709 research outputs found
Nonlinear model predictive control-based guidance law for path following of unmanned surface vehicles
This work proposes a nonlinear model predictive control-based guidance
strategy for unmanned surface vehicles, focused on path following. The
application of this strategy, in addition to overcome drawbacks of previous
line-of-sight-based guidance laws, intends to enable the application of
predictive strategies also to the low-level control, responsible for tracking
the references provided by the guidance strategy. The stability and robustness
of the proposed strategy are theoretically discussed. Furthermore, given the
non-negligible computational cost of such nonlinear predictive guidance
strategy, a practical nonlinear model predictive control strategy is also
applied in order to reduce the computational cost to a great extent. The
effectiveness and advantages of both proposed strategies over other nonlinear
guidance laws are illustrated through a complete set of simulations.Comment: 21 pages, 15 figures. Postprint of the final published wor
Experimental Validation Of An Integrated Guidance And Control System For Marine Surface Vessels
Autonomous operation of marine surface vessels is vital for minimizing human errors and providing efficient operations of ships under varying sea states and environmental conditions which is complicated by the highly nonlinear dynamics of marine surface vessels. To deal with modelling imprecision and unpredictable disturbances, the sliding mode methodology has been employed to devise a heading and a surge displacement controller. The implementation of such a controller necessitates the availability of all state variables of the vessel. However, the measured signals in the current study are limited to the global X and Y positioning coordinates of the boat that are generated by a GPS system. Thus, a nonlinear observer, based on the sliding mode methodology, has been implemented to yield accurate estimates of the state variables in the presence of both structured and unstructured uncertainties. Successful autonomous operation of a marine surface vessel requires a holistic approach encompassing a navigation system, robust nonlinear controllers and observers. Since the overwhelming majority of the experimental work on autonomous marine surface vessels was not conducted in truly uncontrolled real-world environments. The first goal of this work was to experimentally validate a fully-integrated LOS guidance system with a sliding mode controller and observer using a 16â Tracker Pro Guide V-16 aluminium boat with a 60 hp. Mercury outboard motor operating in the uncontrolled open-water environment of Lake St. Clair, Michigan. The fully integrated guidance and controller-observer system was tested in a model-less configuration, whereby all information provided from the vesselâs nominal model have been ignored. The experimental data serves to demonstrate the robustness and good tracking characteristics of the fully-integrated guidance and controller/observer system by overcoming the large errors induced at the beginning of each segment and converging the boat to the desired trajectory in spite of the presence of environmental disturbances. The second focus of this work was to combine a collision avoidance method with the guidance system that accounted for âInternational Regulations for Prevention of Collisions at Seaâ abbreviated as COLREGS. This new system then needed to be added into the existing architecture. The velocity obstacles method was selected as the base to build upon and additional restrictions were incorporated to account for these additional rules. This completed system was then validated with a software in the loop simulation
Identification and Optimal Linear Tracking Control of ODU Autonomous Surface Vehicle
Autonomous surface vehicles (ASVs) are being used for diverse applications of civilian and military importance such as: military reconnaissance, sea patrol, bathymetry, environmental monitoring, and oceanographic research. Currently, these unmanned tasks can accurately be accomplished by ASVs due to recent advancements in computing, sensing, and actuating systems. For this reason, researchers around the world have been taking interest in ASVs for the last decade. Due to the ever-changing surface of water and stochastic disturbances such as wind and tidal currents that greatly affect the path-following ability of ASVs, identification of an accurate model of inherently nonlinear and stochastic ASV system and then designing a viable control using that model for its planar motion is a challenging task. For planar motion control of ASV, the work done by researchers is mainly based on the theoretical modeling in which the nonlinear hydrodynamic terms are determined, while some work suggested the nonlinear control techniques and adhered to simulation results. Also, the majority of work is related to the mono- or twin-hull ASVs with a single rudder. The ODU-ASV used in present research is a twin-hull design having two DC trolling motors for path-following motion.
