The tower crane is widely used in construction and transportation engineering. To improve working efficiency and safety, input shaping methods have been applied. Input shaping is a method of reducing residual vibration of flexible systems by convolving a sequence of impulses with unit step command. However, input shaping is based on the linear system theory in which its control performances are degraded, in case of nonlinearity and unmatched dynamics of the control systems. In this paper, a new optimal reference input shape design method based on minimizing cost function is suggested and applied, to a simple cart-pendulum system which is a simplified model of tower cranes. Since pendulum dynamics is nonlinear, analytic solution does not exist. To overcome this problem, in this paper, a machine learning approach is suggested to find optimal reference input shape for the cart position control. The feasibility of the proposed design method is verified through some simulation examples by using MatLab.
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Dynamic Force‐Shaped Input Control With Adjustable Maneuvering Time for Payload Transportation Systems Abdullah Mohammed, Abdulaziz Al-Fadhli, Khalid Alghanim, Emad Khorshid, Petko Petkov Journal of Control Science and Engineering.2025;[Epub] CrossRef
This paper presents an improved input shaping method to eliminate vibration during circular interpolation of a flexible 2-axis positioning system. Due to the time delay introduced by input shaping, simultaneous 2-axis positioning with circular interpolation results in a certain amount of errors from the intended track or trajectory. This study investigated the track errors associated with circular interpolation caused by input shaping for a flexible 2-axis positioning system. The following three strategies for reducing such errors were proposed: velocity reduction in circular interpolation, adjustment of the time delay between 2 axes commands, and employment of a velocity profile compensation function. Simulations were performed to discuss the pros and cons of the three proposed strategies. Experiments were also performed to validate the results. Simulation and experiments showed that the track errors due to input shaping can be sufficiently reduced by combined use of the proposed strategies.
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A Study on the Improvement of Machining Precision by Applying Input Shaping Method to Machining Center Kang-Ho Ko, Dong-Wook Lim, Seong-Wook Hong Journal of the Korean Society of Manufacturing Technology Engineers.2023; 32(4): 189. CrossRef
Input-shaping-based improvement in the machining precision of laser micromachining systems Dong-Wook Lim, Seong-Wook Hong, Seok-Jae Ha, Ji-Hun Kim, Hyun-Taek Lee The International Journal of Advanced Manufacturing Technology.2023; 125(9-10): 4415. CrossRef
Application of Input Shaping to a CNC Laser Processing Machine to Enhance Processing Precision Kang Ho Ko, Jin Uk Sim, Seong-Wook Hong Journal of the Korean Society of Manufacturing Technology Engineers.2022; 31(5): 346. CrossRef
There are many nonlinear vibration problems of mechanical structures because of various reasons such as geometric parameters, impact loads, or property of materials. One simple solution for the suppression of nonlinear structural vibration is input shaping that generates a command signal to cancel its vibration. However, a motion platform to evaluate the performance of input shapers for nonlinear vibration is rare. This paper presents the evaluation of input shaping methods for the nonlinear vibration system using a Furuta pendulum. First, the mathematical model of the Furuta pendulum is introduced and its nonlinear vibration characteristic is analyzed. Then, commands for canceling the nonlinear vibration of the Furuta pendulum are generated with various input shapers such as ZV, ZVD, and ZVDD. Finally, we illustrate the effects of input shapers on the nonlinear Furuta pendulum by comparing the pendulum overshoot, settling time, and vibration-reduction ratio. The Furuta pendulum is shown to be a good motion platform to evaluate input shaping methods for nonlinear vibration systems.
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A Novel Composite Nonsingular Terminal Sliding Mode Control with Lumped Uncertainties Observer for Robot Manipulator: From Theory to Experiment Anh-Duc Pham, Nhu Thanh Vo International Journal of Precision Engineering and Manufacturing.2026;[Epub] CrossRef
Analysis of the parametric configuration impact on BallBot control performance Anh‐Duc Pham, Ba Hoa Thai, Phuoc Vinh Dang, Nhu Thanh Vo International Journal of Mechanical System Dynamics.2024; 4(4): 446. CrossRef
Most positioning systems experience residual vibration during operation. Such residual vibration can be eliminated or reduced to an acceptable level by using the input shaping method. However, adopting the input shaping methods typically introduces a certain amount of time-delay into a system. This study focused on the development of a delay-time adjustable input shaping method to eliminate vibration caused by repetitive motion in positioning systems. The proposed input shaping method, called the virtual mode (VM) input shaper, uses a virtual frequency parameter that adjusts delay-time and cancels residual vibration. Unlike most previous input shaping studies, this study investigated VM input shaping performance to eliminate the steady-state vibration induced by repetitive motion in positioning systems. To this end, an analytical formulation was derived and used for simulating the input shaping performance with varying dominant parameters involved in a system. Experiments were also performed to validate the proposed method.
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Data Driven Vibration Control: A Review Weiyi Yang, Shuai Li, Xin Luo IEEE/CAA Journal of Automatica Sinica.2024; 11(9): 1898. CrossRef
Improved Input Shaping Method for Circular Interpolation of a 2-Axis Positioning System Jin Uk Sim, Pil Kyu Choi, Sun-Woong Kwon, Seong-Wook Hong Journal of the Korean Society for Precision Engineering.2022; 39(4): 283. CrossRef
Application of Input Shaping to a CNC Laser Processing Machine to Enhance Processing Precision Kang Ho Ko, Jin Uk Sim, Seong-Wook Hong Journal of the Korean Society of Manufacturing Technology Engineers.2022; 31(5): 346. CrossRef
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