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Predictive control for trajectory tracking and decentralized navigation of multi-agent formations

TLDR
This paper addresses a predictive control strategy for a particular class of multi-agent formations with a time-varying topology to guarantee tracking capabilities with respect to a reference trajectory which is pre-specified for an agent designed as the leader.
Abstract
This paper addresses a predictive control strategy for a particular class of multi-agent formations with a time-varying topology. The goal is to guarantee tracking capabilities with respect to a reference trajectory which is pre-specified for an agent designed as the leader. Then, the remaining agents, designed as followers, track the position and orientation of the leader. In real-time, a predictive control strategy enhanced with the potential field methodology is used in order to derive a feedback control action based only on local information within the group of agents. The main concern is that the interconnections between the agents are time-varying, affecting the neighborhood around each agent. The proposed method exhibits effective performance validated through some illustrative examples.

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Journal ArticleDOI

Neural Network-Based Model Predictive Control: Fault Tolerance and Stability

TL;DR: This brief deals with nonlinear model predictive control designed for a tank unit, which is realized by means of a recurrent neural network, which acts as a one-step ahead predictor, and the control law is derived solving an optimization problem.
Journal ArticleDOI

Towards Robust Predictive Fault-Tolerant Control For A Battery Assembly System

TL;DR: In this article, a robust predictive fault-tolerant strategy is developed that is applied to the battery assembly system, which enables tolerating up to some degree mobile robot, processing and transportation faults.
Journal ArticleDOI

An integrodifferential approach to modeling, control, state estimation and optimization for heat transfer systems

TL;DR: Control-oriented modeling approaches are presented for distributed parameter systems assumed to be described by suitable partial differential equations, based on the method of integrodifferential relations, which can be employed to determine accurate, finite-dimensional sets of state equations by using projection techniques.
Journal ArticleDOI

Predictive control and stabilization of nonholonomic formations with integrated spline-path planning

TL;DR: A path planning in the space of multinominals integrated into a model predictive control mechanism for driving formations of autonomous mobile robots is presented, and the convergence of the method and the requirements for stability are shown on the basis of the Lyapunov theorems.
Proceedings ArticleDOI

Hyperplane arrangements in mixed-integer programming techniques. Collision avoidance application with zonotopic sets

TL;DR: The current paper addresses the problem of minimizing the computational complexity of optimization problems with non-convex and possibly non-connected feasible region of polyhedral type using hyperplane arrangements and Mixed-Integer Programming and provides an efficient description of the feasible region in the solution space.
References
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Book

Computers and Intractability: A Guide to the Theory of NP-Completeness

TL;DR: The second edition of a quarterly column as discussed by the authors provides a continuing update to the list of problems (NP-complete and harder) presented by M. R. Garey and myself in our book "Computers and Intractability: A Guide to the Theory of NP-Completeness,” W. H. Freeman & Co., San Francisco, 1979.
Journal ArticleDOI

Coordination of groups of mobile autonomous agents using nearest neighbor rules

TL;DR: A theoretical explanation for the observed behavior of the Vicsek model, which proves to be a graphic example of a switched linear system which is stable, but for which there does not exist a common quadratic Lyapunov function.
Journal ArticleDOI

Survey Constrained model predictive control: Stability and optimality

TL;DR: This review focuses on model predictive control of constrained systems, both linear and nonlinear, and distill from an extensive literature essential principles that ensure stability to present a concise characterization of most of the model predictive controllers that have been proposed in the literature.
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