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Machines
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Control of Robotic Systems
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Control of Robotic Systems

A special issue of Machines (ISSN 2075-1702).

Deadline for manuscript submissions: closed (30 June 2022) | Viewed by 9875

Special Issue Editors

Dr. Jose De Jesus Rubio

E-Mail Website
Guest Editor
Seccion de Estudios de Posgrado e Investigacion, Esime Azcapotzalco, Instituto Politecnico Nacional, Mexico City, 02250 Ciudad de Mexico, Mexico
Interests: control; robotics; mechatronics
Special Issues, Collections and Topics in MDPI journals
Dr. Genaro Ochoa

E-Mail Website
Guest Editor
Departamento de Mecatronica, Instituto Tecnologico Superior de Tierra Blanca, 95180 Veracruz, Mexico
Interests: control; robotics; mechatronics
Special Issues, Collections and Topics in MDPI journals
Dr. Ricardo Balcazar

E-Mail Website
Guest Editor
Departamento de Mecatronica, Tecnologico de Estudios Superiores de Coacalco, 55700 Estado de Mexico, Mexico
Interests: control; robotics; mechatronics
Special Issues, Collections and Topics in MDPI journals
Dr. Luis Arturo Soriano

E-Mail Website
Guest Editor
Departamento de Mecatronica, Universidad Autonoma Chapingo, 56230 Texcoco, Mexico
Interests: control; robotics; mechatronics

Special Issue Information

Dear Colleagues,

Robotic systems represent an interdisciplinary branch of engineering and science that includes mechanical engineering, electronic engineering, information engineering, computer science, and others. Robotics deals with the design, construction, operation, and use of robots, as well as computer systems for their control, sensory feedback, and information processing. These technologies are used to develop machines that can substitute humans and replicate human actions. Robots can be used in many situations and for many purposes, and today many are used in dangerous environments, manufacturing systems, or where humans cannot survive. Examples of these robotic systems are robotic arms, mobile robots, air robots, parallel robots, pendulums, electric motors, electric generators, wind turbines, solar followers, or other.

Control systems direct the behavior of robotic systems using control loops. The control system compares the value of the robot variable being controlled with the desired value, and applies the control signal to bring the robot variable to the desired value. Control has been utilized for regulation, trajectory tracking, stabilization, synchronization, nonlinearities compensation, optimization, obstacle avoiding, and disturbances rejection. It brings the necessity to research control methods of robotic systems. Examples of these control methods include adaptive, model-based, evolving, neural network, fuzzy, intelligent, backstepping, sliding mode, robust, state feedback, geometric, structure at infinity, structure, observer based, active rejection, optimal, and optimization control. Additionally, the stability of the mentioned control methods is a subject worth study.

The objective of this Special Issue of Machines is to cover the control methods of robotic systems.

Original contributions are solicited on topics including but not limited to the following:

  • Adaptive model-based or evolving control of robotic systems;
  • Neural network or fuzzy control of robotic systems;
  • Intelligent or backstepping control of robotic systems;
  • Feedback or geometric control of robotic systems;
  • Sliding mode or robust control of robotic systems;
  • Structure at infinity or structure control of robotic systems;
  • Observer-based or active-rejection control of robotic systems;
  • Optimal or optimization control of robotic systems;
  • Other alternative control methods for robotic systems.

Dr. Jose De Jesus Rubio
Dr. Genaro Ochoa
Dr. Ricardo Balcazar
Dr. Luis Arturo Soriano
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. Machines 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

  • control robotic systems
  • regulation
  • trajectory tracking
  • stabilization
  • synchronization
  • obstacle avoidance
  • disturbance rejection

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Published Papers (4 papers)

