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The technology of hydrodynamic modeling and marine craft motion control systems has progressed greatly in recent years. This timely survey includes the latest tools for analysis and design of advanced guidance, navigation and control systems and presents new material on underwater vehicles and surface vessels. Each section presents numerous case studies and applications, providing a practical understanding of how model-based motion control systems are designed.

This paper presents a passivity based formation control strategy for multiple unmanned aerial vehicles (UAVs) cooperatively carrying a suspended load. The control strategy we propose consists of an internal feedback control law for each UAV and a formation control law that regulates the relative position between each UAV. We show that under this control strategy the interconnected system has a continuum of equilibria and prove stability for all equilibrium points where the cables supporting the suspended load are in tension. This is a submitted manuscript of an article published by Elsevier Ltd in IFAC-PapersOnLine, 18 October 2017.

There exist numerous navigation solutions already implemented into various navigation systems. Depending on the vehicle in which the navigation system is used, it can be distinguished in most cases among; navigation, tactical, and commercial grade categories of such systems. The core of these systems is formed by inertial sensors, i.e. accelerometers and angular rate sensors/gyros. Navigation and tactical grade systems commonly rely on fiber optic/ring laser gyros and servo/quartz accelerometers with high resolution, sensitivity, and stability. In the case of cost-effective navigation systems, for example piloted light and ultralight aircraft, usually use commercial grade sensors, where the situation differs. The sensor outputs are less stable and sensitive, and suffer from manufacturing limits leading to temperature dependency, bias instability, and misalignment which introduces non-negligible disturbances. These conditions commonly limit the applicability of the navigation solution since its stand-alone operation using free integration of accelerations and angular rates is not stable. This paper addresses a cost-effective solution with commercial grade inertial sensors, and studies the performance of different approaches to obtain navigation solution with robustness to GNSS outages. A main goal of this paper is thus comparison of a nonlinear observer and two extended Kalman filter solutions with respect to the accuracy of estimated quantities and their sensitivity to GNSS outages. The performance analyses are carried out on real flight data and evaluated during phases of the flight when the solutions are challenged by different environmental disturbances.

A global nonlinear algebraic transform of nonlinear pseudorange measurement equations enables navigation solutions based on a globally valid linear time-varying measurement model. Using an interconnection of a nonlinear attitude observer and a translational motion observer based on pseudorange and range–range measurements, a tightly coupled integrated aided inertial navigation system is designed. The attitude observer uses a proper acceleration estimate from the translational motion observer as a reference vector for the accelerometer measurement. This leads to a feedback interconnection that is shown to be globally exponentially stable under some conditions on the tuning parameters. The model transformation has eliminated the information about a certain nonlinear relationship that exists among the measurements. While this enables the global solution to be found, it also leads to loss of estimation accuracy when there is measurement noise. In order to recover close-to-optimal (minimum variance) estimates, the observer estimates are only used to generate a locally linearized time-varying model that is subsequently employed by a Kalman filter, without loss of global convergence.

The estimation of a vehicle's position and velocity based on measurements of pseudoranges and range-rates is a nonlinear filtering problem. We utilize a linearized Kalman filter with global convergence that avoids divergence because the local model linearization is not based on the linearized Kalman filter's own estimates. Instead, the linearization is made about the estimates of another suboptimal Kalman filter that is based on a globally valid quasi-linear time-varying measurement model.

This paper presents an exponentially stable nonlinear wind velocity observer for fixed-wing unmanned aerial vehicles (UAVs). The observer uses a model of the aircraft combined with a GNSS-aided inertial navigation system (INS). The INS uses an attitude observer together with a pitot static probe measuring dynamic pressure in the longitudinal direction as well as the airspeed. The observer is able to estimate the wind velocity and from this compute the relative velocity, which directly contains information about the angle of attack (AOA) and sideslip angle (SSA). The nonlinear observer is also able to estimate the scaling factor of the pitot static probe measurement and there are no requirements on persistence of excitation (PE) of the UAV maneuvers. The computational footprint is smaller than the conventional Kalman filter, which makes the algorithm well suited for embedded systems. The designed observer is proven exponentially stable under stable flight and through simulations it is verified that the estimates converge to the true values of a realistic wind velocity when there are no model errors.

