© 2013 IEEE.This paper addresses the robustness of a novel two-stage super-twisting algorithm designed to converge within a prescribed time interval despite disturbances and model uncertainties. Initially, we introduce a method for tuning parameters that guarantees the algorithm's analytic solution will reach the origin precisely at a prescribed instant, assuming an unperturbed scenario. We then enhance this method to maintain prescribed-time convergence, even when faced with unknown bounded disturbances. The algorithm's performance is demonstrated through a numerical simulation of a state estimation problem for a perturbed damped pendulum. The results show that the estimation errors converge robustly to the origin at the prescribed time and remain there afterward.

© 2013 IEEE.This paper is concerned with the attitude and position control of underactuated multirotor aerial vehicles in the presence of matched disturbances and uncertainties, using the hierarchical scheme that nests the attitude control loop inside the position one. It is well-known that the effectiveness of this scheme depends on a proper control tuning for achieving a sufficient time-scale separation (TSS) between the closed-loop (faster) rotational and (slower) translational dynamics. However, a TSS cannot be ensured under an ideal sliding mode position control law since the attitude command, computed from the position control signal, is infinitely fast. The present paper tackles this problem in a way to enforce TSS without losing robustness and using a dull trial-and-error tweak of gains. That is achieved by designing, on the one hand, a new adaptive integral sliding mode attitude control law (AISMAC) that, under a sufficient smooth attitude command, ensures the existence of an attitude sliding mode during all the time, including the adaptation phase, thus allowing an infinitely fast inner loop. On the other hand, the outer loop is equipped with a disturbance-observer-based proportional-derivative position control law that ensures the required smoothness of the attitude command and provides robustness with respect to unknown force terms. The proposed design is extensively evaluated in a realistic simulator and shows to effectively enforce the TSS.

© 2023, The Author(s), under exclusive licence to Springer Nature B.V.This paper is concerned with the robust guidance and control of fully actuated multirotor aerial vehicles in the presence of moving obstacles, linear velocity constraints, and matched model uncertainties and disturbances. We address this problem by adopting a hierarchical flight control architecture consisting of a supervisory outer-loop guidance module and an inner-loop stabilizing control one. The position and attitude control laws are designed using a proportional–derivative approach combined with a high-order sliding mode disturbance observer. The resulting inner-loop control strategy is arbitrarily smooth and robust (in the sliding mode sense) with respect to model disturbances and uncertainties. On the other hand, we propose a robust collision-free guidance strategy that extends the continuous-control-obstacles method to drive the vehicle to a target pose under velocity constraints, disturbances, and uncertainties, in an environment containing moving obstacles. The overall method has been numerically evaluated and shown to be effective in providing satisfactory tracking performance, collision-free guidance, satisfaction of linear velocity constraints, and computational viability. Furthermore, it is shown to outperform an analogous scheme based on the original continuous-control-obstacles method and conventional sliding mode inner-loop control laws.

© 2023 by the authors.This paper is concerned with the robust collision-free guidance and control of underactuated multirotor aerial vehicles in the presence of moving obstacles capable of accelerating, linear velocity and rotor thrust constraints, and matched model uncertainties and disturbances. We address this problem by using a hierarchical flight control architecture composed of a supervisory outer-loop guidance module and an inner-loop stabilizing control one. The inner loop is designed using a typical hierarchical control scheme that nests the attitude control loop inside the position one. The effectiveness of this scheme relies on proper time-scale separation (TSS) between the closed-loop (faster) rotational and (slower) translational dynamics, which is not straightforward to enforce in practice. However, by combining an integral sliding mode attitude control law, which guarantees instantaneous tracking of the attitude commands, with a smooth and robust position control one, we enforce, by construction, the satisfaction of the TSS, thus avoiding the loss of robustness and use of a dull trial-and-error tweak of gains. On the other hand, the outer-loop guidance is built upon the continuous-control-obstacles method, which is incremented to respect the velocity and actuator constraints and avoid multiple moving obstacles that can accelerate. The overall method is evaluated using a numerical Monte Carlo simulation and is shown to be effective in providing satisfactory tracking performance, collision-free guidance, and the satisfaction of linear velocity and actuator constraints.

