scholarly journals A Drag Model-LIDAR-IMU Fault-Tolerance Fusion Method for Quadrotors

Sensors ◽  
2019 ◽  
Vol 19 (19) ◽  
pp. 4337
Author(s):  
Pin Lyu ◽  
Bingqing Wang ◽  
Jizhou Lai ◽  
Shichao Liu ◽  
Zhimin Li

In this paper, a drag model-aided fault-tolerant state estimation method is presented for quadrotors. Firstly, the drag model accuracy was improved by modeling an angular rate related item and an angular acceleration related item, which are related with flight maneuver. Then the drag model, light detection and ranging (LIDAR), and inertial measurement unit (IMU) were fused based on the Federal Kalman filter frame. In the filter, the LIDAR estimation fault was detected and isolated, and the disturbance to the drag model was estimated and compensated. Some experiments were carried out, showing that the velocity and position estimation were improved compared with the traditional LIDAR/IMU fusion scheme.

Author(s):  
Adytia Darmawan ◽  
Sanggar Dewanto ◽  
Dadet Pramadihanto

Position estimation using WIMU (Wireless Inertial Measurement Unit) is one of emerging technology in the field of indoor positioning systems. WIMU can detect movement and does not depend on GPS signals. The position is then estimated using a modified ZUPT (Zero Velocity Update) method that was using Filter Magnitude Acceleration (FMA), Variance Magnitude Acceleration (VMA) and Angular Rate (AR) estimation. Performance of this method was justified on a six-legged robot navigation system. Experimental result shows that the combination of VMA-AR gives the best position estimation.


2020 ◽  
Vol 9 (1) ◽  
pp. 7-13
Author(s):  
Marcin Uradzinski ◽  
Hang Guo

Abstract. With the continuous improvement of the hardware level of the inertial measurement unit (IMU), indoor pedestrian dead reckoning (PDR) using an inertial device has been paid more and more attention. Typical PDR system position estimation is based on acceleration obtained from accelerometers to measure the step count, estimate step length and generate the position with the heading received from angular sensors (magnetometers and gyroscopes). Unfortunately, collected signals are very responsive to the alignment of sensor devices, built-in instrumental errors and distortions from the surrounding environment. In our work, a pedestrian positioning method using step detection based on a shoe-mounted inertial unit is arranged and put to the test, and the final results are analyzed. The extended Kalman filter (EKF) provides estimation of the errors which are acquired by the XSENS IMU sensor biases. The EKF is revised with acceleration and angular rate computations by the ZUPT (zero velocity update) and ZARU (zero angular rate update) algorithms. The step detection associated with these two solutions is the perfect choice to calculate the current position and distance walked and to estimate the IMU sensors' collected errors by using EKF. The test with a shoe-mounted IMU device was performed and analyzed in order to check the performance of the recommended method. The combined PDR final results were compared to GPS/Beidou postprocessing kinematic results (outdoor environment) and to a real route which was prepared and calculated for an indoor environment. After the comparison, the results show that the accuracy of the regular-speed walking under ZUPT and ZARU combination in the case of outdoor positioning did not go beyond 0.19 m (SD) and for indoor positioning accuracy did not exceed 0.22 m (SD). The authors are conscious that built-in drift errors coming from accelerometers and gyroscopes, as well as the final position obtained by XSENS IMU, are only stable for a short time period. Based on this consideration, our future work will be focused on supporting the methods presented with radio technologies (WiFi) or image-based solutions to correct all IMU imperfections.


2021 ◽  
Vol 13 (15) ◽  
pp. 2997
Author(s):  
Zheng Zhao ◽  
Weiming Tian ◽  
Yunkai Deng ◽  
Cheng Hu ◽  
Tao Zeng

Wideband multiple-input-multiple-output (MIMO) imaging radar can achieve high-resolution imaging with a specific multi-antenna structure. However, its imaging performance is severely affected by the array errors, including the inter-channel errors and the position errors of all the transmitting and receiving elements (TEs/REs). Conventional calibration methods are suitable for the narrow-band signal model, and cannot separate the element position errors from the array errors. This paper proposes a method for estimating and compensating the array errors of wideband MIMO imaging radar based on multiple prominent targets. Firstly, a high-precision target position estimation method is proposed to acquire the prominent targets’ positions without other equipment. Secondly, the inter-channel amplitude and delay errors are estimated by solving an equation-constrained least square problem. After this, the element position errors are estimated with the genetic algorithm to eliminate the spatial-variant error phase. Finally, the feasibility and correctness of this method are validated with both simulated and experimental datasets.


2015 ◽  
Vol 2015 ◽  
pp. 1-9 ◽  
Author(s):  
Jian-wei Yang ◽  
Man-feng Dou ◽  
Zhi-yong Dai

Taking advantage of the high reliability, multiphase permanent magnet synchronous motors (PMSMs), such as five-phase PMSM and six-phase PMSM, are widely used in fault-tolerant control applications. And one of the important fault-tolerant control problems is fault diagnosis. In most existing literatures, the fault diagnosis problem focuses on the three-phase PMSM. In this paper, compared to the most existing fault diagnosis approaches, a fault diagnosis method for Interturn short circuit (ITSC) fault of five-phase PMSM based on the trust region algorithm is presented. This paper has two contributions. (1) Analyzing the physical parameters of the motor, such as resistances and inductances, a novel mathematic model for ITSC fault of five-phase PMSM is established. (2) Introducing an object function related to the Interturn short circuit ratio, the fault parameters identification problem is reformulated as the extreme seeking problem. A trust region algorithm based parameter estimation method is proposed for tracking the actual Interturn short circuit ratio. The simulation and experimental results have validated the effectiveness of the proposed parameter estimation method.


Author(s):  
Bryan R Cobb ◽  
Abigail M Tyson ◽  
Steven Rowson

This study sought to evaluate the suitability of angular rate sensors for quantifying angular acceleration in helmeted headform impacts. A helmeted Hybrid III headform, instrumented with a 3-2-2-2 nine accelerometer array and angular rate sensors, was impacted (n = 90) at six locations and three velocities (3.1, 4.9, and 6.4 m/s). Data were low-pass filtered using Butterworth four-pole phaseless digital filters which conform to the specifications described in the Society of Automotive Engineers J211 standard on instrumentation for impact tests. Nine accelerometer array data were filtered using channel frequency class 180, which corresponds to a −3 db cutoff frequency of 300 Hz. Angular rate sensor data were filtered using channel frequency class values ranging from 5 to 1000 Hz in increments of 5 Hz, which correspond to −3 db cutoff frequencies of 8 to 1650 Hz. Root-mean-square differences in peak angular acceleration between the two instrumentation schemes were assessed for each channel frequency class value. Filtering angular rate sensor data with channel frequency class values between 120 and 205 all produced mean differences within ±5%. The minimum root-mean-square difference of 297 rad/s2 was found when the angular rate sensor data were filtered using channel frequency class 175. This filter specification resulted in a mean difference of 28 ± 297 rad/s2 (1.8% ± 8.6%). Condition-specific differences (α=0.05) were observed for 11 of 18 test conditions. A total of 4 of those 11 conditions were within ±5%, and 10 were within ±10%. Furthermore, the nine accelerometer array and angular rate sensor methods demonstrated similar levels of repeatability. These data suggest that angular rate sensor may be an appropriate alternative to the nine accelerometer array for measuring angular head acceleration in helmeted head impact tests with impactor velocities of 3.1–6.4 m/s and impact durations of approximately 10 ms.


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