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Actuators
Special Issues
Learning and Control of Underactuated Mechanical System
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Learning and Control of Underactuated Mechanical System

A special issue of Actuators (ISSN 2076-0825). This special issue belongs to the section "Control Systems".

Deadline for manuscript submissions: closed (30 June 2022) | Viewed by 11737

Special Issue Editors

Prof. Dr. Chunyi Su

E-Mail Website
Guest Editor
Gina Cody School of Engineering and Computer Science, Concordia University, 1455 de Maisonneuve Blvd. W., Montreal, QC H3G 1M8, Canada
Interests: modeling and control of smart material-based actuators; soft robots; control of robotic systems; mechatronic systems
Prof. Dr. Xuzhi Lai

E-Mail Website
Guest Editor
School of Automation, China University of Geosciences, Lumo Road, Wuhan, Hubei 430074, China
Interests: intelligent control; robot control; nonlinear system control and control of underactuated mechanical systems

Special Issue Information

Dear colleagues,

In the last few decades, there has been great theoretical and practical interest in learning and controlling underactuated mechanical systems. These systems are defined as underactuated because they have more joints than control actuators. Much of this interest is a consequence of the importance of such systems in applications. For example, underactuation may arise in free-flying space robots, underwater vehicles without base actuators, legged robots with passive joints, redundant robots with flexible components, and in many other practical applications. Furthermore, when one or more joints of a standard manipulator fail, it becomes an underactuated mechanism and needs a special control algorithm to continue operation; thus, the development of learning and control techniques for underactuated systems will increase the reliability and fault tolerance of current and future robots. Interest in studying underactuated mechanical systems is also motivated by their role as a class of strongly nonlinear systems where complex internal dynamics, nonholonomic behavior, and lack of feedback linearizability are often exhibited. Traditional nonlinear control methods are insufficient in these cases, and new approaches must be developed. This Special Issue aims to present advances in both learning and control of underactuated mechanical systems and the use of underactuated systems in application domains.

Prof. Dr. Chunyi Su
Prof. Dr. Xuzhi Lai
Guest Editors

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Actuators is an international peer-reviewed open access monthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2400 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Keywords

  • underactuation
  • underactuated robotics
  • underactuated mechanisms
  • underactuated control
  • underactuated learning control
  • nonholonomic constraints

Published Papers (4 papers)

