Safe consensus tracking with guaranteed full state and input constraints: A control barrier function based approach
In this paper, we consider the safe consensus tracking problem for uncertain second-order nonlinear multi-agent systems subject to both position, velocity and input constraints. The agents are required to cooperatively track a desired leader's trajectory while always satisfying their local stat...
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Published in | IEEE transactions on automatic control Vol. 68; no. 12; pp. 1 - 8 |
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Main Authors | , , |
Format | Journal Article |
Language | English |
Published |
New York
IEEE
01.12.2023
The Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
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Abstract | In this paper, we consider the safe consensus tracking problem for uncertain second-order nonlinear multi-agent systems subject to both position, velocity and input constraints. The agents are required to cooperatively track a desired leader's trajectory while always satisfying their local state and input constraints. Therefore, conflicting objectives may exist for an agent when the desired trajectory violates its local constraints. We propose to solve this problem using a control barrier function based (CBF-based) approach. The cooperative tracking objective is encoded by a novel control Lyapunov function based (CLF-based) condition while the state and input constraints are handled by CBF-based constraints. For the relative degree two position constraint, two classes of CBF-based conditions are proposed based on high-order CBFs and a modified CBF design, respectively. It is proven that, with the modified CBF, there always exist feasible control inputs which satisfy all the CBF-based constraints. Then, unified quadratic programming (QP) based controllers are formulated and the performances are analyzed. Simulation examples are provided to verify the obtained results. |
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AbstractList | In this article, we consider the safe consensus tracking problem for uncertain second-order nonlinear multiagent systems subject to position, velocity, and input constraints. The agents are required to cooperatively track a desired leader's trajectory while always satisfying their local state and input constraints. Therefore, conflicting objectives may exist for an agent when the desired trajectory violates its local constraints. We propose to solve this problem using a control barrier function (CBF)-based approach. The cooperative tracking objective is encoded by a novel control Lyapunov function-based condition while the state and input constraints are handled by CBF-based constraints. For the relative degree two position constraint, two classes of CBF-based conditions are proposed based on high-order CBFs and a modified CBF design, respectively. It is proven that, with the modified CBF, there always exist feasible control inputs that satisfy all the CBF-based constraints. Then, unified quadratic programming-based controllers are formulated and the performances are analyzed. Simulation examples are provided to verify the obtained results. In this paper, we consider the safe consensus tracking problem for uncertain second-order nonlinear multi-agent systems subject to both position, velocity and input constraints. The agents are required to cooperatively track a desired leader's trajectory while always satisfying their local state and input constraints. Therefore, conflicting objectives may exist for an agent when the desired trajectory violates its local constraints. We propose to solve this problem using a control barrier function based (CBF-based) approach. The cooperative tracking objective is encoded by a novel control Lyapunov function based (CLF-based) condition while the state and input constraints are handled by CBF-based constraints. For the relative degree two position constraint, two classes of CBF-based conditions are proposed based on high-order CBFs and a modified CBF design, respectively. It is proven that, with the modified CBF, there always exist feasible control inputs which satisfy all the CBF-based constraints. Then, unified quadratic programming (QP) based controllers are formulated and the performances are analyzed. Simulation examples are provided to verify the obtained results. |
Author | Wen, Guanghui Yu, Xinghuo Fu, Junjie |
Author_xml | – sequence: 1 givenname: Junjie orcidid: 0000-0002-1528-8727 surname: Fu fullname: Fu, Junjie organization: Jiangsu Key Laboratory of Networked Collective Intelligence, School of Mathematics, Southeast University, Nanjing, China – sequence: 2 givenname: Guanghui orcidid: 0000-0003-0070-8597 surname: Wen fullname: Wen, Guanghui organization: Jiangsu Key Laboratory of Networked Collective Intelligence, School of Mathematics, Southeast University, Nanjing, China – sequence: 3 givenname: Xinghuo orcidid: 0000-0001-8093-9787 surname: Yu fullname: Yu, Xinghuo organization: School of Engineering, RMIT University, Melbourne, VIC, Australia |
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Snippet | In this paper, we consider the safe consensus tracking problem for uncertain second-order nonlinear multi-agent systems subject to both position, velocity and... In this article, we consider the safe consensus tracking problem for uncertain second-order nonlinear multiagent systems subject to position, velocity, and... |
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SubjectTerms | control barrier function input saturation Liapunov functions Lyapunov methods multi-agent system Multi-agent systems Multiagent systems Nonlinear systems Quadratic programming Safe consensus tracking Safety Stability analysis state constraint Target tracking Tracking problem Trajectory Upper bound |
Title | Safe consensus tracking with guaranteed full state and input constraints: A control barrier function based approach |
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