Finite time cooperation method of fractional order agent group under input limitation
By constructing a finite time-varying signal and distributed average time-varying signal estimator suitable for fractional order dynamics, a finite time input restriction control strategy is designed, and the distributed average tracking collaboration problem of fractional order agents under input restriction and finite time constraints is solved, and efficient control effect is achieved.
CN119739040AActive Publication Date: 2025-04-01SHANGHAI JIAOTONG UNIV +1
Patent Information
- Application Number
- CN202411910279.7
- Authority / Receiving Office
- CN · China
- Patent Type
- Applications(China)
- Current Assignee / Owner
- Filing Date
- 2024-12-24
- Publication Date
- 2025-04-01
- Estimated Expiration
- 2044-12-24
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Figure CN119739040A_ABST
Abstract
The invention relates to a finite time cooperation method for a fractional order agent group under input limitation, which comprises the following steps of: describing information flow among fractional order agents, time-varying signals and other agents in a system as a directed graph, and representing information interaction as an algebraic form by utilizing an algebraic graph theory; establishing a fractional order dynamical model of the time-varying signals, and enabling each agent to obtain real-time estimation of the distributed time-varying signals by using a finite time estimation method; on the basis of the constructed directed graph and the real-time estimation of the obtained time-varying signals, enabling each agent to obtain real-time estimation of average time-varying signals by using a finite time distributed estimation method; and based on the real-time estimation of the obtained average time-varying signal, designing a finite time input limited control strategy to realize distributed average tracking. Compared with the prior art, the control method provided by the invention is suitable for a fractional order system, the restrictive relationship between time constraint and input limitation is relieved, and distributed average tracking is guaranteed.
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