This paper addresses the adaptive formation control of a group of vertical take-off and landing (VTOL) unmanned aerial vehicles (UAV) with switching-directed interaction topologies. In addition, to tackle the adverse effect of disturbances, a couple of smooth bounded estimators are involved in the procedure design. Exploiting an extraction algorithm, we take advantage of the fully actuated rotational dynamics, to control the translational dynamics of each vehicle. We propose a distributed control scheme such that all vehicles track a desired reference velocity signal while keeping a desired prespecified formation. In this framework, the underlying topology of the agents may switch among several directed graphs, each having a spanning tree. The stability of the overall closed-loop system is proved through Lyapunov function. Finally, simulation results are given to better highlight the effectiveness of the proposed control scheme.
In this paper, we provide a comprehensive assessment of the consensus of high-order nonlinear multi-agent systems with input saturation and time-varying disturbance under switching topologies. The control directions and model parameters of agents are supposed to be unknown. Our approach is based on transforming the problem of consensus for a network that consists of high-order nonlinear agents to that of perturbed first-order multi-agent systems. The unknown part of dynamics is cancelled using radial basis neural networks. Nussbaum gains and auxiliary systems are respectively employed to overcome the unknown input direction and the saturation. Adaptive sliding mode control is used to compensate for the time-varying disturbance and the imperfect approximation of the developed neural network as well. Through Lyapunov analysis, it is shown that the overall closed-loop system maintains asymptotic stability. Finally, our approach is applied to a group of multiple single-link flexible joint manipulators to highlight better its merit.
Efficient localisation plays a vital role in many modern applications of Unmanned Ground Vehicles (UGV) and Unmanned Aerial Vehicles (UAVs), which contributes to improved control, safety, power economy, etc. The ubiquitous 5G NR (New Radio) cellular network will provide new opportunities to enhance the localisation of UAVs and UGVs. In this paper, we review radio frequency (RF)-based approaches to localisation. We review the RF features that can be utilized for localisation and investigate the current methods suitable for Unmanned Vehicles under two general categories: range-based and fingerprinting. The existing state-of-the-art literature on RF-based localisation for both UAVs and UGVs is examined, and the envisioned 5G NR for localisation enhancement, and the future research direction are explored.
This paper deals with the problem of designing a controller for a thrust-propelled vehicle which steers the vehicle to track a 3D spatial path, while effective compensation for both time-varying disturbances and uncertainties is achieved as well. Taking advantage of extraction algorithm, we separate the design for the translational and rotational dynamics. A back-stepping-based controller and a sliding mode controller are, respectively, designed for the translational and rotational dynamics in succession. The stability of the control framework is established through Lyapunov analysis. A numerical simulation is also included in the paper to render the effectiveness of the proposed control scheme.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.