Real-time force control for servo-hydraulic actuator systems using adaptive time series compensator and compliance springs

2017 ◽  
Vol 47 (4) ◽  
pp. 854-871 ◽  
Author(s):  
Yunbyeong Chae ◽  
Ramin Rabiee ◽  
Abdullah Dursun ◽  
Chul-Young Kim
Keyword(s):  
Time Series ◽  
Real Time ◽  
Force Control ◽  
Hydraulic Actuator ◽  
Adaptive Time

A Real Time Controlled Test Rig for High Bandwidth Force Control

2014 ◽  
Author(s):  
Alessandro Bertucci ◽  
Andrea Mornacchi ◽  
Giovanni Jacazio ◽  
Massimo Sorli
Keyword(s):  
Real Time ◽  
Force Control ◽  
Medium Size ◽  
Feedback Signal ◽  
Model Parameters ◽  
Hydraulic Actuator ◽  
Critical Feature ◽  
Velocity Signal ◽  
Stability Margins ◽  
High Bandwidth

This paper describes an electronically controlled active force control system developed to test the tail rotor actuator of a new medium size helicopter. As for all hydraulic force control systems, the critical control issue is to mitigate the disturbance generated by the actuator velocity. For this particular case, the problem was accrued by the high bandwidth of the tail rotor actuator. To define the optimum control algorithm a model based approach was followed, estimating, when unable to measure directly, mechanical and hydraulic model parameters with a dedicated experimental campaign. A controller was eventually developed able to cope with the severe dynamic disturbances by introducing velocity and acceleration compensation laws. The controller was then implemented in a high recursion rate real time machine interfacing with a servovalve controlling the flow to a hydraulic actuator provided with hydrostatic bearings to minimize the friction force. The actuator force was sensed by a load cell providing the feedback signal for the force servoloop. A critical feature of the control was the need to develop a dedicated complex filter for the velocity signal able to cancel out the signal noise while allowing to retain the correct real time information of the actuator velocity and maintain adequate stability margins.

A Mechatronic Active Force Control System for Real Time Test Loading of an Aircraft Landing Gear

2009 ◽  
Author(s):  
Giovanni Jacazio ◽  
Gualtiero Balossini
Keyword(s):  
Control System ◽  
Real Time ◽  
Force Control ◽  
Landing Gear ◽  
High Rate ◽  
Active Force ◽  
Hydraulic Actuator ◽  
Active Force Control ◽  
Complex Adaptive ◽  
Force Control System

This paper describes an electronically controlled active force control system that was recently developed to provide real time loading for the tests of a landing gear. As the landing gear moves during the test, a force is generated on the landing gear in order to ensure that its dynamics is identical to that that would occur during its operation in an actual flight. Since landing gear deployment and retraction can occur at different environmental and flight conditions, the load profile that must be developed by the force control system depends on the simulated flight condition and is determined by an appropriate landing gear model. To attain accurate force control, a system was setup comprised of a servovalve controlled hydraulic actuator, force and position sensors, and a high rate digital controller implementing a complex adaptive control law. An excellent accuracy of the load control was eventually achieved for all load profiles occurring on the landing gear.

Model of multicomponent narrow-band periodical non-stationary random signal

2020 ◽  
Vol 2020 (48) ◽  
pp. 17-24
Author(s):  
I.M. Javorskyj ◽  
◽  
R.M. Yuzefovych ◽  
P.R. Kurapov ◽  
◽  
...  
Keyword(s):  
Time Series ◽  
Real Time ◽  
Hilbert Transform ◽  
Spectral Properties ◽  
Narrow Band ◽  
Analytic Signal ◽  
Random Signal ◽  
Hilbert Transformation ◽  
The Hilbert Transform

The correlation and spectral properties of a multicomponent narrowband periodical non-stationary random signal (PNRS) and its Hilbert transformation are considered. It is shown that multicomponent narrowband PNRS differ from the monocomponent signal. This difference is caused by correlation of the quadratures for the different carrier harmonics. Such features of the analytic signal must be taken into account when we use the Hilbert transform for the analysis of real time series.

A Polishing Robot Force Control System Based on Time Series Data in Industrial Internet of Things

2021 ◽  
Vol 21 (2) ◽  
pp. 1-22
Author(s):  
Chen Zhang ◽  
Zhuo Tang ◽  
Kenli Li ◽  
Jianzhong Yang ◽  
Li Yang
Keyword(s):  
Time Series ◽  
Control System ◽  
Force Control ◽  
Time Series Data ◽  
Industrial Robot ◽  
Industrial Robots ◽  
Series Data ◽  
Industrial Internet Of Things ◽  
Industrial Internet ◽  
Force Control System

Installing a six-dimensional force/torque sensor on an industrial arm for force feedback is a common robotic force control strategy. However, because of the high price of force/torque sensors and the closedness of an industrial robot control system, this method is not convenient for industrial mass production applications. Various types of data generated by industrial robots during the polishing process can be saved, transmitted, and applied, benefiting from the growth of the industrial internet of things (IIoT). Therefore, we propose a constant force control system that combines an industrial robot control system and industrial robot offline programming software for a polishing robot based on IIoT time series data. The system mainly consists of four parts, which can achieve constant force polishing of industrial robots in mass production. (1) Data collection module. Install a six-dimensional force/torque sensor at a manipulator and collect the robot data (current series data, etc.) and sensor data (force/torque series data). (2) Data analysis module. Establish a relationship model based on variant long short-term memory which we propose between current time series data of the polishing manipulator and data of the force sensor. (3) Data prediction module. A large number of sensorless polishing robots of the same type can utilize that model to predict force time series. (4) Trajectory optimization module. The polishing trajectories can be adjusted according to the prediction sequences. The experiments verified that the relational model we proposed has an accurate prediction, small error, and a manipulator taking advantage of this method has a better polishing effect.

Force Control of a Hydraulic Actuator With a Neural Network Inverse Model

2021 ◽  
Vol 6 (2) ◽  
pp. 2814-2821
Author(s):  
Sung-Woo Kim ◽  
Buyoun Cho ◽  
Seunghoon Shin ◽  
Jun-Ho Oh ◽  
Jemin Hwangbo ◽  
...  
Keyword(s):  
Neural Network ◽  
Force Control ◽  
Inverse Model ◽  
Hydraulic Actuator
Sign in / Sign up

Export Citation Format

Share Document