Performance Comparison of Extended Kalman Filter and Unscented Kalman Filter for the Control Moment Gyroscope Inverted Pendulum

2017 ◽  
Author(s):  
Jyot R. Buch ◽  
Yogendra P. Kakad ◽  
Yawo H. Amengonu
Keyword(s):  
Kalman Filter ◽  
Extended Kalman Filter ◽  
Inverted Pendulum ◽  
Unscented Kalman Filter ◽  
Performance Comparison ◽  
Control Moment Gyroscope ◽  
Control Moment

Real-Time Signal Denoising Algorithm in Wheel Force Transducer

2014 ◽  
Vol 615 ◽  
pp. 244-247
Author(s):  
Dong Wang ◽  
Guo Yu Lin ◽  
Wei Gong Zhang
Keyword(s):  
Kalman Filter ◽  
Real Time ◽  
Extended Kalman Filter ◽  
Unscented Kalman Filter ◽  
Force Transducer ◽  
Time Signal ◽  
Signal Denoising ◽  
Observation Function ◽  
Simulation Results ◽  
Wheel Force Transducer

The wheel force transducer (WFT) is used to measure dynamic wheel loads. Unlike other force sensors, WFT is rotating with the wheel. For this reason, the outputs and the inputs of the transducer are nonlinearly related, and traditional Kalman Filter is not suitable. In this paper, a new real-time filter algorithm utilizing Quadrature Kalman Filter (QKF) is proposed to solve this problem. In Quadrature Kalman Filter, Singer model is introduced to track the wheel force, and the observation function is established for WFT. The simulation results illustrate that the new filter outperforms the traditional Unscented Kalman Filter (UKF) and Extended Kalman Filter (EKF).

scholarly journals Extraction and Filter Algorithm of Guidance Information for Full-strapdown Seeker on Rotation Missile

2018 ◽  
Vol 214 ◽  
pp. 03008 ◽  
Author(s):  
YongShan Liu ◽  
Li Song ◽  
JingLong Li
Keyword(s):  
Kalman Filter ◽  
Extended Kalman Filter ◽  
Simple Structure ◽  
Unscented Kalman Filter ◽  
High Reliability ◽  
Engineering Application ◽  
Line Of Sight ◽  
Light Weight ◽  
Rate Information ◽  
Guidance Information

Strapdown seekers are superior to platform seekers for their simple structure, high reliability and light weight but cannot measure the line-of-sight angle rate information for the guidance of rotation missile directly. This paper aims at the engineering application of full-strapdown seekers on rotation missile problem. Firstly, a line-of-sight angle rate solution model is established. Based on the MATLAB, the extended Kalman filter (EKF) algorithm and unscented Kalman filter (UKF) algorithm are used to estimate the line-of-sight angle rate information of the full-strapdown seekers. The results show that using EKF filter and UKF filter both can obtain effective guidance information and the UKF’s effect is better.

scholarly journals A New Linear Regression Kalman Filter with Symmetric Samples

Symmetry ◽  
2021 ◽  
Vol 13 (11) ◽  
pp. 2139
Author(s):  
Xiuqiong Chen ◽  
Jiayi Kang ◽  
Mina Teicher ◽  
Stephen S.-T. Yau
Keyword(s):  
Kalman Filter ◽  
Linear Regression ◽  
Particle Filter ◽  
Normal Distribution ◽  
Extended Kalman Filter ◽  
Nonlinear Filtering ◽  
Unscented Kalman Filter ◽  
Standard Normal Distribution ◽  
Leibler Divergence ◽  
Standard Normal

Nonlinear filtering is of great significance in industries. In this work, we develop a new linear regression Kalman filter for discrete nonlinear filtering problems. Under the framework of linear regression Kalman filter, the key step is minimizing the Kullback–Leibler divergence between standard normal distribution and its Dirac mixture approximation formed by symmetric samples so that we can obtain a set of samples which can capture the information of reference density. The samples representing the conditional densities evolve in a deterministic way, and therefore we need less samples compared with particle filter, as there is less variance in our method. The numerical results show that the new algorithm is more efficient compared with the widely used extended Kalman filter, unscented Kalman filter and particle filter.