© 2023, American Institute of Aeronautics and Astronautics Inc, AIAA. All rights reserved.Real-time fluid engineering simulations require significant computational power and high-resolution grids to ensure accuracy. This paper proposes a novel CUDA-C-based simulation algorithm nemesys that leverages GPU devices to solve the Navier-Stokes equations with precision and speed. The algorithm uses a Successive Over Relaxation (SOR) iterative process on a multi-dimensional CUDA core to accelerate solving speed. The co-located Rhie and Chow interpolation scheme is applied to unstructured grids to solve the equations using an implicit finite volume method. Benchmark simulations are performed on two problems aimed to validate the effectiveness of the proposed methodology: the classical lid-driven cavity and closed-channel flow. Results exhibit a significant advantage of the proposed method in terms of convergence rate compared to state-of-the-art techniques using varying grid resolutions and Reynolds numbers. Specifically, the strategy is nearly 850 times faster than parallel CPU-based code when utilizing an RTX 3090 Nvidia graphics card. Furthermore, the algorithm's performance is investigated on an airfoil simulation, confirming the approach's effectiveness. The findings highlight that GPU-based parallel programming is a promising approach for achieving realtime simulations, and the proposed algorithm presents a significant improvement over CPU-based techniques.

© 2017 IEEE.This letter is concerned with the collision avoidance for mobile robots with uncertain dynamics in the presence of obstacles that can considerably change their velocities over time. To address this problem, we propose a robust collision-avoidance method based on the continuous-control-obstacles one. The proposed method uses an arbitrary-order overdamped low-pass filter to generate sufficiently smooth position commands for the robot and a high-order sliding mode differentiator to robustly estimate the obstacles' maximum accelerations. Based on these estimates, we define a set of possible future positions for the obstacles according to how each one is changing its velocity to calculate a robust position command for the robot. The method has been numerically evaluated using a conventional quadcopter flying among moving obstacles and has been shown to be effective in providing collision avoidance and velocity constraints satisfaction.

© 2013 IEEE.The ability of multiple manned and unmanned aircraft systems to cooperatively engage and disable an aerial threat plays a decisive role in modern warfare scenarios. In this paper, we apply key methods to enable the so-called cooperative threat engagement capability among multiple networked agents, e.g., a swarm of drones, with combat and communication capabilities. In particular, this research combines AI-based decision-making and control techniques for a swarm of loyal wingman drones to coordinate efficient defense actions in a cooperative and autonomous manner. We apply these concepts in a defense scenario that is modeled to analyze the loyal wingman concept, which we consider an interesting testbed for cooperative decision-making and low-level control techniques. The investigated methods were implemented in a realistic 3D UAV simulator for demonstration and evaluation.

© 2022 ISAThe present paper is concerned with the robust and smooth attitude-position tracking control of fully actuated multirotor aerial vehicles equipped with fixed rotors and subject to matched model uncertainties and disturbances. The vehicle coupled dynamic equations representing the translational and rotational motions are thoroughly derived using the multibody approach, considering the external torque and force disturbances as well as the uncertainties in the inertia parameters of the airframe and the rotors. From this model, it is shown that the overall disturbances and uncertainties can be lumped into an additive-matched plant-model discrepancy. Then, based on a geometrically consistent description of the control error in SE(3), a novel joint geometric attitude-position control law is designed using a multi-input smooth second-order sliding mode strategy. The latter uses a high-order sliding mode disturbance observer to guarantee the overall system robustness. The second-order sliding mode is proved to exist using vector-field homogeneity, and the tracking error is shown to exponentially converge to the origin. The method is extensively evaluated via numerical simulations using a fully actuated hexacopter with tilted rotors, showing advantages with respect to state-of-the-art alternatives.

