Experimental verification of progressive learning control for high-speed direct-drive robots with structure flexibility and non-collocated sensors

2005 ◽  
pp. 319-330
Author(s):  
Shih-Hung Li ◽  
Boo-Ho Yang ◽  
Haruhiko Asada
Keyword(s):  
Experimental Verification ◽  
High Speed ◽  
Learning Control ◽  
Direct Drive ◽  
Structure Flexibility ◽  
Progressive Learning

Iterative learning control of air pressure variation inside a high-speed train under the excitation of the tunnel pressure wave with a fixed-morphologic form

2021 ◽  
pp. 095440972110327
Author(s):  
Zhiying He ◽  
Chunjun Chen ◽  
Dongwei Wang ◽  
Chao Deng ◽  
Jia Hu ◽  
...  
Keyword(s):  
Iterative Learning Control ◽  
Pressure Wave ◽  
High Speed ◽  
Learning Control ◽  
Pressure Variation ◽  
Iterative Learning ◽  
Air Pressure ◽  
High Speed Train ◽  
Comfort Index ◽  
Simulation Signal

Based on the characteristics that the tunnel pressure wave has a fixed-morphologic form when the same train passes through the same tunnel, an applicational approach based on the iterative learning control (ILC) is developed, aiming at overcoming the drawbacks of the traditional strategy for controlling the air pressure variation inside a high-speed train carriage. To achieve the goal, the control system is mathematically modelled. Then, the problem is formulated. The task of suppressing the influence of the tunnel pressure wave on the air pressure inside the carriages is shifted as an ILC problem of tracking the comfort index with varying trial length. The algorithm of refreshing the control signal from trial to trial is determined and the process of ILC control is designed. Next, the convergence of the newly-developed applicational ILC algorithm is discussed and the algorithm is simulated by the simulation signal and field-test signal. Results show that the applicational ILC algorithm be more adaptable in handling the control of the air pressure inside carriage under the excitation of varying-amplitude, varying-scale and varying-initial-states tunnel pressure wave. Meanwhile, the matching with tunnel pressure wave makes the applicational ILC algorithm will take both the riding comfort and fresh air into consideration, which upgrades the performances when the high-speed train passing through long tunnels.

Design and control of a high-speed direct-drive manipulator

1989 ◽  
Vol 27 (3) ◽  
pp. 375-394 ◽  
Author(s):  
K. YOUCEF-TOUMI ◽  
A. T. Y. KUO
Keyword(s):  
High Speed ◽  
Direct Drive ◽  
And Control

scholarly journals High-Speed Elevator Car Air Pressure Compensation Method Based on Coupling Analysis of Internal and External Flow Fields

2021 ◽  
Vol 11 (4) ◽  
pp. 1700
Author(s):  
Lemiao Qiu ◽  
Huifang Zhou ◽  
Zili Wang ◽  
Shuyou Zhang ◽  
Lichun Zhang ◽  
...  
Keyword(s):  
Pressure Fluctuation ◽  
Iterative Learning Control ◽  
High Speed ◽  
Learning Control ◽  
Flow Fields ◽  
External Flow ◽  
Iterative Learning ◽  
Air Pressure ◽  
Coupling Analysis ◽  
Pressure Compensation

As the demand for high-speed elevators grows, the requirements of elevator performance have also developed. The high speed will produce strong airflow disturbances and drastic pressure changes, which is prone to cause passenger discomfort. In this paper, an elevator car air pressure compensation method based on coupling analysis of internal and external flow fields (IE-FF) is proposed. It helps to adaptively track the ideal air pressure curve (IAPC) inside the car and controls the air pressure fluctuation to improve the ride comfort of the elevator. To obtain the air pressure transient value in the elevator car, an IE-FF modeling method is proposed. Based on the IE-FF model, the air pressure compensation system is developed. To realize the air pressure compensation inside the car, an adaptive iterative learning control (A-ILC) algorithm is proposed, to eliminate the passengers’ ear pressing due to the severe air pressure fluctuation. To verify the proposed method, the KLK2 (Canny Elevator Co., Ltd., 2015, Suzhou, China) high-speed elevator is applied. The numerical experiment results show that the proposed method has higher tracking accuracy and convergence speed compared to the classical Proportion Integral Differential (PID) algorithm and the Proportion Integral-iterative learning control (PD-ILC) algorithm.

STAND-UP MOTION SUPPORT BY A MOBILE MANIPULATOR SYSTEM WITH HIGH SPEED TACTILE SENSORS

2011 ◽  
Vol 08 (03) ◽  
pp. 181-195
Author(s):  
ZHAOXIAN XIE ◽  
HISASHI YAMAGUCHI ◽  
MASAHITO TSUKANO ◽  
AIGUO MING ◽  
MAKOTO SHIMOJO
Keyword(s):  
Fuzzy Logic ◽  
Feedback Control ◽  
Experimental Verification ◽  
High Speed ◽  
Center Of Pressure ◽  
Tactile Sensor ◽  
Mobile Manipulator ◽  
Tactile Sensing ◽  
Robot Arm ◽  
Tactile Sensors

As one of the home services by a mobile manipulator system, we are aiming at the realization of the stand-up motion support for elderly people. This work is charaterized by the use of real-time feedback control based on the information from high speed tactile sensors for detecting the contact force as well as its center of pressure between the assisted human and the robot arm. First, this paper introduces the design of the tactile sensor as well as initial experimental results to show the feasibility of the proposed system. Moreover, several fundamental tactile sensing-based motion controllers necessary for the stand-up motion support and their experimental verification are presented. Finally, an assist trajectory generation method for the stand-up motion support by integrating fuzzy logic with tactile sensing is proposed and demonstrated experimentally.

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