Uncertainty and Disturbance Estimator-Based Robust Trajectory Tracking Control for a Quadrotor in a Global Positioning System-Denied Environment

2017 ◽  
Vol 140 (3) ◽  
Author(s):  
Qi Lu ◽  
Beibei Ren ◽  
Siva Parameswaran ◽  
Qing-Chang Zhong
Keyword(s):  
Global Positioning System ◽  
Trajectory Tracking ◽  
Tracking Control ◽  
Position Estimation ◽  
Accurate Estimation ◽  
Positioning System ◽  
Trajectory Tracking Control ◽  
Global Positioning ◽  
Uncertainty And Disturbance Estimator ◽  
Disturbance Estimator

This paper addresses the problem of autonomous trajectory tracking control for a quadrotor in a global positioning system (GPS)-denied environment using only onboard sensing. To achieve that goal, it requires accurate estimation of quadrotor states followed by proper control actions. For the position estimation in a GPS-denied environment, an open source high speed optical flow sensor PX4FLOW is adopted. As for the quadrotor control, there are several challenges due to its highly nonlinear system dynamics, such as underactuation, coupling, model uncertainties, and external disturbances. To deal with those challenges, the cascaded inner–outer uncertainty and disturbance estimator (UDE)-based robust control scheme has been developed and applied to the attitude and position control of a quadrotor. Extensive real flight experiments, including attitude stabilization, hover, disturbance rejection, trajectory tracking, and comparison with the proportional–integral–derivative (PID) controller are carried out to demonstrate the effectiveness of the developed UDE-based controllers.

scholarly journals Indoor Positioning System Based on Global Positioning System Signals with Down- and Up-Converters in 433 MHz ISM Band

Sensors ◽  
2021 ◽  
Vol 21 (13) ◽  
pp. 4338
Author(s):  
Abdulkadir Uzun ◽  
Firas Abdul Ghani ◽  
Amir Mohsen Ahmadi Najafabadi ◽  
Hüsnü Yenigün ◽  
İbrahim Tekin
Keyword(s):  
Global Positioning System ◽  
Indoor Positioning ◽  
Position Estimation ◽  
Line Of Sight ◽  
Positioning System ◽  
Gps Receiver ◽  
Ism Band ◽  
Global Positioning ◽  
Indoor Positioning System ◽  
Non Line Of Sight

In this paper, an indoor positioning system using Global Positioning System (GPS) signals in the 433 MHz Industrial Scientific Medical (ISM) band is proposed, and an experimental demonstration of how the proposed system operates under both line-of-sight and non-line-of-sight conditions on a building floor is presented. The proposed method is based on down-converting (DC) repeaters and an up-converting (UC) receiver. The down-conversion is deployed to avoid the restrictions on the use of Global Navigation Satellite Systems (GNSS) repeaters, to achieve higher output power, and to expose the GPS signals to lower path loss. The repeaters receive outdoor GPS signals at 1575.42 MHz (L1 band), down-convert them to the 433 MHz ISM band, then amplify and retransmit them to the indoor environment. The front end up-converter is combined with an off-the-shelf GPS receiver. When GPS signals at 433 MHz are received by the up-converting receiver, it then amplifies and up-converts these signals back to the L1 frequency. Subsequently, the off-the-shelf GPS receiver calculates the pseudo-ranges. The raw data are then sent from the receiver over a 2.4 GHz Wi-Fi link to a remote computer for data processing and indoor position estimation. Each repeater also has an attenuator to adjust its amplification level so that each repeater transmits almost equal signal levels in order to prevent jamming of the off-the-shelf GPS receiver. Experimental results demonstrate that the indoor position of a receiver can be found with sub-meter accuracy under both line-of-sight and non-line-of-sight conditions. The estimated position was found to be 54 and 98 cm away from the real position, while the 50% circular error probable (CEP) of the collected samples showed a radius of 3.3 and 4 m, respectively, for line-of-sight and non-line-of-sight cases.

Production prediction of conventional and global positioning system–based earthmoving systems using simulation and multiple regression analysis

2008 ◽  
Vol 35 (6) ◽  
pp. 574-587 ◽  
Author(s):  
Seungwoo Han ◽  
Taehoon Hong ◽  
Sangyoub Lee
Keyword(s):  
Regression Analysis ◽  
Multiple Regression Analysis ◽  
Multiple Regression ◽  
Global Positioning System ◽  
Appropriate Technology ◽  
Accurate Estimation ◽  
Positioning System ◽  
Construction Technology ◽  
Unit Costs ◽  
Global Positioning

Accurate estimation of construction production, which is composed of productivity and unit costs, allows construction planners and managers to have excellent control over current processes and to correctly predict the production of similar projects in the future. Due to the need for accurate production estimation, selection of the appropriate construction technology is a critical factor in the success of a project. This paper presents a methodology for developing a model capable of predicting productivity and unit costs using several procedures, such as actual data collection, input data generation using construction simulation, and multiple regression analysis. An earthmoving operation was analyzed to estimate the proposed methodology’s prediction of construction production. A global positioning system (GPS)–based earthmoving system was selected as the new construction technology to be compared with the conventional system, to evaluate the decision-making process at a jobsite. The proposed methodology is expected to provide users with a basis for selecting appropriate technology. The case study presented in this paper demonstrates how to utilize the proposed methodology and analyze its predicted results.

scholarly journals A system level implementation of wavelet based filtering for GNSS signals