© 2021 ISAThe present paper is concerned with the wayset-based guidance of underactuated multirotor aerial vehicles (MAVs). A hierarchical guidance and control structure is first established, in which the guidance is realized as a supervisory loop. The lower-level stabilizing attitude and position control laws are assumed to be available. On the other hand, the outer-loop guidance is designed based on a fixed-horizon tube-based robust model predictive control (MPC), which conducts the MAV to visit a given sequence of waysets, without violating their state and control bounds, and allowing the vehicle to rest in each wayset for a specified period. The MPC is designed using a reduced-order closed-loop dynamic model describing the vehicle's translation, which is derived considering the stabilizing position and attitude control laws and the assumption of a time-scale separation between the closed-loop translational and rotational dynamics. This model is put into a discrete-time linear state–space representation subject to additive bounded random disturbance and measurement noise. The properties of the proposed method, which includes the MPC recursive feasibility and robust stability as well as the overall guidance feasibility, are analytically studied. The method is also numerically evaluated using a realistic quadrotor dynamic model, showing its effectiveness and confirming its properties.

© 2022, The Author(s), under exclusive licence to The Brazilian Society of Mechanical Sciences and Engineering.The study of inverted pendulum configurations has attracted the attention of researchers during many decades. One of the main reasons is that inverted-pendulum models have the feature of approximating the dynamics of many real-world mechanisms. Therefore, this paper presents the detailed dynamic modeling and control of a novel spherical pendulum with a variable speed control moment gyroscope. The dynamic model is obtained from the generic 3D pendulum, and the necessary assumptions to model the spherical pendulum are conducted in order to avoid singularities. Furthermore, a proportional-derivative nonlinear controller based on Lyapunov theory is designed to use favorably the features of the variable speed control moment gyroscope to control the spherical pendulum combining the gyroscopic torque and the torque provided by the reaction wheel. The proposed dynamic model and nonlinear controller are evaluated through numerical simulations for two different scenarios, driving the pendulum to a sequence of attitude commands including the upright position and tracking a desired trajectory. The results have shown that the proposed model is nonsingular and that the control law has provided adequate rates controlling the pendulum in both scenarios.

© 2022, The Author(s), under exclusive licence to Springer Nature B.V.Researchers have been interested in the dynamics and control of pendulums for many decades since the mathematical models of these systems are able to represent the dynamics of real-world applications such as satellite launchers and balancing robots. This paper derives a novel multi-input global predefined-time sliding mode control strategy for the attitude control of a 3D pendulum. A different sliding variable is proposed assuring the convergence of the system to the equilibrium within a predefined time chosen by the designer in advance. Numerical simulations are carried out to evaluate the proposed controller in two different scenarios: taking the pendulum from the downward position to the upright position and tracking a sinusoidal reference. The results have shown that by using the proposed controller the system’s dynamics reaches the desired references within the predefined time, while being less conservative than other existing controllers.

© 2021 ISAThe present work is concerned with the wayset-based guidance of a very general class of fully-actuated multirotor aerial vehicles which can be equipped with fixed or vectorable rotors. The problem is tackled by means of a hierarchical guidance and control framework containing two nested loops. For the outer loop, a guidance strategy based on the nonlinear model predictive control paradigm is proposed. It steers the vehicle through a sequence of position-attitude waysets, while guaranteeing the satisfaction of the control allocation constraints. For the inner loop, a single multi-variable inverse-dynamic force–torque control law is designed to stabilize the translational and rotational dynamics, and an optimal control allocator is formulated, by means of a convex program, to distribute the required control efforts among the available actuators. The asymptotic stability of the inner and outer loop, the recursive feasibility of the guidance algorithm, as well as the feasibility of the control allocator are proved to hold. The proposed method is numerically illustrated with a quadrotor containing two-degrees-of-freedom vectorable rotors and shows to be effective to guide the vehicle while respecting all the rotor constraints.

