期刊
IEEE TRANSACTIONS ON CONTROL OF NETWORK SYSTEMS
卷 8, 期 2, 页码 654-666出版社
IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
DOI: 10.1109/TCNS.2021.3087621
关键词
Decentralized control; large-scale biped robot system; linear matrix inequality (LMI); Robust stochastic H-infinity control; virtual leader formation
资金
- Ministry of Science and Technology of Taiwan [MOST 108-2221-E007-009-MY3]
This study proposes a robust decentralized stochastic H-infinity tracking control design for a large-scale biped robot team system, dealing with team formation tracking problem efficiently. By utilizing the concept of virtual leader and decentralized control approach, biped robots can track their reference paths reliably. Through converting the original design problem into a set of independent optimization problems, the difficulties in solving HJIs are overcome using convex optimization methods, and the team formation tracking control can scale to a very large size easily.
In this study, a robust decentralized stochastic H-infinity tracking control design is proposed to deal with the team formation tracking problem for a large-scale biped robot team system with external disturbance and communication requirement on biped robots and leader. Under the concept of virtual leader and the decentralized control approach, biped robots walking in a large-scale team formation are controlled to track their own reference paths with the robust stochastic H-infinity tracking performance. Consequently, the original robust decentralized stochastic H-infinity large-scale biped robot team formation tracking control design problem can be transformed to a set of independent Hamilton-Jacobi inequality (HJI)-constrained optimization problems for each biped robot. To cope with the difficulties in solving the HJIs for the robust decentralized stochasticH(infinity) team formation tracking control design, a numerical framework is introduced to approximate the walking biped robot systems. Based on the tensor-product model transformation technique, the set of independent HJI-constrained optimization problems for the robust decentralized stochastic H-infinity team formation tracking control design is converted into a set of independent linear-matrixinequality-constrained optimization problems, which can be solved efficiently by the convex optimization methods. Since the robust decentralized stochastic H-infinity team formation tracking control can be designed individually, the magnitude of a biped robot team can be easily increased to a very large scale. Finally, a simulation example of decentralized-H-infinity formation tracking control design for a 30-scale biped robot team is given to validate the effectiveness of the proposed scheme.
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