1,067 research outputs found
Intelligent control of miniature holonomic vertical take-off and landing robot
This paper discusses the development of a fuzzy based controller for miniaturized unmanned aerial vehicle (UAV).This controller is designed to control the center-of-gravity (CoG) in a new configuration of coaxial miniaturized flying robot (MFR). The idea is to shift the CoG by controlling two pendulums located in perpendicular directions; each pendulum ends with a small mass. A key feature of this work is that the control algorithm represents the original nonlinear function that describes the dynamics of the proposed system. The controller model incorporates two cascaded subsystems: PD and PI fuzzy logic controllers. These two controllers regulate the attitude and the position of the flying robot, respectively. A model of the proposed controllers has been developed and evaluated in terms of stability and maneuverability. The results show that the presented control system can be used efficiently for the MFR applications
Robust Adaptive Learning-based Path Tracking Control of Autonomous Vehicles under Uncertain Driving Environments
This paper investigates the path tracking control
problem of autonomous vehicles subject to modelling uncertainties and external disturbances. The problem is approached
by employing a 2-degree of freedom vehicle model, which is
reformulated into a newly defined parametric form with the
system uncertainties being lumped into an unknown parametric
vector. On top of the parametric system representation, a novel
robust adaptive learning control (RALC) approach is then
developed, which estimates the system uncertainties through
iterative learning while treating the external disturbances by
adopting a robust term. It is shown that the proposed approach
is able to improve the lateral tracking performance gradually
through learning from previous control experiences, despite only
partial knowledge of the vehicle dynamics being available. It is
noteworthy that a novel technique targeting at the non-square
input distribution matrix is employed so as to deal with the
under-actuation property of the vehicle dynamics, which extends
the adaptive learning control theory from square systems to
non-square systems. Moreover, the convergence properties of
the RALC algorithm are analysed under the framework of
Lyapunov-like theory by virtue of the composite energy function
and the λ-norm. The effectiveness of the proposed control
scheme is verified by representative simulation examples and
comparisons with existing methods
A survey on fractional order control techniques for unmanned aerial and ground vehicles
In recent years, numerous applications of science and engineering for modeling and control of unmanned aerial vehicles (UAVs) and unmanned ground vehicles (UGVs) systems based on fractional calculus have been realized. The extra fractional order derivative terms allow to optimizing the performance of the systems. The review presented in this paper focuses on the control problems of the UAVs and UGVs that have been addressed by the fractional order techniques over the last decade
Discrete-time Robust PD Controlled System with DOB/CDOB Compensation for High Speed Autonomous Vehicle Path Following
Autonomous vehicle path following performance is one of significant
consideration. This paper presents discrete time design of robust PD controlled
system with disturbance observer (DOB) and communication disturbance observer
(CDOB) compensation to enhance autonomous vehicle path following performance.
Although always implemented on digital devices, DOB and CDOB structure are
usually designed in continuous time in the literature and also in our previous
work. However, it requires high sampling rate for continuous-time design block
diagram to automatically convert to corresponding discrete-time controller
using rapid controller prototyping systems. In this paper, direct discrete time
design is carried out. Digital PD feedback controller is designed based on the
nominal plant using the proposed parameter space approach. Zero order hold
method is applied to discretize the nominal plant, DOB and CDOB structure in
continuous domain. Discrete time DOB is embedded into the steering to path
following error loop for model regulation in the presence of uncertainty in
vehicle parameters such as vehicle mass, vehicle speed and road-tire friction
coefficient and rejecting external disturbance like crosswind force. On the
other hand, time delay from CAN bus based sensor and actuator command
interfaces results in degradation of system performance since large negative
phase angles are added to the plant frequency response. Discrete time CDOB
compensated control system can be used for time delay compensation where the
accurate knowledge of delay time value is not necessary. A validated model of
our lab Ford Fusion hybrid automated driving research vehicle is used for the
simulation analysis while the vehicle is driving at high speed. Simulation
results successfully demonstrate the improvement of autonomous vehicle path
following performance with the proposed discrete time DOB and CDOB structure
Navigation Control of an Automated Guided Underwater Robot using Neural Network Technique
In recent years, under water robots play an important role in various under water operations. There is an increase in research in this area because of the application of autonomous underwater robots in several issues like exploring under water environment and resource, doing scientific and military tasks under water. We need good maneuvering capabilities and a well precision for moving in a specified track in these applications. However, control of these under water bots become very difficult due to the highly non-linear and dynamic characteristics of the underwater world. The logical answer to this problem is the application of non-linear controllers. As neural networks (NNs) are characterized by flexibility and an aptitude for dealing with non-linear problems, they are envisaged to be beneficial when used on underwater robots. In this research our artificial intelligence system is based on neural network model for navigation of an Automated Underwater robot in unpredictable and imprecise environment. Thus the back propagation algorithm has been used for the steering analysis of the underwater robot when it is encountered by a left, right and front as well as top obstacle. After training the neural network the neural network pattern was used in the controller of the underwater robot. The simulation of underwater robot under various obstacle conditions are shown using MATLAB
State-of-the-Art System Solutions for Unmanned Underwater Vehicles
Unmanned Underwater Vehicles (UUVs) have gained popularity for the last decades, especially for the purpose of not risking human life in dangerous operations. On the other hand, underwater environment introduces numerous challenges in navigation, control and communication of such vehicles. Certainly, this fact makes the development of these vehicles more interesting and engineering-wise more attractive. In this paper, we first revisit the existing technology and methodology for the solution of aforementioned problems, then we try to come up with a system solution of a generic unmanned underwater vehicles
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 16’ 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 vessel’s 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 “International Regulations for Prevention of Collisions at Sea” 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
A survey on uninhabited underwater vehicles (UUV)
ASME Early Career Technical Conference, ASME ECTC, October 2-3, 2009, Tuscaloosa, Alabama, USAThis work presents the initiation of our underwater robotics research which will be focused on underwater
vehicle-manipulator systems. Our aim is to build an underwater vehicle with a robotic manipulator which has a robust system and also can compensate itself under the influence of the hydrodynamic effects. In this paper, overview of the existing underwater vehicle systems, thruster designs, their dynamic models and control architectures are given. The purpose and results of the existing methods in underwater robotics are investigated
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