© 2022 Elsevier Masson SASThe present work deals with the optimal control allocation of fully actuated multirotor aerial vehicles (MAVs) equipped with fixed (non-vectoring and constant-pitch) rotors. To tackle the problem, a cascaded control architecture is considered in which the control allocation is separated from the control law itself. The latter provides the resulting control efforts (three-dimensional force and torque) from the desired state trajectory, while the former is entrusted to distribute the resulting control efforts among the available actuators. The control allocation is formulated as a convex optimization problem, which, on the one hand, unifies the previous methods and, on the other hand, extends the literature by rigorously considering the rotors' dynamics and bounds, thus resulting in a novel constrained optimal control allocation algorithm suitable for quite general fixed-rotor fully actuated MAVs. Moreover, a control-allocation feasibility analysis based on the control allocator admissible set is presented. It provides a necessary and sufficient condition for the existence of a solution to the control allocation problem. We argue that this condition can be explicitly used in the design of the control law, thus improving its synergy with the control allocator. The proposed control allocation method is mathematically analyzed and widely illustrated by the computer simulation of two non-planar omnidirectional MAVs.

© 2022 ICAS. All Rights Reserved.The ability of multiple manned and unmanned aircraft systems to cooperatively engage and disable an aerial threat plays a decisive role in modern warfare scenarios. In this paper, we apply key methods to enable the so-called cooperative threat engagement capability among multiple networked agents, e.g., a swarm of drones, with combat and communication capabilities. In particular, this research combines AI-based decision-making and control techniques for a swarm of loyal wingman drones to coordinate efficient defense actions in cooperative and autonomous manner. We apply these concepts in a defense scenario, modeled to analyze the loyal wingman concept, which we consider an interesting testbed for cooperative decision-making as well as low-level control techniques. The methodologies were merged with the creation of a 3D UAV simulator to provide an application and evaluation of behavior strategies and control methods.

© 2022 IEEE.This paper is concerned with the robust guidance and control of fully actuated mobile robots subject to velocity and control constraints in dynamic environments involving external disturbances. The overall method consists of an outer-loop guidance based on the acceleration-velocity-obstacles strategy and a stabilizing control loop based on a global sliding mode policy. The guidance strategy generates velocity commands aiming to reach a target position while avoiding collision with moving obstacles and respecting velocity and acceleration bounds. On the other hand, the global sliding mode ensures that the velocity commands are, in theory, exactly tracked all the time. The proposed method is numerically evaluated using two-dimensional robots and shows to be effective.

© 2022 IEEE.The present paper proposes a novel specified-time stable second-order sliding-mode dynamic system, formulated through a modification of the super-twisting algorithm. A broader definition of finite-time stability with specified convergence time, denominated here as specified-time stability, is provided. We devise a state observer for a damped simple pendulum to test the proposed algorithm's efficacy. The simulations illustrate that the estimation errors are taken to the origin at the specified settling time, with proper choice of the observer parameters.

© 2022 IEEE.This paper is concerned with the design of a predefined-time sliding mode control law suitable for the attitude control of a quadrotor aerial vehicle. Using the Newton-Euler approach, the modeling of the rotation kinematics and dynamics of the quadrotor is formulated in terms of the control errors and put in the regular state-space form. Then, a multi-input predefined-time first-order sliding mode control law is designed so that, under reasonable conditions, the settling-time bound of the tracking error can be directly specified by a unique parameter independently of the initial conditions. The proposed control law is evaluated through numerical simulations where the results have confirmed that the tracking errors in fact converge to zero within the predefined time.

© 2017 IEEE.The present work deals with the optimal control allocation of under-Actuated multirotor aerial vehicles (UAMAVs). The problem is formulated as a convex optimization, which unifies the previous methods and extends the literature by considering the rotors' dynamics and actual bounds. A feasibility analysis based on the control allocator admissible set is presented, which provides a condition for an exact control allocation to exist. This condition can be explicitly used in the design of the control law, thus improving its synergy with the control allocator. The proposed control allocation method is numerically exemplified on an octa-rotor UAMAV.

© 1965-2011 IEEE.Due to a production error, in the original article [1], Figs. 1, 2 and 3 were incorrectly published. We apologize for this error. The correct figures, with their corresponding captions, are shown below (Figure Presented).