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Research

12 pages, 546 KiB  
Communication
A Model-Free Output Feedback Control Approach for the Stabilization of Underactuated TORA System with Input Saturation
by Changzhong Pan, Chenchen Cui, Lan Zhou, Peiyin Xiong and Zhijing Li
Actuators 2022, 11(3), 97; https://doi.org/10.3390/act11030097 - 21 Mar 2022
Cited by 3 | Viewed by 3022
Abstract
The horizontal translational oscillator with a rotational actuator (TORA) is a typical underactuated mechanical system, whose control problem is still open and theoretically challenging. At present, the existing control methods are structurally complicated and require an exact knowledge of the system parameters. Moreover, [...] Read more.
The horizontal translational oscillator with a rotational actuator (TORA) is a typical underactuated mechanical system, whose control problem is still open and theoretically challenging. At present, the existing control methods are structurally complicated and require an exact knowledge of the system parameters. Moreover, few works have considered the output feedback stabilization of the TORA system subject to practical constraints of input saturation and angular velocity unmeasurement. To address these problems, this paper proposes a novel model-free amplitude-limited control approach to stabilize the TORA system at the origin using only angle feedback. Firstly, the passivity of the horizontal TORA system is analyzed, based on which a novel Lyapunov function augmented with an auxiliary signal is constructed by taking the input saturation into account. Then, an amplitude-limited control law is derived in a straightforward manner. In order to make the control law independent of velocity feedback, the auxiliary signal is designed in terms of the ball rotational angle and an output of a dynamic system. The asymptotic stability of the entire control system is rigorously guaranteed by utilizing Lyapunov theory and LaSalle’s invariance principle. Finally, simulation results with comparisons to existing methods demonstrate the effectiveness and superiority of the proposed control approach. Full article
(This article belongs to the Special Issue Learning and Control of Underactuated Mechanical System)
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14 pages, 852 KiB  
Article
Equivalent Rope Length-Based Trajectory Planning for Double Pendulum Bridge Cranes with Distributed Mass Payloads
by Qingxiang Wu, Ning Sun and Xiaokai Wang
Actuators 2022, 11(1), 25; https://doi.org/10.3390/act11010025 - 17 Jan 2022
Cited by 4 | Viewed by 2812
Abstract
The hoisting form in which the payload is hung on the hook by two rigging ropes is widely used in the industry, but it also results in the complex double pendulum dynamic of the bridge crane, making the anti-swing trajectory planning full of [...] Read more.
The hoisting form in which the payload is hung on the hook by two rigging ropes is widely used in the industry, but it also results in the complex double pendulum dynamic of the bridge crane, making the anti-swing trajectory planning full of challenges. In this paper, based on the concept of the equivalent rope length, an equivalent single pendulum model of the double pendulum bridge crane with the distributed mass payload is established. On this basis, the particle swarm optimization algorithm is adopted to solve the equivalent rope length and calculate the parameters of the anti-swing velocity trajectory based on the phase plane method. To evaluate the effectiveness of the proposed method, experiments with a laboratory double pendulum bridge crane are conducted. Experimental results demonstrate that the residual oscillation angle of the payload of the proposed method is smaller than those of the existing methods, such as the trajectory planning without the equivalent rope length, input shaping and command smoothing. Full article
(This article belongs to the Special Issue Learning and Control of Underactuated Mechanical System)
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12 pages, 487 KiB  
Article
A Simple Control Strategy Based on Trajectory Planning for Vertical Acrobot
by Lejun Wang, Siyu Chen, Pan Zhang, Jinhua She and Xuzhi Lai
Actuators 2021, 10(12), 308; https://doi.org/10.3390/act10120308 - 25 Nov 2021
Cited by 3 | Viewed by 2497
Abstract
This paper presents a simple control method on the basis of the trajectory planning for vertical Acrobot to accomplish the control goal of moving the system from the downward initial position (DIP) and steadying the system at the upward target position (UTP). First, [...] Read more.
This paper presents a simple control method on the basis of the trajectory planning for vertical Acrobot to accomplish the control goal of moving the system from the downward initial position (DIP) and steadying the system at the upward target position (UTP). First, for the active link, we frame a trajectory that contains some adjustable parameters. Along the framed trajectory, we can make the active link stabilize at its end angle from its start angle. Furthermore, we change the trajectory parameters to make the passive link also arrive at the zone near the end angle. Next, we devise a PD-based tracking controller to track this planned trajectory. In this way, the vertical Acrobot is swung up to a small zone near the UTP. Then, from the approximate linear model at the UTP, we devise a stabilization controller to stabilize the vertical Acrobot at the UTP. Finally, we implement the simulation to show the validity of the proposed method. Full article
(This article belongs to the Special Issue Learning and Control of Underactuated Mechanical System)
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11 pages, 835 KiB  
Article
Continuous Control Strategy of Planar 3-Linkage Underactuated Manipulator Based on Broad Neural Network
by Siyu Chen, Yawu Wang, Pan Zhang and Chun-Yi Su
Actuators 2021, 10(10), 249; https://doi.org/10.3390/act10100249 - 27 Sep 2021
Cited by 4 | Viewed by 2016
Abstract
For the position control of a planar 3-linkage underactuated manipulator (PTUM) with a passive first linkage, a continuous control strategy is developed in this paper. In particular, a broad neural network (BNN)-based model is first established to accurately describe the motion coupling relationship [...] Read more.
For the position control of a planar 3-linkage underactuated manipulator (PTUM) with a passive first linkage, a continuous control strategy is developed in this paper. In particular, a broad neural network (BNN)-based model is first established to accurately describe the motion coupling relationship between the passive linkage and the second linkage. Based on this model, by using the particle swarm optimization algorithm, the target angles of all linkages are calculated combining the start states of all linkages and the target position of the PTUM. Then, the target angles of the active linkages are directly achieved by their respective actuators, and that of the passive linkage is also achieved by the rotation of the second linkage. By carrying out several experiments, the effectiveness of the above strategy is verified. Full article
(This article belongs to the Special Issue Learning and Control of Underactuated Mechanical System)
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