scholarly journals Fault Diagnosis of PMSG Stator Inter-Turn Fault Using Extended Kalman Filter and Unscented Kalman Filter

Energies ◽  
2020 ◽  
Vol 13 (11) ◽  
pp. 2972 ◽  
Author(s):  
Waseem El Sayed ◽  
Mostafa Abd El Geliel ◽  
Ahmed Lotfy
Keyword(s):  
Kalman Filter ◽  
Fault Diagnosis ◽  
Extended Kalman Filter ◽  
Continuous Monitoring ◽  
Unscented Kalman Filter ◽  
Fault Tolerant ◽  
Synchronous Generator ◽  
Operating Conditions ◽  
Practical Implementation ◽  
Complete Failure

Since the permeant magnet synchronous generator (PMSG) has many applications in particular safety-critical applications, enhancing PMSG availability has become essential. An effective tool for enhancing PMSG availability and reliability is continuous monitoring and diagnosis of the machine. Therefore, designing a robust fault diagnosis (FD) and fault tolerant system (FTS) of PMSG is essential for such applications. This paper describes an FD method that monitors online stator winding partial inter-turn faults in PMSGs. The fault appears in the direct and quadrature (dq)-frame equations of the machine. The extended Kalman filter (EKF) and unscented Kalman filter (UKF) were used to detect the percentage and the place of the fault. The proposed techniques have been simulated for different fault scenarios using Matlab®/Simulink®. The results of the EKF estimation responses simulation were validated with the practical implementation results of tests that were performed with a prototype PMSG used in the Arab Academy For Science and Technology (AAST) machine lab. The results showed impressive responses with different operating conditions when exposed to different fault states to prevent the development of complete failure.

Performance Comparison of Inertial Measurement Units Fused With Odometry in Extended Kalman Filter for Dead-Reckoning Navigation

2019 ◽  
Author(s):  
Kevin Carey ◽  
Benjamin Abruzzo ◽  
David P. Harvie ◽  
Christopher Korpela
Keyword(s):  
Kalman Filter ◽  
Extended Kalman Filter ◽  
Autonomous Vehicle ◽  
Dead Reckoning ◽  
Ground Truth ◽  
Performance Comparison ◽  
Inertial Measurement Units ◽  
Ground Vehicle ◽  
Inertial Measurement ◽  
Measurement Units

Abstract This paper aims to aid robot and autonomous vehicle designers by providing a comparison between four different inertial measurement units (IMUs) which could be used to aid in vehicle navigation in a GPS-denied or inertial-only scenario. A differential-drive ground vehicle was designed to carry the multiple different IMUs, mounted coaxially, to enable direct comparison of performance in a planar environment. The experiments focused on the growth of pose error of the ground vehicle originating from the odometry senors and the IMUs. An extended Kalman Filter was developed to fuse the odometry and inertial measurements for this comparison. The four specific IMUs evaluated were: CNS 5000, Xsens 300, Microstrain GX5-35, and Phidgets 1044 and the ground truth for experiments was provided by an Optitrack motion capture system (MCS). Finally, metrics for choosing IMUs, merging cost and performance considerations, are proposed and discussed. While the CNS 5000 has the best objective error specifications, based on these metrics the Xsens 300 exhibits the best absolute performance while the Phidgets 1044 provides the best performance-per-dollar.

Gyroscopic Stabilization of a Self-Balancing Robot Bicycle

2011 ◽  
Vol 5 (6) ◽  
pp. 916-923 ◽  
Author(s):  
Pom Yuan Lam ◽  
◽  
Tan Kian Sin
Keyword(s):  
Nonlinear System ◽  
Inverted Pendulum ◽  
Experimental Results ◽  
Design And Development ◽  
Control Moment Gyroscope ◽  
Control Moment ◽  
Gyroscopic Stabilization ◽  
Balancing Robot

This paper reports the design and development of a self-balancing bicycle using off-the-shelf electronics. A self-balancing bicycle is an unstable nonlinear system similar to an inverted pendulum. Experimental results show the robustness and efficiency of the proportional plus derivative controller balancing the bicycle. The system uses a control moment gyroscope as an actuator for balancing.

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