© 1965-2011 IEEE.This article is concerned with the robust flight control of multirotor aerial vehicles (MAVs) subject to bounded force and torque disturbances. The focus is on the entire class of MAVs containing an arbitrary even number (${\geq}4$) of fixed (not vectoring) rotors. To deal with this problem, first, a ubiquitous hierarchical control architecture in which the attitude control loop is nested inside the position control loop is adopted and augmented with a control allocator which makes the design of the control laws themselves independent of the rotor arrangement. Specially, the control allocation problem is formulated as a quadratic program that minimizes the thrust commands and accounts for the thrust range and rate bounds. Second, geometric attitude and position control laws are designed separately using a multi-input fast nonsingular terminal sliding mode control (FNTSMC) strategy, which guarantees singularity-free finite-time stability and robustness. The main contributions are, first, the augmentation of the hierarchical control scheme for extending its applicability to any fixed-rotor MAV and, second, a detailed geometric design and finite-time stability analysis of the position and attitude control loops using the FNTSMC theory. The system is evaluated on computational simulations as well as on a hardware-in-the-loop experiment, showing that it is effective, simple to implement and adjust, and reliable to operate in nonlinear regimes as well as under bounded disturbances.

Copyright © 2020 ASMEThe present work addresses the subsonic aerodynamic coefficients model for bluff ellipsoidal hulls at transitional and turbulent Reynolds number. The drag, lift, and moment aerodynamic coefficients model are based on computational fluid dynamics (CFD) simulations for four bluff ellipsoids with aspect ratio of 1, 2, 3, and 4, in the Reynolds number range of 1×103 to 2×106 and angle of attack range from 0 to 20 degrees. The Large Eddy Simulation (LES) turbulence model is used with the sub-grid turbulence model Wall-Adapting Local-Eddy Viscosity (WALE) to solve the fluid field. To reduce computational simulation time, at a first instant, the mesh is gradually refined until the point that it does not influence anymore in the final result (mesh independence). For each aerodynamic coefficient a nonlinear equation structure, valid for all the ellipsoids, is proposed as a parametric model with parameters estimated using the least mean square algorithm applied to the results of the computational fluid dynamics simulations. The proposed equations have a superior performance, in terms of precision and number of terms, when compared to polynomial equations fitted to the same data.

© 2019 ISAThe present paper is concerned with the dynamic modeling and design of control laws for a small non-rigid multi-rotor airship constituted of an oblate-spheroid helium balloon coupled with an electric-powered hexa-rotor airframe. The vehicle is assumed to operate in windless and low-speed conditions. A six-degree-of-freedom nonlinear dynamic model is derived for it using the Newton–Euler approach and considering, among other efforts, a restoring torque due to the displacement of the balloon's center of buoyancy above the vehicle's center of mass and the added-mass effect resulting from the air–structure interaction. Using the derived model and assuming a time-scale separation between the translational and rotational dynamics, the attitude and position control laws are designed separately from each other. Both laws are formulated using feedback linearization combined with control input saturation within appropriate parallelepipedal sets, which are carefully chosen to respect pre-defined bounds on the control torque, control force and maximum inclination angle. The effect of temperature and pressure fluctuations is taken into account through a parametric probabilistic approach, where Maximum Entropy Principle is used to construct a physically consistent stochastic model and Monte Carlo method is used as the stochastic solver to propagate the uncertainties through the system. Extensive simulation results show the effectiveness of the proposed control system and quantify the uncertainty of its performance over a wide range of local temperature and pressure.

© 2018 IEEE.Typical industrial applications, which can benefit from using Micro Aerial Vehicles (MAV) take place at well-controlled environments. In this case, the MAVs can rely on a fiducial system to improve their navigation based on a reliable map of the environment. In this work, we assess the use of artificial landmarks for accurate and robust visual-inertial navigation within a controlled environment. The use of artificial landmarks presents relevant advantages over techniques that assume an unknown environment. They require less processing effort and provide more robustness for dynamic and large environments. As a result, one can employ simpler, affordable platforms enabling commercially attractive applications due to cost reduction, energy efficiency, simplicity and determinism during operation. Therefore, this work presents the design and development of an accurate and efficient visual-inertial navigation system to provide feedback information allowing low and high-level control functionalities for MAV applications.