We conduct full-scale experimental validation and comparison of three different nonlinear attitude observers, two of them with inherent heave estimation, in two different operational scenarios encountered by an offshore vessel in the North Sea. Two different micro-electro-mechanical inertial measurement units are the primary sensors for driving the nonlinear observers, which are aided by gyrocompasses and position reference systems. The results are compared with data from well-proven industry standard vertical reference units.

Dead reckoning capabilities are vital in ship navigation if position and heading references are unrealizable or lost. In safety critical marine operations such as dynamic positioning, the International Maritime Organization and classification societies require that the vessel possesses dead reckoning capabilities and position reference redundancy. In this paper, we conduct a full-scale experimental validation and comparison of the dead reckoning capabilities using two different high-rate and low-cost micro-electro-mechanical inertial measurement units. The full-scale experimental validation is achieved with two nonlinear observers, aided by gyrocompasses and position reference systems, in a dynamic positioning operation carried out by an offshore vessel in the North Sea. The dead reckoning performance is evaluated after ten minutes without aiding from position reference system measurements.

Launch and recovery phases pose significant challenges to the operation of UAVs, in particular, for fixed-wing UAVs operating from smaller ships or other geographically or operationally constrained sites without a proper runway. Although UAV missions can often be operated autonomously under pilot supervision via telemetry, the launch and recovery phases often require piloting by using manual remote control (RC) and the pilot's visual feedback. Availability of reliable automatic recovery functionality with predictable performance is an important step towards increased autonomy that could potentially lead to reduced operating costs (no need for a skilled RC pilot) and improved safety records and thereby enable increased use of UAVs.

Summary We present a direct and an indirect nonlinear adaptive path-following controller for marine craft based on a line-of-sight guidance principle used by ancient navigators. The control laws are implemented using hydro-acoustic relative velocity measurements as opposed to absolute velocity measurements. For this purpose, a kinematic model for relative velocity in amplitude-phase form is derived. The first contribution is an adaptive indirect controller based on a disturbance observer designed for estimation and compensation of ocean currents. The equilibrium points of the cross-track and parameter estimation errors are proven to be globally κ exponentially stable. This guarantees that the estimated drift term converges to its true value exponentially. The observer is used in conjuncture with a control law to obtain asymptotic tracking and path following in the presence of ocean currents. The second contribution is a direct adaptive integral line-of-sight controller for path following. Global convergence of the cross-track error is proven by using Barbalat's lemma, which ensures that the parameter estimation error is bounded. Both methods can be applied to the horizontal-plane motion of surface vessels and autonomous underwater vehicles. An autonomous underwater vehicle case study is included to verify the results. Copyright © 2015 John Wiley & Sons, Ltd.

A ship's roll dynamics is very sensitive to changes in the loading conditions and a worst-case scenario is the loss of stability. This paper proposes an approach for online estimation of a ship's ...

A ship's roll dynamics is sensitive to the mass and mass distribution. Changes in these physical properties might introduce unpredictable behavior of the ship and a worst-case scenario is that the ship will capsize. In this paper, a recently proposed approach for online estimation of mass and center of mass is validated using experimental data. The experiments were performed using a scale model of a ship in a wave basin. The data were collected in free run experiments where the rudder angle was recorded and the ship's motion was measured using an inertial measurement unit. The motion measurements are used in conjunction with a model of the roll dynamics to estimate the desired properties. The estimator uses the rudder angle measurements together with an instrumental variable method to mitigate the influence of disturbances. The experimental study shows that the properties can be estimated with quite good accuracy but that variance and robustness properties can be improved further.

This paper deals with the construction of nonlinear observers for navigation purposes. We first present a globally exponentially stable observer for attitude and gyro bias, based on gyro measurements and two or more pairs of vector measurements. We avoid the well-known topological obstructions to global stability by not confining the attitude estimate to SO ( 3 ) , but rather estimating a full rotation matrix with nine degrees of freedom. We also show how the attitude can be estimated under a relaxed persistency-of-excitation condition, with a single vector measurement as a special case. Next, we use the attitude observer to construct a globally exponentially stable observer for gnss/ins integration, based on accelerometer, gyro, and magnetometer measurements, as well as gnss measurements of position and (optionally) velocity. We verify the stability properties of the design using experimental data from a light fixed-wing aircraft.