2021 ◽  
Author(s):  
Jorge Leon
Keyword(s):  
Wavelet Analysis ◽  
Global Positioning System ◽  
Cross Correlation ◽  
Position Estimation ◽  
System Level ◽  
Positioning System ◽  
Wavelet Filter ◽  
Detail Design ◽  
Global Positioning ◽  
Multipath Errors

A project is presented to study the Global Positioning System and learn how to apply wavelet analysis to mitigate the effects of multipath errors on GNSS signals. The analysis is carried out using the SystemC language to demonstrate how one may try to implement the GPS signal wavelet filter in hardware. Wavelet analysis, the SystemC library and additional tools are discussed in detail. Design issues such as control signaling and position estimation are explained. System evaluation is performed at two levels, one using cross correlation of signals and the second by measuring the amount of clustering in position plots.

scholarly journals A system level implementation of wavelet based filtering for GNSS signals

2021 ◽  
Author(s):  
Jorge Leon
Keyword(s):  
Wavelet Analysis ◽  
Global Positioning System ◽  
Cross Correlation ◽  
Position Estimation ◽  
System Level ◽  
Positioning System ◽  
Wavelet Filter ◽  
Detail Design ◽  
Global Positioning ◽  
Multipath Errors

A project is presented to study the Global Positioning System and learn how to apply wavelet analysis to mitigate the effects of multipath errors on GNSS signals. The analysis is carried out using the SystemC language to demonstrate how one may try to implement the GPS signal wavelet filter in hardware. Wavelet analysis, the SystemC library and additional tools are discussed in detail. Design issues such as control signaling and position estimation are explained. System evaluation is performed at two levels, one using cross correlation of signals and the second by measuring the amount of clustering in position plots.

Normal Deceleration Behavior of Passenger Vehicles at Stop Sign–Controlled Intersections Evaluated with In-Vehicle Global Positioning System Data

2005 ◽  
Vol 1937 (1) ◽  
pp. 120-127 ◽  
Author(s):  
Jun Wang ◽  
Karen K. Dixon ◽  
Hainan Li ◽  
Jennifer Ogle
Keyword(s):  
Global Positioning System ◽  
Accurate Estimation ◽  
Positioning System ◽  
Data Set ◽  
Passenger Vehicles ◽  
Stop Sign ◽  
Global Positioning ◽  
System Data ◽  
Deceleration Time ◽  
Maximum Deceleration

Deceleration characteristics of passenger cars are often used in traffic simulation, vehicle fuel consumption and emissions models, and intersection and deceleration-lane design. Most previous studies collected spot speed data with detectors or radar guns. Because of the limitations of the data collection methods, these studies could not determine when and where drivers began to decelerate. Therefore, the studies may not provide an accurate estimation of deceleration time and distance. Furthermore, most previous studies are based on outdated and limited data, and their conclusions may not be applicable to the current vehicle fleet and drivers. The normal deceleration behavior of current passenger vehicles is evaluated at stop sign–controlled intersections on urban streets on the basis of in-vehicle Global Positioning System data. This study determined that drivers with higher approach speeds decelerated over a longer time and distance. Higher initial deceleration rates were also associated with higher approach speeds. However, the collected data in this study did not indicate a clear relationship between the average and maximum deceleration rates and approach speeds. With second-by-second deceleration profile data, the authors found that most drivers reached their maximum deceleration rates about 5 s or less than 5 s before stopping, and the maximum deceleration rate (3.4 m/s2) recommended by AASHTO was applicable to most of the study drivers. This review verified several previous deceleration models with the current observations and found that the polynomial model developed by Akcelik and Biggs provides the best fit for the data set in this study. Finally, this study developed a new deceleration model based on the approach speeds and deceleration time.

scholarly journals Metabolic Power Method: Underestimation of Energy Expenditure in Field-Sport Movements Using a Global Positioning System Tracking System

2016 ◽  
Vol 11 (8) ◽  
pp. 1067-1073 ◽  
Author(s):  
Darcy M. Brown ◽  
Dan B. Dwyer ◽  
Samuel J. Robertson ◽  
Paul B. Gastin
Keyword(s):  
Energy Expenditure ◽  
Global Positioning System ◽  
Tracking System ◽  
Exercise Session ◽  
Gps Tracking ◽  
Accurate Estimation ◽  
Positioning System ◽  
Metabolic Power ◽  
Global Positioning ◽  
Global Positioning System Tracking

The purpose of this study was to assess the validity of a global positioning system (GPS) tracking system to estimate energy expenditure (EE) during exercise and field-sport locomotor movements. Twenty-seven participants each completed a 90-min exercise session on an outdoor synthetic futsal pitch. During the exercise session, they wore a 5-Hz GPS unit interpolated to 15 Hz and a portable gas analyzer that acted as the criterion measure of EE. The exercise session was composed of alternating 5-minute exercise bouts of randomized walking, jogging, running, or a field-sport circuit (×3) followed by 10 min of recovery. One-way analysis of variance showed significant (P < .01) and very large underestimations between GPS metabolic power– derived EE and oxygen-consumption (VO2) -derived EE for all field-sport circuits (% difference ≈ –44%). No differences in EE were observed for the jog (7.8%) and run (4.8%), whereas very large overestimations were found for the walk (43.0%). The GPS metabolic power EE over the entire 90-min session was significantly lower (P < .01) than the VO2 EE, resulting in a moderate underestimation overall (–19%). The results of this study suggest that a GPS tracking system using the metabolic power model of EE does not accurately estimate EE in field-sport movements or over an exercise session consisting of mixed locomotor activities interspersed with recovery periods; however, is it able to provide a reasonably accurate estimation of EE during continuous jogging and running.

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