A Unified Framework for Multi-Agent Formation with a Non-repetitive Leader Trajectory: Adaptive Control and Iterative Learning Control

Abstract

<p>Formation tracking (FT) control aims at handling cooperative tasks in multi-agent systems (MASs) to achieve desired performance. In these tasks, the leader's input is generally non-zero and unknown to all followers, i.e., its trajectory can be arbitrary and non-repetitive. In this paper, the additive property of linear systems is exploited to develop a unified framework for FT tasks of MASs, consisting of adaptive observer-based control (AOC) and iterative learning control (ILC). This framework employs an AOC controller to guarantee a fixed-shape formation between the leader and followers during the whole process, which reserves the initial condition for ILC. Also, it employs ILC to improve the FT performance of certain repetitive tasks (followers rotating around the leader) over the trials. This gives rise to a fully distributed algorithm working for a directed communication graph containing a spanning tree without requiring any eigenvalue information from the Laplacian matrix of the graph, which enables its application to MASs with a large number of agents. Comparisons are provided via a numerical simulation to show that the proposed combined AOC-ILC algorithm has less FT error than pure AOC (without ILC), which validates the feasibility and efficacy of this algorithm.</p>

An overview of intelligent image segmentation using active contour models

“…The general optimization process of ACMs is to minimize the associated energy function through gradient or steepest descent method. However, it should be aware that it may be hard to figure out the global minima if the energy function is non-convex [33,[84][85][86][87] , which may cause a failed segmentation in the form of falling into a local minima. Specifically, the traditional gradient or steepest descent approach is initialized by the initial level set function and then descends at each iteration, ; the descending direction is controlled by the slope or the derivative of the evolution curve.…”