The control algorithm hierarchy of motion control for over-actuated mechanical systems with a redundant set of effectors and actuators commonly includes three levels. First, a high-level motion control algorithm commands a vector of virtual control efforts (i.e. forces and moments) in order to meet the overall motion control objectives. Second, a control allocation algorithm coordinates the different effectors such that they together produce the desired virtual control efforts, if possible. Third, low-level control algorithms may be used to control each individual effector via its actuators. Control allocation offers the advantage of a modular design where the high-level motion control algorithm can be designed without detailed knowledge about the effectors and actuators. Important issues such as input saturation and rate constraints, actuator and effector fault tolerance, and meeting secondary objectives such as power efficiency and tear-and-wear minimization are handled within the control allocation algorithm. The objective of the present paper is to survey control allocation algorithms, motivated by the rapidly growing range of applications that have expanded from the aerospace and maritime industries, where control allocation has its roots, to automotive, mechatronics, and other industries. The survey classifies the different algorithms according to two main classes based on the use of linear or nonlinear models, respectively. The presence of physical constraints (e.g input saturation and rate constraints), operational constraints and secondary objectives makes optimization-based design a powerful approach. The simplest formulations allow explicit solutions to be computed using numerical linear algebra in combination with some logic and engineering solutions, while the more challenging formulations with nonlinear models or complex constraints and objectives call for iterative numerical optimization procedures. Experiences using the different methods in aerospace, maritime, automotive and other application areas are discussed. The paper ends with some perspectives on new applications and theoretical challenges.

When trying to capture the heaving motion of a marine vessel in waves, conventional position references such as global navigation satellite systems fall short in many cases. Because of design and satellite geometry, the vertical position measurement is typically inferior in both accuracy and precision compared to its horizontal counterparts. For aiding an inertial navigation system (INS), using conventional vertical position references may therefore be suboptimal. This article presents an alternative algorithm utilizing a virtual vertical reference (VVR) concept, based on the mean sea level, to aid the INS. The novelty of the algorithm arises where the VVR concept is augmented with an error model, used to improve the heave estimation performance. The motion of the vessel is estimated using an INS, employing a feedback-interconnected observer framework, based on nonlinear theory. The INS, using low-cost micro-electro-mechanical-system-based inertial measurement units, provides position, velocity and attitude in a dead-reckoning fashion, and is aided by a horizontal position reference, the VVR, and a compass to prevent the estimates from drifting. The estimation performance obtained with the observer structure is evaluated using Monte Carlo simulations and compared to preceding results. The algorithm is also validated experimentally and compared to an industry standard vertical reference unit using data collected on board an offshore vessel. © 2017. This is the authors’ accepted and refereed manuscript to the article. LOCKED until 16.10.2018 due to copyright restrictions. This manuscript version is made available under the CC-BY-NC-ND 4.0 license http://creativecommons.org/licenses/by-nc-nd/4.0/

In this paper, we consider the problem of trajectory tracking of a multirotor Unmanned Aerial Vehicle carrying a suspended payload. The movement of the suspended payload influences the dynamics of the multirotor, which must be appropriately handled by the controller to achieve satisfactory tracking results. We derive a mathematical model of the interconnected multi-body system using Kane’s equations, and develop a non-linear tracking controller based on the backstepping technique. In addition to suppressing the effects of the swinging payload, the controller also compensates for an unknown constant wind disturbance. The origin of the tracking error is proven UGAS (Uniformly Globally Asymptotically Stable) and ULES (Uniformly Locally Exponentially Stable) through Lyapunov analysis. To reduce the swing motion of the suspended load, a nominal swing-free path is generated through open loop shaping filters, then further perturbed through a delayed feedback approach from measured load deflection angles to achieve robustness. The proposed controller structure is verified by simulations and experiments. © Springer Science+Business Media Dordrecht 2017. This is a post-peer-review, pre-copyedit version of the article, locked until 2 March 2018 due to copyright restrictions. The final authenticated version is available online at: http://dx.doi.org/10.1007/s10846-017-0509-6