© 2018, The Brazilian Society of Mechanical Sciences and Engineering.In this work, the authors propose a formation control strategy of a group of three multirotor aerial vehicles being able to avoid multiple obstacles and collisions. To deal with this problem, a decentralized architecture is proposed which has one model predictive controller per vehicle including a set of convex constraints on the vehicle’s position to prevent collisions with other agents and different shapes of obstacles. The resulting decentralized scheme controls the formation based on a virtual structure approach. For the purpose of avoiding collisions, each local controller considers the predicted position of every neighbor vehicles. The effectiveness of the developed scheme is demonstrated through numerical simulations considering a “figure-of-eight” as the reference trajectory, and the results show its capability to handle thrust force, obstacle and collision avoidance constraints.

© 2018 ISAThe present paper is concerned with the design and experimental evaluation of optimal control laws for the nonlinear attitude dynamics of a multirotor aerial vehicle. Three design methods based on Hamilton-Jacobi-Bellman equation are taken into account. The first one is a linear control with guarantee of stability for nonlinear systems. The second and third are a nonlinear suboptimal control techniques. These techniques are based on an optimal control design approach that takes into account the nonlinearities present in the vehicle dynamics. The stability Proof of the closed-loop system is presented. The performance of the control system designed is evaluated via simulations and also via an experimental scheme using the Quanser 3-DOF Hover. The experiments show the effectiveness of the linear control method over the nonlinear strategy.

© 2017, Brazilian Society for Automatics--SBA.This paper treats the problem of position formation flight control of a group of three multirotor aerial vehicles under obstacle and collision avoidance constraints. In order to solve the problem, a distributed architecture with model predictive controllers for each vehicle includes a set of convex constraints on the vehicles’s position to prevent collisions with other vehicles and obstacles. The resulting distributed scheme controls the formation based on a virtual structure approach where the computers of the architecture exchange position data through diagrams in Simulink. The performance of the method is assessed through simulations considering that the vehicles are subject to disturbance forces and the results show the effectiveness and the ability of the control architecture to handle the obstacle and collision avoidance constraints.

© 2016, Springer Science+Business Media Dordrecht.The employment of embedded cameras in navigation and guidance of Unmanned Aerial Vehicles (UAV) has attracted the focus of many academic researches. In particular, for the multirotor UAV, the camera is widely employed for applications performed in indoor environments, where the GNSS signal is often unreliable and electromagnetic interference can be a concern. In the literature, images are mostly adopted for position and velocity estimation, rather than attitude estimation. This paper proposes an attitude determination method for multirotor aerial vehicles using pairs of vector measurements taken from a downward-facing strapdown camera. The method is composed of three modules. The first one detects and identifies the visible landmarks by processing the images. The second module computes the vector measurements related to the direction from the camera to the landmarks. The third module estimates attitude from the vector measurements. In the last module, a version of the Multiplicative Extended Kalman Filter (MEKF) with sequential update is proposed as estimation method. The overall method is evaluated via Monte Carlo simulations, showing that it is effective in determining the vehicle’s attitude and revealing its properties.

© 2016, Brazilian Society for Automatics--SBA.This paper is concerned with state estimation of discrete-time linear systems subject to additive faults represented as inputs to both the state and measurement equations. Particularly, the sequence of fault inputs is assumed to be parameterizable by three fault parameters: fault magnitude, fault instant, and fault mode index. Moreover, these parameters are treated as unknown realizations of random variables defined so as to account for prior knowledge about possible faults. For tackling this problem, a two-stage filter structure is invoked.

