scholarly journals Studies on the Practical Use of Learning Feed-Forward Control System to Ship Manoeuvring Motion (I)

1996 ◽  
Vol 1996 (180) ◽  
pp. 705-712 ◽  
Author(s):  
Yoichi Ogawara ◽  
Seiji Iwamoto ◽  
Yoshihiro Yamamoto
2006 ◽  
Vol 2006.15 (0) ◽  
pp. 301-304
Author(s):  
Yuji KARIYA ◽  
Takehiko FUJIOKA ◽  
Hajime OYAMA ◽  
Shinya KUDOU ◽  
Takeshi TERAZAWA

Author(s):  
Ming Li ◽  
Huapeng Wu ◽  
Heikki Handroos ◽  
Marco Ceccarelli ◽  
Giuseppe Carbone

Due to the high stiffness, high dynamic performance, the parallel manipulator presents great advantages in the industrial manufacture. However in the machining process, the external low frequency disturbance, e.g. the varying cutting force, has a significant effect on the control system of parallel manipulator, which presents a chatter phenomenon on the end-effector of manipulator. In this paper, a feed forward control strategy is proposed to eliminate the effect of the random external disturbance on the control system of parallel manipulator. By applying the external disturbance force on the inverse dynamic model, the compensation torque is calculated and fed forward into the manipulator driving joints to cancel out the effect of the disturbance acting on the manipulator end-effector. The key issue herein is to be able to establish the accurate dynamic model for the parallel manipulator. Furthermore, in order to guarantee the position precision of the manipulator, a feed forward model-based control strategy combined with the feedback loop PV (position and velocity) control has been developed based on the reference trajectory, which could relatively simplify the highly nonlinear control system of the parallel manipulator and obtain a stable tracking error model. The whole research has been carried out on a parallel manipulator named CaPaMan which has been built in the laboratory of robotics and mechatronics in university of Cassino and South Latium. The results show that the chatter phenomenon could be utterly depressed by the force compensation from the feed forward path of the external disturbance; meanwhile the model-based controller can guarantee the trajectory tracking accuracy within a stable error by choosing the suitable PV gains.


2018 ◽  
Vol 154 ◽  
pp. 03002
Author(s):  
Barlian Henryranu Prasetio ◽  
Wijaya Kurniawan

This research implements self-balancing robot using 3 algorithms. There are PID Controller, Ensemble Kalman Filter and Feed-Forward Control system. The PID controller function is as a robot equilibrium control system. The Kalman Ensemble algorithm is used to reduce noise measurement of accelerometer and gyroscope sensors. The PID controller and Ensemble Kalman filter were implemented on self-balancing robot in previous research. In this paper, we added the Feed-Forward controller that serves to detect disturbance derived from the unevenness of the ground. Disturbance is detected using 2 proximity sensors. Base on test results that the system can detect disturbance with an average delay of 2.15 seconds at Kff optimal value is 2.92. Feed-Forward effects result in self-balancing robots increasing power so that the pitch of the robot changes to anticipation of disturbance.


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