Navigation is a term with broad usage in everyday life and can mean the act of moving, moving through an unknown environment, ascertaining a craft's position, or even browsing on the Internet. Originally, the term meant the skill of sailing a ship, in particular steering and maneuvering, and is derived from the Latin words navis and agere, meaning "ship" and "to drive." The modern field of study of navigation in a scientific context usually relates to the ascertainment or determination of position, velocity, and orientation of some object relative to a reference point and is used for all type of crafts and vehicles, such as aircraft, ships, submarines, and cars. © 2017 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works.

In this paper, we study the path-following problem for marine craft which are unactuated in the sway dynamics. The proposed control law is derived using the method of least squares to find an approximate solution of overdetermined systems. The controller adjusts the speed according to the distance to the path and the rate of convergence while it stabilizes the unactuated dynamics. We show the circumstances under which the proposed controller achieves path following. The origin of the error dynamics is proven to be globally asymptotically and locally exponentially stable.

In this work we have designed a signal based K-exponentially stable frequency estimator for the estimation of the wave encounter frequency at sea. The frequency estimator under consideration is a second-order filter designed for the estimation of the frequency of a sinusoid with unknown amplitude, frequency, and phase. The wave encounter frequency is estimated using measurements of the roll angle of the ship. The frequency estimator is able to estimate the frequency correctly when the ship is experiencing parametric roll resonance and when the resonance has damped out. The frequency estimator is therefore fitted with a switching gain in the frequency adaptation law. A stability proof is provided for the estimator with switching gain. The effectiveness of the designed estimator is demonstrated in a simulation study. In this simulation study we use a roll angle measurement generated by a second-order model of ship's roll dynamics. The frequency estimator is validated using experimental data.

Marine craft employing a dynamic positioning system rely on measurements from numerous position reference systems in order to maintain the craft's desired position during operation. Faults in such systems pose a serious risk. In particular, slowly emerging faults are difficult to detect and can result in vessel drive-offs, that may in turn have dire consequences. An inertial measurement unit may provide independent position and orientation information, provided that the attitude estimates of the observer are sufficiently accurate. In this paper a three-stage nonlinear observer, based on strapdown inertial measurement units aided by a position reference system with uniform semiglobal exponential stability properties, is posed. The design includes lever arm compensation of position references. Fault detection is achieved with established methodology. Simulations show that this design has the potential to detect slowly emerging position reference faults.

Ship-based Unmanned Aerial Vehicle (UAV) operations represent an important field of research which enables a large variety of mission types. Most of these operations demand a high level of endurance which normally requires the use of a fixed-wing UAV. Traditionally, a net located on the ship deck is used for recovering the fixed-wing UAV. However, there are numerous challenges when attempting autonomous landings in such environments. Waves will induce heave motion, and turbulence near the ship will make approaches challenging. In this paper, we present a concept using multirotor UAVs to move the recovery operation off the ship deck. To recover the fixed-wing UAV, a net is suspended below two coordinated multirotor UAVs which can synchronize the movement with the fixed-wing UAV. The approach trajectory can be optimized with respect to the wind direction, and turbulence caused by the ship can be avoided. In addition, the multirotor UAVs can transport the net at a certain speed along the trajectory of the fixed-wing UAV, thus decreasing the relative velocity between the net and fixed-wing UAV to reduce the forces of impact. This paper proves the proposed concept through a simulation study and a preliminary control system architecture.

In this paper, using the idea of integrator backstepping, a dynamic controller is designed for two-dimensional path maneuvering of underactuated marine craft. The geometric errors are explicitly considered in the design procedure and convergence to the path is guaranteed. The marine craft converges to the path at the expense of sacrificing the speed assignment task when the craft moves off the path. Moreover, the unactuated dynamics is demonstrated to be globally bounded. The effectiveness of the method is verified by performing simulations.