A novel approach of time-domain open-loop observer Kalman filter identifications (OKID) and state-feedback optimal linear tracking control of ODU-ASV is presented, in which a linear state-space model of ODU-ASV is obtained from the measured input and output data. The accuracy of the identified model for ODU-ASV is confirmed by validation results of model output data reconstruction and benchmark residual analysis. Then, the OKID-identified model of the ODU-ASV is utilized to design the proposed controller for its planar motion such that a predefined cost function is minimized using state and control weighting matrices, which are determined by a multi-objective optimization genetic algorithm technique. The validation results of proposed controller using step inputs as well as sinusoidal and arc-like trajectories are presented to confirm the controller performance. Moreover, real-time water-trials were performed and their results confirm the validity of proposed controller in path-following motion of ODU-ASV
A Survey of path following control strategies for UAVs focused on quadrotors
The trajectory control problem, defined as making a vehicle follow a pre-established path in space, can be solved by means of trajectory tracking or path following. In the trajectory tracking problem a timed reference position is tracked. The path following approach removes any time dependence of the problem, resulting in many advantages on the control performance and design. An exhaustive review of path following algorithms applied to quadrotor vehicles has been carried out, the most relevant are studied in this paper. Then, four of these algorithms have been implemented and compared in a quadrotor simulation platform: Backstepping and Feedback Linearisation control-oriented algorithms and NLGL and Carrot-Chasing geometric algorithms.Peer ReviewedPostprint (author's final draft
Automatic Control and Routing of Marine Vessels
Due to the intensive development of the global economy, many problems are constantly emerging connected to the safety of shipsâ motion in the context of increasing marine traffic. These problems seem to be especially significant for the further development of marine transportation services, with the need to considerably increase their efficiency and reliability. One of the most commonly used approaches to ensuring safety and efficiency is the wide implementation of various automated systems for guidance and control, including such popular systems as marine autopilots, dynamic positioning systems, speed control systems, automatic routing installations, etc. This Special Issue focuses on various problems related to the analysis, design, modelling, and operation of the aforementioned systems. It covers such actual problems as tracking control, path following control, ship weather routing, course keeping control, control of autonomous underwater vehicles, ship collision avoidance. These problems are investigated using methods such as neural networks, sliding mode control, genetic algorithms, L2-gain approach, optimal damping concept, fuzzy logic and others. This Special Issue is intended to present and discuss significant contemporary problems in the areas of automatic control and the routing of marine vessels
Aerial Vehicles
This book contains 35 chapters written by experts in developing techniques for making aerial vehicles more intelligent, more reliable, more flexible in use, and safer in operation.It will also serve as an inspiration for further improvement of the design and application of aeral vehicles. The advanced techniques and research described here may also be applicable to other high-tech areas such as robotics, avionics, vetronics, and space
Underwater Vehicles
For the latest twenty to thirty years, a significant number of AUVs has been created for the solving of wide spectrum of scientific and applied tasks of ocean development and research. For the short time period the AUVs have shown the efficiency at performance of complex search and inspection works and opened a number of new important applications. Initially the information about AUVs had mainly review-advertising character but now more attention is paid to practical achievements, problems and systems technologies. AUVs are losing their prototype status and have become a fully operational, reliable and effective tool and modern multi-purpose AUVs represent the new class of underwater robotic objects with inherent tasks and practical applications, particular features of technology, systems structure and functional properties
An adaptive autopilot design for an uninhabited surface vehicle
An adaptive autopilot design for an uninhabited surface vehicle
Andy SK Annamalai
The work described herein concerns the development of an innovative approach to the
design of autopilot for uninhabited surface vehicles. In order to fulfil the requirements of
autonomous missions, uninhabited surface vehicles must be able to operate with a minimum
of external intervention. Existing strategies are limited by their dependence on a fixed
model of the vessel. Thus, any change in plant dynamics has a non-trivial, deleterious effect
on performance. This thesis presents an approach based on an adaptive model predictive
control that is capable of retaining full functionality even in the face of sudden changes in
dynamics.
