

N1 - Publisher Copyright: © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2024.

PY - 2024

Y1 - 2024

N2 - Taking advantage of fast motion, strong load capacity, and large working space of cable-driven parallel robots (CDPRs), it is newly developed and applied as the capture system for reusable rockets to improve the success of recovery. However, it is a challenge to precisely control the end-effector of CDPRs to catch the landing rocket under the disturbances of the impinging exhaust jet and plume distribution and undergo the inherent unidirectional force characteristic of CDPRs. To deal with this challenge, the combination of the model predictive control (MPC) algorithm and the moving horizon estimation (MHE) method is employed in the capturing process of CDPRs. These two methods are based on the optimization method. The pseudo-drag problem due to the unidirectional force characteristic is solved by MPC, and the disturbances such as process noise and measurement noise on the state feedback loop can be filtered by MHE method. The precision and performance of the combination control scheme are verified and compared by some benchmark simulations.

AB - Taking advantage of fast motion, strong load capacity, and large working space of cable-driven parallel robots (CDPRs), it is newly developed and applied as the capture system for reusable rockets to improve the success of recovery. However, it is a challenge to precisely control the end-effector of CDPRs to catch the landing rocket under the disturbances of the impinging exhaust jet and plume distribution and undergo the inherent unidirectional force characteristic of CDPRs. To deal with this challenge, the combination of the model predictive control (MPC) algorithm and the moving horizon estimation (MHE) method is employed in the capturing process of CDPRs. These two methods are based on the optimization method. The pseudo-drag problem due to the unidirectional force characteristic is solved by MPC, and the disturbances such as process noise and measurement noise on the state feedback loop can be filtered by MHE method. The precision and performance of the combination control scheme are verified and compared by some benchmark simulations.

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Y2 - 1 September 2023 through 5 September 2023

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Hou Y, Song X, Kong Z, Chen T, Zhang H. Model Predictive Control for Cable-Driven Parallel Robots Using Moving Horizon State Estimation. In Rui X, Liu C, editors, Proceedings of the 2nd International Conference on Mechanical System Dynamics - ICMSD 2023. Springer Science and Business Media Deutschland GmbH. 2024. p. 2975-2986. (Lecture Notes in Mechanical Engineering). doi: 10.1007/978-981-99-8048-2_203

Model Predictive Control for Cable-Driven Parallel Robots Using Moving Horizon State Estimation

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