This paper demystifies how ocean currents together with wind and wave loads influence the marine craft equations of motion. In the literature there exists great confusion of the use of absolute and relative velocity terms when modeling rigid-body and hydrodynamic forces. The article is useful for engineers who want to simulate and predict the motions of marine craft exposed to wind, wave and ocean currents as well as control engineers evaluating the performance of marine craft control systems. The results are also very useful for testing and tuning of integral action time constants for compensation of ocean current and 2nd-order wave-induced drift forces.

A simple nonlinear model for variable pitch wind turbines is described. The model is aimed specifically at nonlinear control design and analysis. We propose a parametric model and subsequently describe a method to determine the parameters for any turbine that falls into the scope of the model. The result is a model that describes a turbine rotor, which is free to move in all six degrees of freedom. This freedom is required to model the new breed of floating offshore turbines. The resulting model is compared to experimental data with good results. Cyclic forces at large yaw offsets are not modeled well, however. Limitations of the model are discussed.

This paper presents a modified version of a well known line-of-sight (LOS) guidance algorithm for path-following. The proposed method employs a time-varying equation for the lookahead distance which depends on the cross-track error. A sliding mode controller is designed in order to stabilize the vehicle heading angle to the desired value specified by the guidance system. The guidance system along with the controller form a cascaded structure which is shown to be globally κ-exponentially stable when the control task is to converge to a straight line. The effectiveness of the proposed strategy is demonstrated by simulations indicating that the variable lookahead distance algorithm can contribute to obtaining a diminished oscillatory behavior around the desired path.

An efficient potential flow solver is applied to marine vessel path-planning for cluttered environments. The approach is computationally light. This is achieved by employing a simplified potential flow solution as well as generating the path online. The method relies on a simple guidance law that; (A)Regulates a target point to maintain a constant stream-function value, (B)Employ rudder control to steer a vessel towards this target. The utility of potential flow for path-planning is discussed. Simulation results are presented, showing the promise of the above approach.

Parametric roll is a dangerous resonance phenomenon for ships caused by time-varying restoring forces. The resulting large roll oscillations may endanger the ship's safety and possibly lead to capsizing. The susceptibility of container ships to parametric roll resonance has caused considerable research activities in the development of control and operational strategies to avoid large roll motions. In this paper, a novel approach to the active control of ships experiencing parametric roll resonance is presented. The methodology of extremum seeking control is used to iteratively determine the set-point for the wave encounter frequency in order to avoid the conditions for the onset and build-up of parametric roll. The desired trajectory for the wave encounter frequency is tracked by mapping it to the ship speed and heading angle by a control allocation, formulated as a constrained optimization problem, and consequently by implementing speed and heading controllers. The combined variation of the speed and heading angle is shown to efficiently drive the ship out of the parametric roll resonance region.

In this article, we have described the main components of a ship motion-control system and two particular motion-control problems that require wave filtering, namely, dynamic positioning and heading autopilot. Then, we discussed the models commonly used for vessel response and showed how these models are used for Kalman filter design. We also briefly discussed parameter and noise covariance estimation, which are used for filter tuning. To illustrate the performance, a case study based on numerical simulations for a ship autopilot was considered. The material discussed in this article conforms to modern commercially available ship motion-control systems. Most of the vessels operating in the offshore industry worldwide use Kalman filters for velocity estimation and wave filtering. Thus, the article provides an up-to-date tutorial and overview of Kalman-filter-based wave filtering.

Ship-to-ship operations, such as underway replenishment (UNREP), lightering, etc., entail potentially hazardous situations due to the possibility of collisions between two ships operating in close proximity. In order to ensure safe joint operations with collision avoidance, knowledge of the hydrodynamic interaction loads between the two vessels is highly advantageous. This paper thus considers the hydrodynamic interaction effects between two advancing ships and their maneuvering behaviors in calm water during typical replenishment operations. For this purpose, a unified seakeeping and maneuvering model of two interacting ships based on a two-time scales and modular concept relevant for calm water is employed. The maneuvering module is based on generalized slender-body theory, while calm-water interaction forces and moments between the two ships are estimated using Newman-Tuck theory. Automatic steering and speed control algorithms for both ships are also employed to achieve high-precision and collision-free UNREP maneuvers, which is illustrated through a numerical simulation involving the well-known “ESSO OSAKA’ and “MARINER’ models from the ship literature.