In the first part of this work recent developments in the field of uninhabited surface vehicles
and trends in marine control are discussed. Historical developments and different strategies
for model predictive control as applicable to surface vehicles are also explored. This thesis
also presents innovative work done to improve the hardware on existing Springer
uninhabited surface vehicle to serve as an effective test and research platform. Advanced
controllers such as a model predictive controller are reliant on the accuracy of the model to
accomplish the missions successfully. Hence, different techniques to obtain the model of
Springer are investigated. Data obtained from experiments at Roadford Reservoir, United
Kingdom are utilised to derive a generalised model of Springer by employing an innovative
hybrid modelling technique that incorporates the different forward speeds and variable
payload on-board the vehicle. Waypoint line of sight guidance provides the reference
trajectory essential to complete missions successfully.
The performances of traditional autopilots such as proportional integral and derivative
controllers when applied to Springer are analysed. Autopilots based on modern controllers
such as linear quadratic Gaussian and its innovative variants are integrated with the
navigation and guidance systems on-board Springer. The modified linear quadratic
Gaussian is obtained by combining various state estimators based on the Interval Kalman
filter and the weighted Interval Kalman filter.
Change in system dynamics is a challenge faced by uninhabited surface vehicles that result
in erroneous autopilot behaviour. To overcome this challenge different adaptive algorithms
are analysed and an innovative, adaptive autopilot based on model predictive control is
designed. The acronym âaMPCâ is coined to refer to adaptive model predictive control that
is obtained by combining the advances made to weighted least squares during this research
and is used in conjunction with model predictive control. Successful experimentation is
undertaken to validate the performance and autonomous mission capabilities of the adaptive
autopilot despite change in system dynamics.EPSRC (Engineering and Physical Sciences Research Council
A COLLISION AVOIDANCE SYSTEM FOR AUTONOMOUS UNDERWATER VEHICLES
The work in this thesis is concerned with the development of a novel and practical collision
avoidance system for autonomous underwater vehicles (AUVs). Synergistically,
advanced stochastic motion planning methods, dynamics quantisation approaches,
multivariable tracking controller designs, sonar data processing and workspace representation,
are combined to enhance significantly the survivability of modern AUVs.
The recent proliferation of autonomous AUV deployments for various missions such
as seafloor surveying, scientific data gathering and mine hunting has demanded a substantial
increase in vehicle autonomy. One matching requirement of such missions is
to allow all the AUV to navigate safely in a dynamic and unstructured environment.
Therefore, it is vital that a robust and effective collision avoidance system should be
forthcoming in order to preserve the structural integrity of the vehicle whilst simultaneously
increasing its autonomy.
This thesis not only provides a holistic framework but also an arsenal of computational
techniques in the design of a collision avoidance system for AUVs. The
design of an obstacle avoidance system is first addressed. The core paradigm is the
application of the Rapidly-exploring Random Tree (RRT) algorithm and the newly
developed version for use as a motion planning tool. Later, this technique is merged
with the Manoeuvre Automaton (MA) representation to address the inherent disadvantages
of the RRT. A novel multi-node version which can also address time varying
final state is suggested. Clearly, the reference trajectory generated by the aforementioned
embedded planner must be tracked. Hence, the feasibility of employing the
linear quadratic regulator (LQG) and the nonlinear kinematic based state-dependent
Ricatti equation (SDRE) controller as trajectory trackers are explored.
The obstacle detection module, which comprises of sonar processing and workspace
representation submodules, is developed and tested on actual sonar data acquired
in a sea-trial via a prototype forward looking sonar (AT500). The sonar processing
techniques applied are fundamentally derived from the image processing perspective.
Likewise, a novel occupancy grid using nonlinear function is proposed for the
workspace representation of the AUV. Results are presented that demonstrate the
ability of an AUV to navigate a complex environment.
To the author's knowledge, it is the first time the above newly developed methodologies
have been applied to an A UV collision avoidance system, and, therefore, it is
considered that the work constitutes a contribution of knowledge in this area of work.J&S MARINE LT
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