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Research

17 pages, 3002 KiB  
Article
Orientation Modeling Using Quaternions and Rational Trigonometry
by Rogelio Martínez, Erik Zamora, Humberto Sossa, Fernando Arce and Luis Arturo Soriano
Machines 2022, 10(9), 749; https://doi.org/10.3390/machines10090749 - 30 Aug 2022
Cited by 2 | Viewed by 2634
Abstract
In recent years, the recreational and commercial use of flight and driving simulators has become more popular. All these applications require the calculation of orientation in either two or three dimensions. Besides the Euler angles notation, other alternatives to represent rigid body rotations [...] Read more.
In recent years, the recreational and commercial use of flight and driving simulators has become more popular. All these applications require the calculation of orientation in either two or three dimensions. Besides the Euler angles notation, other alternatives to represent rigid body rotations include axis-angle notation, homogeneous transformation matrices, and quaternions. All these methods involve transcendental functions in their calculations, which represents a disadvantage when these algorithms are implemented in hardware. The use of transcendental functions in software-based algorithms may not represent a significant disadvantage, but in hardware-based algorithms, the potential of rational models stands out. Generally, to calculate transcendental functions in hardware, it is necessary to utilize algorithms based on the CORDIC algorithm, which requires a significant amount of hardware resources (parallel) or the design of a more complex control unit (pipelined). This research presents a new procedure for model orientation using rational trigonometry and quaternion notation, avoiding trigonometric functions for calculations. We describe the orientation of a gimbal mechanism presented in many applications, from autonomous vehicles such as cars or drones to industrial manipulators. This research aims to compare the efficiency of a rational implementation to classical modeling using the techniques mentioned above. Furthermore, we simulate the models with software tools and propose a hardware architecture to implement our algorithms. Full article
(This article belongs to the Special Issue Control of Robotic Systems)
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15 pages, 1735 KiB  
Article
Navigation of a Differential Wheeled Robot Based on a Type-2 Fuzzy Inference Tree
by Dante Mújica-Vargas, Viridiana Vela-Rincón, Antonio Luna-Álvarez, Arturo Rendón-Castro, Manuel Matuz-Cruz and José Rubio
Machines 2022, 10(8), 660; https://doi.org/10.3390/machines10080660 - 5 Aug 2022
Cited by 5 | Viewed by 1825
Abstract
This paper presents a type-2 fuzzy inference tree designed for a differential wheeled mobile robot that navigates in indoor environments. The proposal consists of a controller designed for obstacle avoidance, a controller for path recovery and goal reaching, and a third controller for [...] Read more.
This paper presents a type-2 fuzzy inference tree designed for a differential wheeled mobile robot that navigates in indoor environments. The proposal consists of a controller designed for obstacle avoidance, a controller for path recovery and goal reaching, and a third controller for the real-time selection of behaviors. The system takes as inputs the information provided for a 2D laser range scanner, i.e., the distance of nearby objects to the robot, as well as the robot position in space, calculated from mechanical odometry. The real performance is evaluated through metrics such as clearance, path smoothness, path length, travel time and success rate. The experimental results allow us to demonstrate an appropriate performance of our proposal for the navigation task, with a higher efficiency than the reference methods taken from the state of the art. Full article
(This article belongs to the Special Issue Control of Robotic Systems)
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24 pages, 1652 KiB  
Article
Flatness-Based Active Disturbance Rejection Control for a PVTOL Aircraft System with an Inverted Pendular Load
by Cesar Alejandro Villaseñor Rios, Alberto Luviano-Juárez, Norma Beatriz Lozada-Castillo, Blanca Esther Carvajal-Gámez, Dante Mújica-Vargas and Octavio Gutiérrez-Frías
Machines 2022, 10(7), 595; https://doi.org/10.3390/machines10070595 - 21 Jul 2022
Cited by 8 | Viewed by 2119
Abstract
This paper presents a systematic procedure for the control scheme design for a PVTOL aircraft system with an inverted pendular load, which is a nonlinear underactuated system. The control scheme is based on the use of angular movement as an artificial control in [...] Read more.
This paper presents a systematic procedure for the control scheme design for a PVTOL aircraft system with an inverted pendular load, which is a nonlinear underactuated system. The control scheme is based on the use of angular movement as an artificial control in order to propose new auxiliary control inputs. This is achieved by a linear extended state observer-based active disturbance rejection control to reject both nonmodeled dynamics and external disturbances. The flying planar inverted pendulum is then linearized around an unstable equilibrium point, and the resulting system is subdivided into two subsystems: (1) the height system, and (2) the horizontal pendulum system. For the height system, a linear extended state observer-based active disturbance rejection control is proposed in order to accomplish a take-off and landing task in the presence of external disturbances and non-linearities neglected in the linearization process. The flatness property in the horizontal-pendulum system is exploited in order to propose another active disturbance rejection control of linear nature. The flatness of the tangentially linearized model provides a unique structural property that results in an advantageous low-order cascade decomposition of the linear extended state observer design. Numerical simulations show the effectiveness of the proposed control scheme in trajectory tracking tasks in the presence of disturbances caused by crosswinds with random amplitudes. Full article
(This article belongs to the Special Issue Control of Robotic Systems)
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13 pages, 2338 KiB  
Article
Virtual Neuromuscular Control for Robotic Ankle Exoskeleton Standing Balance
by Kaiyang Yin, Yantao Jin, Haojie Du, Yaxu Xue, Pengfei Li and Zhengsen Ma
Machines 2022, 10(7), 572; https://doi.org/10.3390/machines10070572 - 15 Jul 2022
Cited by 2 | Viewed by 1862
Abstract
The exoskeleton is often regarded as a tool for rehabilitation and assistance of human movement. The control schemes were conventionally implemented by developing accurate physical and kinematic models, which often lack robustness to external variational disturbing forces. This paper presents a virtual neuromuscular [...] Read more.
The exoskeleton is often regarded as a tool for rehabilitation and assistance of human movement. The control schemes were conventionally implemented by developing accurate physical and kinematic models, which often lack robustness to external variational disturbing forces. This paper presents a virtual neuromuscular control for robotic ankle exoskeleton standing balance. The robustness of the proposed method was improved by applying a specific virtual neuromuscular model to estimate the desired ankle torques for ankle exoskeleton standing balance control. In specialty, the proposed control method has two key components, including musculoskeletal mechanics and neural control. A simple version of the ankle exoskeleton was designed, and three sets of comparative experiments were carried out. The experimentation results demonstrated that the proposed virtual neuromuscular control could effectively reduce the wearer’s lower limb muscle activation, and improve the robustness of the different external disturbances. Full article
(This article belongs to the Special Issue Control of Robotic Systems)
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