In this paper a robotic approach is taken to develop a dynamic nonlinear model of an offshore pipeline installation. A compact dynamic representation of the pipe and its kinematics, for effective implementation in a computer code is developed. The pipe model is used in simulations to compute the dynamic tension from the pipe on the vessel. The pipe tension is commonly computed by quasi-static methods based on the catenary equation, which lack the dynamic behavior and flexural effects of the pipe. The model can also replace computationally slower finite element models in applications with real-time requirements. The model is suitable for many applications, such as real-time decision support, training simulators, motion prediction systems, Hardware-In-the-Loop (HIL) testing, operability analysis, control applications and pre-design of ships.

In this paper, the implementation of genetic programming (GP) to design a controller structure is assessed. GP is used to evolve control strategies that, given the current and desired state of the propulsion and heading dynamics of a supply ship as inputs, generate the commanded forces required to maneuver the ship. The controllers created using GP are evaluated through computer simulations and real maneuverability tests in a laboratory water basin facility. The robustness of each controller is analyzed through the simulation of environmental disturbances. In addition, GP runs in the presence of disturbances are carried out so that the different controllers obtained can be compared. The particular vessel used in this paper is a scale model of a supply ship called CyberShip II. The results obtained illustrate the benefits of using GP for the automatic design of propulsion and navigation controllers for surface ships.

A propeller with a rudder can produce a thrust vector within a range of directions and magnitudes in the horizontal plane for low-speed maneuvering and dynamic positioning. The set of attainable thrust vectors is non-convex because significant lift can be produced by the rudder only with forward thrust. It is suggested to decompose the attainable thrust region into a finite union of convex polyhedral sets and a mixed-integer-like convex quadratic programming formulation of the optimal control allocation problem for marine vessels with any number of rudders as well as thrusters and other propulsion devices is derived. Actuator rate and position constraints are explicitly taken into account. Using multi-parametric quadratic programming software, an explicit piecewise linear representation of the least-squares optimal control allocation law is pre-computed. It can therefore be implemented with low computational complexity and high software reliability without the use of real-time optimization. The method is illustrated using a scale model ship in a basin.

A nonlinear observer for estimation of the longitudinal velocity, lateral velocity, and yaw rate of a vehicle, designed for the purpose of vehicle side-slip estimation, is modified and extended in order to work for different road surface conditions. The observer relies on a road-tire friction model and is therefore sensitive to changes in the adhesion characteristics of the road surface. The friction model is parametrized with a single friction parameter, and an update law is designed. The adaptive observer is proven to be uniformly globally asymptotically stable and uniformly locally exponentially stable under a persistency-of-excitation condition and a set of technical assumptions, using results related to Matrosov's theorem. The observer is tested on recorded data from two test vehicles and shows good results on a range of road surfaces.

This paper considers the subject of straight-line target tracking for unmanned surface vehicles (USVs). Target-tracking represents motion control scenarios where no information about the target behavior is known in advance, i.e., the path that the target traverses is not defined apriori. Specifically, this work presents the design of a motion control system which enables an underactuated USV to track a target that moves in a straight line at high speed. The motion control system employs a guidance principle originally developed for interceptor missiles, as well as a novel velocity controller inspired by maneuverability and agility concepts found in fighter aircraft literature. The performance of the suggested design is illustrated through full-scale USV experiments in the Trondheimsfjord.

An essential ability of autonomous unmanned surface vessels (USVs) and autonomous underwater vehicles (AUVs) moving in a horizontal plane is to follow a general two-dimensional path in the presence of unknown ocean currents. This paper presents a method to achieve this. The proposed guidance and control system only requires absolute velocity measurements for feedback, thereby foregoing the need for expensive sensors to measure relative velocities. The closed-loop system consists of a guidance law and an adaptive feedback linearizing controller combined with sliding mode, and is shown to render the path cross-track error dynamics UGAS and USGES. Simulation results are presented to verify the theoretical results. © 2017 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works.”

