The study of water quality in reservoirs, lakes, and coasts is an activity that mainly uses human-crewed marine vehicles to obtain site parameters such as temperature, conductivity, salinity, pH, and others. This task is facilitated by unmanned vehicles, which improve data quality in hazardous areas and minimize human exposure. This work presents a novel methodology based on systems engineering concepts and hybrid control architecture for a catamaran-class unmanned surface vehicle (USV) named EDSON-J, for remote water quality monitoring activities with payload instrumentation. Critical aspects of the project development are considered, such as requirements, risk management, design flexibility, logical decomposition, functional classification, verification, integration and validation, and technological plan. The applied methodology proposes the main components for the vehicle, a main computer running robotic operating system (ROS) with deliberative control architecture for high-level tasks and a secondary computer running finite state machine (FSM) with hierarchical control architecture for low-level tasks, executing control and navigation algorithms. The results are given through missions of water quality monitoring, attaching a multiparameter payload sonde. Manual and automatic mode controls are suitable for circular and zig-zag maneuvers and show better performance for the proposed platform, guaranteeing the specifications and requirements of the vehicle design and validating the proposed hybrid control architecture.

Designing a controller for the cooperative transport of a payload using quadcopter-type unmanned aerial vehicles (UAVs) is a very challenging task in control theory because these vehicles are underactuated mechanical systems. This paper presents a novel robust adaptive formation control design for the cooperative transport of a suspended payload by ropes using two underactuated quadcopters in the presence of external disturbances and parametric uncertainties. The structure of the proposed controller is divided into two subsystems: fully actuated and underactuated. An integral sliding mode adaptive control strategy is proposed for the fully actuated subsystem, and for the underactuated subsystem, an adaptive control strategy based on the combination of Backstepping and sliding mode is proposed. Then, the control parameters of the sliding surfaces of both control subsystems are adaptively tuned by a neural network. In addition, to improve the robustness of the proposed controller, a disturbance observer is incorporated to estimate and compensate the lumped disturbances. The asymptotic stability of the cooperative transport system is verified with the Lyapunov theorem. Finally, numerical simulations are performed in MATLAB/Simulink environment, and the results show that the proposed controller successfully transports the payload safely and without oscillations. Moreover, the desired formation pattern is maintained throughout the flight task, even with external disturbances and parametric uncertainties.

Robot Operating System 2 (ROS2) and Micro-ROS, as advanced robotic platforms, present a potent fusion of versatility, efficiency, and scalability. While ROS 2 continues to evolve with a modular architecture and flexible communication framework, Micro-ROS provides a lightweight and efficient solution tailored for resource-constrained systems. Together, they extend the horizons of robotics across a spectrum of applications, ranging from autonomous robots to highly constrained environments, thus setting a comprehensive standard in the realm of contemporary robotic system development. In this study, we leverage the capabilities of ROS2 and Micro-ROS to realize an experimental platform designed for the development of attitude control algorithms. This platform comprises a dedicated Computer Environment Dedicated to Data Processing (CEDDP) and a module for Attitude Determination & Control System (ADCS). Our investigation entails a measurement of the response time of the CEDDP unit under both exclusive and shared network usage scenarios. Furthermore, we quantify the extent of message loss across three segments during a complete control-task cycle, under various Quality of Service (QoS) configurations. Additionally, we analyze message periodicity at four key points within the ROS2 entities participating in the system. The outcomes of our experimentation reveal a robust experimental platform built upon the ROS2 and Micro-ROS frameworks. Employing a best-effort QoS policy, along with minor adjustments to QoS profiles, emerges as an optimal approach for designing attitude control algorithms.

A testbed that simulates space conditions in a terrestrial laboratory is essential for evaluating, verifying, and teaching attitude control in nanosatellites. The control methodology applied dictates the configuration of each testbed, and highlights the need for an appropriate system for such tests. This study presents the development and validation of a spherical testbed designed to simulate the space environment, which includes a decentralized architecture ADCS module. This architecture allows for reduced time between the Model-in-the-Loop and Hardware-in-the-Loop phases, as well as facilitating high-level programming for evaluating attitude control algorithms based on reaction wheels. To validate the testbed, both point-to-point and tracking maneuvers were implemented and evaluated using the following algorithms: traditional PID control, feedback control, and a robust adaptive controller developed by Boskovic. Additionally, the system’s mathematical model was constructed, and its validity was confirmed through maximum likelihood estimation of the equation-error using the controller results. The findings demonstrate the effectiveness of this testbed, which is both extendable and accessible for evaluating reaction wheel-based attitude control algorithms. However, the study also identifies limitations and outlines directions for future work. Notably, in ground-based tests, the torques generated by gravity gradient are unknown and difficult to counteract, complicating the control of the roll and pitch axes.

This article presents a new robust formation control approach for a system of multiple Quadcopter Unmanned Aerial Vehicle (QUAV) in complex and challenging flight scenarios with large lumped uncertainties. The aim is to achieve fast convergence to the desired formation pattern, high tracking accuracy, and solid robustness. To this end, a novel finite-time nonlinear control strategy, Adaptive Backstepping Recursive Integral Non-singular Fast Terminal Sliding Mode Control (ABRINFTSMC), is designed. The formation control system of each QUAV, based on ABRINFTSMC, is divided into an underactuated position subsystem for the outer loop and a fully actuated attitude subsystem for the inner loop. A Robust Finite-Time Distributed Consensus Formation Control Protocol (RFDCFCP) is developed for the outer loop to ensure the convergence of the aircraft to the desired formation pattern in a finite time and maintain its alignment throughout the flight mission. For the inner loop, a Robust Finite-Time Attitude Stabilization Control (RFASC) is developed to allow the aircraft to track the desired attitude generated by the outer loop in a finite time. The stability of the closed-loop system is rigorously analyzed using Lyapunov theory to ensure convergence of all formation tracking errors to the origin in finite time. Finally, numerical simulations are performed under different scenarios to validate the performance of the proposed method, and a comprehensive comparative study with recent formation control approaches is carried out. The results confirm that the proposed formation control exhibits superior performance regarding fast convergence, tracking accuracy, and robustness, crucial features for multi-QUAV system flight formation.

In the aerospace field, researchers and engineers have been using attitude simulators to test and evaluate spacecraft attitude control algorithms, usually developed at the design stage. Moreover, thanks to the new technological achievements, small satellites can include more complex algorithms in their attitude determination and control systems. In consequence, the development of an attitude simulator that is able to perform different control algorithms with high attitude accuracy and stability is in high demand. In this paper, an automatic balancing method, along with a modified Model Reference Adaptive Control architecture for an uncertain dynamical system with unknown perturbation, was developed to address uncertainty suppression and disturbance rejection for an air-bearing spherical attitude simulator. The main feature of the proposed scheme consists of obtaining estimates of the offset vector generated by an unbalanced mass system in order to reduce it by moving small masses along each principal axis, ensuring stability and improving motion performance with an adaptive controller with input error modification. Simulation results were conducted according to the parameters for a small satellite 1U-class CubeSat platform inside a spherical structure.