Iterative learning control method for tracking consistency of fractional-order multi-agent system

Abstract

An iterative learning control method for tracking consistency of a fractional-order multi-agent system comprises the following steps: a, transforming the control problem of coordinated tracking of fractional-order multi-agent systems with different orders into a stability control problem of a tracking error system in a fixed time interval; b, designing a distributed P-type iterative learning controller with initial state learning capability; and c, solving an initial state learning matrix and an iterative learning gain matrix to be determined in the iterative learning controller. The inventionsolves the problem of coordinated tracking in the case where the initial state offset and the model unknown exist simultaneously in the fractional-order multi-agent systems with different orders by using the iterative learning control method, and the proposed iterative learning controller is not only simple in design and solving, but also can resist the offset of the initial state, and can ensurethe consistency of fractional-order multi-agent systems with different orders during the whole moving process after certain number of iterations, thereby having high practicability.

Description

technical field [0001] The invention relates to a coordinated tracking control method for a fractional-order multi-agent system that uses an iterative learning control method to solve order differences, initial state offsets and model unknowns, and belongs to the field of control technology. Background technique [0002] Research in recent years has found that some physical systems with special conditions, such as vehicles running on sandy or muddy roads and aircraft flying in rain, snow, hail, etc., should be described by fractional order systems. In addition, many natural phenomena, such as the simultaneous behavior of agents in fractal environments, polymer fluids, and porous media, must also be rationally explained using agent models with fractional-order dynamics. Due to its broad application prospects in engineering, biology and social economy, fractional-order multi-agent systems have become a research hotspot in the field of system control. Researchers in the field ...

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Problems solved by technology

[0005] The purpose of the present invention is to address the drawbacks of the prior art, to provide a fractional-order multi-agent tracking consistency iterative learning control method to solve the fractional-order multi-agent system with order difference, initial state offset and model unknown Coordinated Tracking Control Problem for

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