A two-dimensional path following control system for autonomous marine surface vessels is presented. The guidance system is obtained through a way-point guidance scheme based on line-of-sight projection algorithm and the speed controller is achieved through state feedback linearization. A new approach concerning the calculation of a dynamic line-of-sight vector norm is presented which main idea is to improve the speed of the convergence of the vehicle to the desired path. The results obtained are compared with the traditional line-of-sight scheme. It is intended that the complete system will be tested and implemented in a model of the “Esso Osaka” tanker. The results of simulations are presented here showing the effectiveness of the system aiming in to be robust enough to perform tests either in tanks or lakes.

A thrust estimation scheme for a marine propeller has been experimentally tested in waves and with a device that simulates the influence of a vessel hull. The scheme is formed by a nonlinear propeller torque observer and a mapping to generate the thrust from the observed torque. The mapping includes the estimation of the advance number. This is utilized to improve the performance when the propeller is lightly loaded. The advance speed is assumed to be unknown, and only measurements of shaft speed and motor torque have been used. Accurate results have been obtained in experimental tests.

The motion of marine vessels has traditionally been studied using two different approaches: manoeuvring and seakeeping. These two approaches use different reference frames and coordinate systems to describe the motion. This paper derives the kinematic models that characterize the transformation of motion variables (position, velocity, accelerations) and forces between the different coordinate systems used in these theories. The derivations hereby presented are done in terms of the formalism adopted in robotics. The advantage of this formulation is the use of matrix notation and operations. As an application, the transformation of linear equations of motion used in seakeeping into body-fixed coordinates is considered for both zero and forward speed.

In this paper a recently reported four-quadrant nonlinear thrust controller for marine propellers is applied to the velocity control of an underwater vehicle. The controller, designed for fixed pitch electrically driven propellers, is based on a shaft speed control and employs an estimate of the propeller torque loss. A simulation study is performed in order to compare the presented approach with the conventional shaft speed and torque propeller controllers.

This paper considers employing missile guidance concepts to design motion control systems for marine craft. Initially, classical concepts such as line of sight (LOS), pure pursuit (PP), and constant bearing (CB) are reviewed. Subsequently, the relationship of these concepts to motion camouflage strategies in nature is pointed out, as well as their application to robot manipulators. Ultimately, the CB guidance scheme is used to design a motion control system for fully actuated marine surface craft. For this purpose, the notion of asymptotic interception becomes fundamental, as the motion control goal is not to hit a physical target in finite time, but to hit a virtual target asymptotically. A modular control design inspired by backstepping and cascade theory results in a classical inner-outer loop guidance and control structure.

In this paper, we present a cooperative control strategy for a team of multirotor type UAVs to lift a suspended payload. The interconnected system is modeled by the Udwadia-Kalaba equations of constrained motion. A robust path-following controller is developed for each vehicle in the system, and coordination is achieved through synchronization of the path parameterization. Stability of the interconnected system consisting of a network of local path-following controllers is analyzed. Results are verified by numerical simulations.

This paper describes a nonlinear controller for following references generated by a Line-of-Sight (LOS) guidance algorithm. Good performance is achieved even in disturbed conditions without integral action by controlling the vehicle's course instead of heading. A cascaded system architecture is employed and a uniform semiglobal exponential stability (USGES) proof is presented. Software-in-the-loop simulation results support the theoretical conclusions.

Marine craft employing a dynamic positioning system rely on measurements from position reference systems and gyrocompasses, and faults in these systems and sensors pose a serious risk of vessel drive-offs, that may in turn have dire consequences. An inertial measurement unit may provide independent position and orientation information, provided that the attitude estimates of the observer in use are accurate enough. In this paper we compare three nonlinear strapdown inertial-measurement-unit-based attitude estimators aided by global navigation satellite systems, and put them to test in a simulation of two fault detection and isolation scenarios. The comparison finds that all attitude estimators under test have the potential for use in a fault detection and isolation scheme.

This paper considers the control of a multirotor-type unmanned aerial vehicle (UAV) with a suspended load. The load is modeled as a pendulum, with a rigid link. We consider the case when the suspended load is connected to the centre of gravity of the UAV, and the interconnected system is modeled by Kane's method. A nonlinear controller based on the backstepping technique is derived, that ensures trajectory tracking of the UAV regardless of the pendulum motion. The origin of the tracking error is proved to be globally asymptotically stable, and results are verified by simulations.

