Multi-sensor fusion in Kalman-filter for high performance force sensing

2011 ◽  
Author(s):  
Thao Tran Phuong ◽  
Chowarit Mitsantisuk ◽  
Kiyoshi Ohishi
Keyword(s):  
Kalman Filter ◽  
Sensor Fusion ◽  
High Performance ◽  
Force Sensing

scholarly journals High-performance Load Torque Compensation of Industrial Robot using Kalman-filter-based Instantaneous State Observer

2015 ◽  
Vol 4 (5) ◽  
pp. 589-590 ◽  
Author(s):  
Takashi Yoshioka ◽  
Thao Tran Phuong ◽  
Akinori Yabuki ◽  
Kiyoshi Ohishi ◽  
Toshimasa Miyazaki ◽  
...  
Keyword(s):  
Kalman Filter ◽  
High Performance ◽  
Industrial Robot ◽  
State Observer ◽  
Load Torque

scholarly journals Asynchronous Sensor Fusion using Multi-rate Kalman Filter

2014 ◽  
Vol 63 (11) ◽  
pp. 1551-1558 ◽  
Author(s):  
Young Seop Son ◽  
Wonhee Kim ◽  
Seung-Hi Lee ◽  
Chung Choo Chung
Keyword(s):  
Kalman Filter ◽  
Sensor Fusion

Parameter Estimation in a Hydrostatic System Using Extended Kalman Filter

2001 ◽  
Author(s):  
Yuvin A. Chinniah ◽  
Richard Burton ◽  
Saeid Habibi
Keyword(s):  
Kalman Filter ◽  
Bulk Modulus ◽  
Extended Kalman Filter ◽  
High Performance ◽  
State Space Model ◽  
System Response ◽  
Actuation System ◽  
Accuracy And Precision ◽  
Hydrostatic System ◽  
Entrained Air

Abstract In this paper, the Extended Kalman Filter (EKF) estimation technique is applied to a novel hydrostatic actuation system referred to as the Electrohydraulic Actuator (EHA). A state space model of the EHA is developed and the effective bulk modulus is estimated in simulation. The EHA is a high performance actuation system capable of moving large loads with very high accuracy and precision. In a practical situation, this parameter is very difficult to measure directly as it depends on entrained air which cannot be known at a particular point of time. The bulk modulus is critical for system response and a low bulk modulus as a result of air in the system can seriously hinder the performance of EHA and cause safety problems.

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