© 2016, Springer Science+Business Media Dordrecht.This paper presents a polynomial chaos-based framework for designing optimal linear feedback control laws for nonlinear systems with stochastic parametric uncertainty. The spectral decomposition of the original stochastic dynamical model in an orthogonal polynomial basis, prescribed by the Wiener–Askey scheme, provides a deterministic model from which the optimal linear control law is designed. Optimality of the proposed control law is proved by solving the Hamilton–Jacobi–Bellman equation, and asymptotic stability of the controlled nonlinear systems is guaranteed in the Lyapunov sense. We are especially interested in synchronization of chaotic systems. For this reason, the control strategy is applied in the trajectory tracking of periodic orbits for the Duffing oscillator and the Rössler system with uncertain stochastic parameters and initial conditions. The results are verified with Monte Carlo simulations.

© 2017, Journal of Aerospace Technology and Management. All rights reserved.The present study faces the problem of safely controlling the position trajectory of a multirotor aerial vehicle subjected to a conic constraint on the total thrust vector and a linear convex constraint on the position vector. The problem is solved using a linear state-space model predictive control strategy, whose optimization is made handy by replacing the original conic constraint set on the thrust vector by an inscribed pyramidal space, which renders a linear set of inequalities. The proposed method is evaluated on the basis of Monte Carlo simulations taking into account a random disturbance force. The simulation results show the effectiveness of the method in tracking the commanded trajectory while respecting the constraints. They also predict the effect of both the speed command and the maximum allowed inclination angle on the system performance.

© The Authors, published by EDP Sciences, 2016.This work presents the modeling and control of a multirotor aerial vehicle with tethered configuration. It is considered an octocopter with a saturated proportional-plus-derivative position control. A viscoelastic model is considered for the tether, which has a tension control. Numerical simulations are carried out to compare the performance of the tethred configuration with the vehicle in free flight.

© The Authors, published by EDP Sciences, 2016.The interest for multirotor aerial vehicles (MAVs) is currently growing due to their low cost, high manoeuvrability, simplified mechanics, capability to perform vertical take-off and landing as well as hovering flight. These characteristics make them a promising technology suitable for applications such as surveillance of indoor and urban environments. The present work faces the problem of controlling the attitude of a MAV by means of a linear feedback control which guarantees asymptotic stability when controlling nonlinear dynamics. The simulations show the effectiveness of the method.

© The Authors, published by EDP Sciences, 2016.This paper proposes a method for in-flight parameter estimation for Multirotor Aerial Vehicles (MAV). This task is important because it provides parameters with better accuracy for the actual vehicle operation. In order to simulate a flight it is adopted a simulation environment Software-In-the-Loop (SIL).

© 2016, Journal of Aerospace Technology and Management. All rights reserved.The cooperative control of small unmanned aerial vehicles such as the multicopters has been extensively investigated worldwide for functionality augmentation and cost reduction with respect to a single larger vehicle. The present paper proposes a software-in-the-loop simulation scheme for performance evaluation and demonstration of formation flight control systems of multicopters. The simulation scheme consists of a computer network where each computer simulates one of the vehicles using the MATLAB/Simulink for implementing the local control system and the X-Plane for simulating the flight dynamics and environment. For cooperation, the local control systems exchange position data by means of the network. In order to illustrate the proposed scheme, a group of 3 octocopters is taken into consideration and a leader-follower strategy is chosen for triangular position formation, with the leader moving in a straight line with constant speed.

© 2015 IEEE.Among the main sub-areas covering the cooperative control problem of Unmanned Aerial Vehicles (UAVs), formation flight has attracted great interest and has been widely investigated. The main purpose of the formation flight control is to establish a desired shape of formation for a group of vehicles by controlling the positions of each vehicle. The present paper deals with the problem of position formation flight control of a group of three multirotor helicopters with collision avoidance. In order to solve the problem, we propose a decentralized scheme based on model predictive controllers (MPC) for formation according to a virtual structure approach. For collision avoidance, a set of convex constraints on the vehicle's positions are included. The proposed method is evaluated on the basis of computational simulations considering that the vehicles are subject to disturbance forces. Simulation results show the effectiveness of the method with primary focus on treatment of anti-collision constraints.

