Distributed Containment Control of MIMO Pure-Feedback Multiagent Systems Using Filter-Driven-Approximation Approach

• Published in: IEEE transactions on systems, man, and cybernetics. Systems Vol. 51; no. 9; pp. 5490 - 5502
• Main Authors: Choi, Yun Ho, Yoo, Sung Jin
• Format: Journal Article
• Language: English
• Published: New York IEEE 01.09.2021; The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
• Subjects: Adaptive control; Approximation; Containment; Containment control; Control design; Control systems design; Convexity; Feedback; filter-driven-approximation (FDA); Fuzzy logic; MIMO communication; Multi-agent systems; multi-input–multi-output (MIMO) pure-feedback multiagent systems; Multiagent systems; Neural networks; Nonlinear systems; Nonlinearity; unknown nonlinearities
• ISSN: 2168-2216; 2168-2232
• DOI: 10.1109/TSMC.2019.2955996

This article addresses a filter-driven-approximation (FDA)-based design problem for the distributed containment control of multi-input-multi-output pure-feedback multiagent systems with completely unknown nonlinearities. Local filter-driven approximators are designed to compensate for unknown nonaffine nonlinear functions lumped in the local controller design procedure where the first-order filtered signals of the error surfaces, state variables, and control inputs are linearly combined for the design of the filter-driven approximators. A containment control scheme using the filter-driven function approximators is recursively constructed to ensure that the outputs of the followers converge to the convex hull spanned by multiple time-varying leaders. Compared with existing containment control results using adaptive neural-network-based or fuzzy-based approximators, the proposed FDA-based containment control scheme depends only on the relative output information among agents and does not require any adaptive techniques. Thus, the proposed control structure can be simplified. It is shown that the closed-loop signals, including approximation errors are semi-globally uniformly ultimately bounded. Simulation examples are provided to validate the effectiveness of the proposed theoretical strategy.