It is proposed to estimate wind velocity, Angle-Of-Attack (AOA) and Sideslip Angle (SSA) of a fixed-wing Unmanned Aerial Vehicle (UAV) using only kinematic relationships with a Kalman Filter (KF), avoiding the need to know aerodynamic models or other aircraft parameters. Assuming that measurements of airspeed and attitude of an UAV are available as inputs, a linear 4th order time-varying model of the UAV's longitudinal speed and the 3-D wind velocity is used to design a Kalman-filter driven by a GNSS velocity measurement airspeed sensor. An observability analysis shows that the states can be estimated along with an airspeed sensor calibration factor provided that the flight maneuvers are persistently exciting, i.e. the aircraft changes attitude. The theoretical analysis of the KF shows that global exponential stability of the estimation error is achieved under these conditions. The method is tested using experimental data from three different UAVs, using their legacy autopilot to provide basic estimates of UAV velocity and attitude. The results show that convergent estimates are achieved with typical flight patterns indicating that excitation resulting from the environment and normal flight operation is sufficient. Wind velocity estimates correlate well with observed winds at the ground. The validation of AOA and SSA estimates is preliminary, but indicate some degree of correlation between the AOA estimate and vertical accelerometer measurements, as would be expected since lift force can be modeled as a linear function of AOA in normal flight.

In order to achieve a high degree of operational flexibility, it is often required to recover small UAVs without infrastructure such as a runway. To help overcome this difficulty, deep stall landing can be used as a landing method on small space. The UAV is in a deep stall when the angle of attack is beyond the stall angle, and the condition causes the UAV to loose height rapidly. In the post-stall phase the angle of attack is controlled and the UAV can land with relatively low speed. In this article we focus on the highly non-linear longitudinal dynamics, and employ a non-linear model predictive control (MPC) to find a control sequence to guide a model of a fixed-wing UAV into a deep stall to land at a given location and given path angle with minimum speed.

A system for autonomous precision recovery of fixedwing unmanned aerial vehicles (UAVs) using low-cost GPS L1 C/A based RTK (Real-Time Kinematic) solution utilizing locally generated corrections is described and field tested. We present a system architecture which includes the setup of the hardware and software for the onboard GPS receiver, base-station, differential link, computers running open-source carrier-phase positioning software, roll-stabilized GPS-antenna, dedicated flight control algorithms for the final approach, and their integration with the ArduPilot open-source autopilot in the small X8 UAV (flying-wing). Experimental results show proof-of-concept field tests where the prototype implementation has been used for recovery in a stationary recovery net.

Nonlinear observers for estimation of lateral and longitudinal velocity of automotive vehicles are proposed. The observers are based on a sensor suite that is standard in many new cars, consisting of acceleration and yaw rate measurements in addition to wheel speed and steering angle measurements. Two approaches are considered: first, a modular approach where the estimated longitudinal velocity is used as input to the observer for lateral velocity, and second, a combined approach where all states are estimated in the same observer. Both approaches use a tire-road friction model, which is assumed to be known. It is also assumed that the road is flat. Stability of the observers is proven in the form of input-to-state stability of the observer error dynamics, under a structural assumption on the friction model. The assumption on the friction model is discussed in detail, and the observers are validated on experimental data from cars.

This paper presents a method for formation control of marine surface craft inspired by Lagrangian mechanics. The desired formation configuration and response of the marine surface craft are given as a set of constraint functions. The functions are treated according to constraints in analytical mechanics. Thus, constraint forces arise and feedback from the constraint functions keeps the formation assembled. Since the constraint functions are designed for a desired effect, the forces can be interpreted as control laws. Examples of constraint functions that maintain a formation are presented. Furthermore, the same approach has been applied with no major modification to position control purposes for a single vessel. An extension to underactuated vessels is given. Simulations with nonlinear models of tugboats illustrate the proposed method versatility and its robustness with respect to environmental disturbances and time delays