© 2015, IFAC (International Federation of Automatic Control) Hosting by Elsevier Ltd. All rights reserved.The present paper deals with the problem of position control of a flying robot type multirotor helicopter with obstacle avoidance. In order to solve the problem, an architecture with model predictive controller (MPC) minimize the tracking error, where are implemented the inclusion of convex constraints on the position vector, making it possible to avoid obstacles with a flexible trajectory. The proposed method is evaluated on the basis of computational simulations considering that the vehicles is subject to disturbance forces. Simulation results show the effectiveness of the method related to the tracking performance with focus on the treatment of obstacle avoidance constraints.

This study applies retrospective cost adaptive control to command following in the presence of multi-variable convex input saturation constraints. To account for the saturation constraint, the authors use convex optimisation to minimise the quadratic retrospective cost function. The use of convex optimisation bounds the magnitude of the retrospectively optimised input and thereby influences the controller update to satisfy the control bounds. This technique is applied to a multi-rotor helicopter with constraints on the total thrust magnitude and inclination of the rotor plane. © The Institution of Engineering and Technology 2014.

The multirotor control system structure that has mostly been adopted is constituted by an inner and an outer control loop. In this scheme, the inner loop carries out attitude control while the outer loop is responsible for trajectory control. The present work addresses the problem of safely controlling the trajectory of a multirotor helicopter by taking into account specified constraints on both the total thrust magnitude and the inclination of the rotor plane. The proposed solution partitions the whole problem into an altitude and an horizontal position control. The control laws of the two parts combine the feedback linearization principle with saturated proportional-derivative controllers. The proposed method is evaluated by computational simulations, which show its effectiveness to control the vehicle along a spiral trajectory as well as respond to abrupt position commands. © 2013 IEEE.

This paper applies retrospective cost adaptive control (RCAC) to command following in the presence of multivariable convex input saturation constraints. To account for the satu-ration constraint, we use convex optimization to minimize the quadratic retrospective cost function. The use of convex opti-mization bounds the magnitude of the retrospectively optimized input and thereby influences the controller update to satisfy the control bounds. This technique is applied to a tiltrotor with con-straints on the total thrust magnitude and inclination of the rotor plan. Copyright © 2013 by ASME.

The design of a low cost university satellite ITASAT seeks to meet launch constraints as a secondary, piggyback payload. The dual-spin configuration has been investigated to determine the performance of the autonomous Attitude Control System (SCA) when the satellite separates from the launch vehicle in an unfavorable initial condition prior to attitude acquisition. The dual-spinner is controlled in three axes to acquire and maintain a single face pointing to the Sun by means of a momentum wheel whose rotation axis is orthogonal to that face, and a triad of air-core coil magnetotorquers that provide gyroscopic stiffness and control torques to maneuver and point the solar panel to the Sun. The SCA starts actuation as from separation, and operates in closed loop with estimates of the satellite attitude and angular velocity. These estimates are computed by an extended Kalman filter (FKE) that processes vector measurements of the Sun direction and the geomagnetic field provided by Sun sensors and a triaxial magnetometer. Starting from unfavorable initial conditions, approximately 1.5 day has been required to yield a pointing error under 10°, and less than two days to maintain the error below 0.1°. Satellite oscillations about the wheel axis have been within an acceptable margin. The duration of the maneuvers in relation to the capacity of the batteries on board have confirmed the feasibility of the dual-spin configuration. The resulting performance and complexity have been compared with those of the rigid-body spin stabilization to select an appropriate configuration for the satellite mission.

This paper is concerned with model-based isolation and estimation of additive faults in discrete-time linear Gaussian systems. The isolation problem is stated as a multiple composite hypothesis testing on the innovation sequence of the Kalman filter (KF) that considers the system operating under fault-free conditions. Fault estimation is carried out, after isolating a fault mode, by using the Maximum a Posteriori (MAP) criterion. An explicit solution is presented for both fault isolation and estimation when the parameters of the fault modes are assumed to be realizations of specific random variables (RV). © 2010 Elsevier Ltd. All rights reserved.