TRAJECTORY CONTROL AND ITS APPLICATION TO APPROACH A TARGET: PART I. DEVELOPMENT OF TRAJECTORY CONTROL ALGORITHMS FOR AN AUTONOMOUS VEHICLE

2002 ◽  
Vol 45 (4) ◽  
Author(s):  
T. Takigawa ◽  
L. Sutiarso ◽  
M. Koike ◽  
H. Kurosaki ◽  
H. Hasegawa
Keyword(s):  
Autonomous Vehicle ◽  
Trajectory Control ◽  
Control Algorithms

Hardware-in-the-Loop Platform for Testing Autonomous Vehicle Control Algorithms

2019 ◽  
Author(s):  
Jani Erik Heikkinen ◽  
Salimzhan Gafurov ◽  
Sergey Kopylov ◽  
Tatiana Minav ◽  
Sergey Grebennikov ◽  
...  
Keyword(s):  
Autonomous Vehicle ◽  
Vehicle Control ◽  
Control Algorithms ◽  
Hardware In The Loop

Smart Autodriver Algorithm for Real-Time Autonomous Vehicle Trajectory Control

2020 ◽  
pp. 1-12
Author(s):  
Sina Milani ◽  
Hamid Khayyam ◽  
Hormoz Marzbani ◽  
William Melek ◽  
Nasser L. Azad ◽  
...  
Keyword(s):  
Real Time ◽  
Autonomous Vehicle ◽  
Trajectory Control ◽  
Vehicle Trajectory ◽  
Time Autonomous

System identification of flybar-less rotorcraft UAV

2020 ◽  
Vol 92 (10) ◽  
pp. 1483-1493
Author(s):  
Khadeeja Nusrath T.K. ◽  
Lulu V.P. ◽  
Jatinder Singh
Keyword(s):  
Stability Analysis ◽  
System Identification ◽  
Degrees Of Freedom ◽  
Autonomous Vehicle ◽  
Model Identification ◽  
Control Algorithms ◽  
Small Scale ◽  
Content Type ◽  
Statistical Measures ◽  
Instrumented Vehicle

Purpose This paper aims to build an accurate mathematical model which is necessary for control design and attitude estimation of a miniature unmanned rotorcraft and its subsequent conversion to an autonomous vehicle. Design/methodology/approach Frequency-domain system identification of a small-size flybar-less remote controlled helicopter is carried out based on the input–output data collected from flight tests of the instrumented vehicle. A complete six degrees of freedom quasi-steady dynamic model is derived for hover and cruise flight conditions. Findings The veracity of the developed model is ascertained by comparing the predicted model responses to the actual responses from flight experiments and from statistical measures. Dynamic stability analysis of the vehicle is carried out using eigenvalues and eigenvectors. The identified model represents the vehicle dynamics very well in the frequency range of interest. Research limitations/implications The model needs to be augmented with additional terms to represent the high-frequency dynamics of the vehicle. Practical implications Control algorithms developed using the first principles model can be easily reconfigured using the identified model, because the model structure is not altered during identification. Originality/value This paper gives a practical solution for model identification and stability analysis of a small-scale flybar-less helicopter. The estimated model can be easily used in developing control algorithms.

scholarly journals Integrated Mobile Robotic Platform Model

2021 ◽  
Vol 31 (4) ◽  
pp. 609-627
Author(s):  
Mikhail V. Chugunov ◽  
Irina N. Polunina ◽  
Alexander G. Divin ◽  
Aleksandra A. Generalova ◽  
Artem A. Nikulin ◽  
...  
Keyword(s):  
Solid Mechanics ◽  
Trajectory Control ◽  
Control Algorithms ◽  
Multi Agent System ◽  
Agricultural Machinery ◽  
Robotic Platform ◽  
Agent System ◽  
Model Control ◽  
Multi Agent ◽  
Software And Hardware

Introduction. The “Smart Agroˮ committee of Research and Education Center “Engineering of the Future” has identified a number of tasks relevant for improving the efficiency of precision, soil-protecting and conservation agriculture. One of these tasks is the development of a digital multi-agent system, which provides a number of services for agricultural enterprises, developers and manufacturers of agricultural machinery. The purpose of the present study is to model an autonomous mobile robotic platform, including the development of software and hardware for trajectory control. Materials and Methods. To solve the problem, there are used modern CAx systems and their applications, the methods of 3D and full-body modeling, and the method of numerical solution of problems in solid mechanics. To expand and improve the standard functionality of CAx-systems (SolidWorks) in the software implementation of trajectory control algorithms, the methods and technologies of programming using API SolidWorks, VisualStudio C++ (MFC, ATL, COM) are used, and to build physical full-scale models ‒ Arduino and fischertechnik platforms. Results. The result of the study is a software and hardware module of trajectory control for an integrated (physical and virtual) model of a mobile robotic platform, which can be provided to the consumer as a service for technology autonomation. For the developed integrated model, control algorithms for various types of trajectories were tested. Discussion and Conclusion. The developed integrated software and hardware model of trajectory control can be used by developers and manufacturers of agricultural machinery, and directly by agro-enterprises for implementing typical technological processes. A feature of the implementation is an open hardware and software interface that provides the integration of mobile robotic platforms based on a digital multi-agent system.

scholarly journals PD CONTROLLER BASED UNMANNED SHIP NAVIGATION

2017 ◽  
Vol 5 (4RACEEE) ◽  
pp. 147-154
Author(s):  
Adinath Jain ◽  
Hari Prasad ◽  
Sujata Dahal ◽  
Rajesh Sudi
Keyword(s):  
Computation Time ◽  
Open Loop ◽  
Trajectory Control ◽  
Pid Controllers ◽  
Control Algorithms ◽  
Adaptive Controllers ◽  
Wave Disturbances ◽  
Unmanned Ship ◽  
Standard Models ◽  
Predictive Controllers

For the improvement of the performance of track keeping of unmanned water vehicle numerous ship models, wave disturbances models and distinct control algorithms has been proposed. Researchers are using variants of PID controllers, Adaptive controllers and Predictive controllers for accurate trajectory control. Being simpler in nature still PID controller are popular in control domain. In this paper we have implemented PD based controller for trajectory control of unmanned vehicle considering all standard models of sea disturbances. Analysis of result obtained using PD control proved that path tracking is more accurate than open loop controller in terms of computation time, complexity and fuel consumption.

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