scholarly journals A novel shared control algorithm for industrial robots

2016 ◽  
Vol 13 (6) ◽  
pp. 172988141668270 ◽  
Author(s):  
Marco Ramacciotti ◽  
Mario Milazzo ◽  
Fabio Leoni ◽  
Stefano Roccella ◽  
Cesare Stefanini
Keyword(s):  
High Precision ◽  
Control Algorithm ◽  
Industrial Robots ◽  
Shared Control ◽  
Mechatronic Systems ◽  
Industrial Activities ◽  
Control Approach ◽  
Human Management

Human management of robots in many specific industrial activities has long been imperative, due to the elevated levels of complexity involved, which can only be overcome through long and wasteful preprogrammed activities. The shared control approach is one of the most emergent procedures that can compensate and optimally couple human smartness with the high precision and productivity characteristic to mechatronic systems. To explore and to exploit this approach in the industrial field, an innovative shared control algorithm was elaborated, designed and validated in a specific case study.

A Methodology for Remote Debug, Test and Maintenance Based on IEEE 1588

2011 ◽  
Author(s):  
Peter Ro¨ssler ◽  
Roland Ho¨ller ◽  
Martin Zauner
Keyword(s):  
High Precision ◽  
Clock Synchronization ◽  
Automotive Electronics ◽  
Mechatronic Systems ◽  
Ieee 1588 ◽  
Remote Testing ◽  
Synchronization Protocol ◽  
Precision Clock

This work describes a new methodology for the purpose of remote testing, debugging and maintenance of networked electronic and mechatronic systems which makes use of the IEEE 1588 high-precision clock synchronization protocol. After the underlying concepts of IEEE 1588 are briefly sketched, the paper describes how functionalities like testing, debugging and maintenance can benefit from a network-wide notion of time as provided by the IEEE 1588 standard. An implementation of the IEEE 1588 protocol with support for test, debug and maintenance as well as links to the integration of the proposed concept into existing tools are presented. Further, the proposed approach is discussed under consideration of recent standardization efforts. Finally, a case study from the area of automotive electronics is described.

A General Technique to Evaluate the Effects of Manufacturing Errors on Positioning Precision During Design

2016 ◽  
Author(s):  
Henrique Simas ◽  
Raffaele Di Gregorio
Keyword(s):  
High Precision ◽  
Industrial Robots ◽  
Geometric Errors ◽  
General Technique ◽  
Positioning Precision ◽  
Accurate Evaluation ◽  
Manufacturing Errors ◽  
Geometric Constants

Industrial robots designed to accomplish high precision tasks require an accurate evaluation of the effects of manufacturing and assembly (geometric) errors on positioning precision. In the literature, such evaluations are mainly tailored on particular architectures and the proposed techniques are difficult to extend. Here, a general discussion on how to take into account geometric errors’ effects is presented together with a method for selecting either which workspace region is less affected by geometric errors or which geometric constants must be carefully sized to reduce these effects. The proposed method can be applied to any architecture. A case study is presented to better explain the method.

scholarly journals Learning Feedforward Control Using Multiagent Control Approach for Motion Control Systems

Energies ◽  
2021 ◽  
Vol 14 (2) ◽  
pp. 420
Author(s):  
Phong B. Dao
Keyword(s):  
Real Time ◽  
Feedforward Control ◽  
Design Method ◽  
Mechatronic Systems ◽  
Control Approach ◽  
Runtime Environment ◽  
Multiagent Control ◽  
On Line ◽  
Promising Solution ◽  
Function Approximator

Multiagent control system (MACS) has become a promising solution for solving complex control problems. Using the advantages of MACS-based design approaches, a novel solution for advanced control of mechatronic systems has been developed in this paper. The study has aimed at integrating learning control into MACS. Specifically, learning feedforward control (LFFC) is implemented as a pattern for incorporation in MACS. The major novelty of this work is that the feedback control part is realized in a real-time periodic MACS, while the LFFC algorithm is done on-line, asynchronously, and in a separate non-real-time aperiodic MACS. As a result, a MACS-based LFFC design method has been developed. A second-order B-spline neural network (BSN) is used as a function approximator for LFFC whose input-output mapping can be adapted during control and is intended to become equal to the inverse model of the plant. To provide real-time features for the MACS-based LFFC system, the open robot control software (OROCOS) has been employed as development and runtime environment. A case study using a simulated linear motor in the presence of nonlinear cogging and friction force as well as mass variations is used to illustrate the proposed method. A MACS-based LFFC system has been designed and implemented for the simulated plant. The system consists of a setpoint generator, a feedback controller, and a time-index LFFC that can learn on-line. Simulation results have demonstrated the applicability of the design method.

scholarly journals A force/motion control approach based on trajectory planning for industrial robots with closed control architecture

IEEE Access ◽  
2021 ◽  
pp. 1-1
Author(s):  
Alejandro GutierreznGiles ◽  
Luis U. EvangelistanHernandez ◽  
Marco A. Arteaga ◽  
Carlos A. CruznVillar ◽  
Alejandro RodrigueznAngeles
Keyword(s):  
Motion Control ◽  
Trajectory Planning ◽  
Industrial Robots ◽  
Control Architecture ◽  
Control Approach

scholarly journals An Adaptive Neuro-Fuzzy Control of Pneumatic Mechanical Ventilator

Actuators ◽  
2021 ◽  
Vol 10 (3) ◽  
pp. 51
Author(s):  
Jozef Živčák ◽  
Michal Kelemen ◽  
Ivan Virgala ◽  
Peter Marcinko ◽  
Peter Tuleja ◽  
...  
Keyword(s):  
Control System ◽  
Control Algorithm ◽  
Fuzzy Inference ◽  
Fuzzy Controller ◽  
Mechanical Design ◽  
Mechanical Ventilator ◽  
Mechanical Ventilators ◽  
Inference System ◽  
Control Approach ◽  
Neuro Fuzzy

COVID-19 was first identified in December 2019 in Wuhan, China. It mainly affects the respiratory system and can lead to the death of the patient. The motivation for this study was the current pandemic situation and general deficiency of emergency mechanical ventilators. The paper presents the development of a mechanical ventilator and its control algorithm. The main feature of the developed mechanical ventilator is AmbuBag compressed by a pneumatic actuator. The control algorithm is based on an adaptive neuro-fuzzy inference system (ANFIS), which integrates both neural networks and fuzzy logic principles. Mechanical design and hardware design are presented in the paper. Subsequently, there is a description of the process of data collecting and training of the fuzzy controller. The paper also presents a simulation model for verification of the designed control approach. The experimental results provide the verification of the designed control system. The novelty of the paper is, on the one hand, an implementation of the ANFIS controller for AmbuBag pressure control, with a description of training process. On other hand, the paper presents a novel design of a mechanical ventilator, with a detailed description of the hardware and control system. The last contribution of the paper lies in the mathematical and experimental description of AmbuBag for ventilation purposes.

The Study of Control Strategy for Sensor-Less PMSM

2014 ◽  
Vol 1006-1007 ◽  
pp. 575-580
Author(s):  
Qing Xie Chen ◽  
Jing Jing Chen ◽  
Yi Biao Fan
Keyword(s):  
Control System ◽  
Permanent Magnet ◽  
High Precision ◽  
Control Strategy ◽  
Control Algorithm ◽  
Simulation Experiment ◽  
Permanent Magnet Synchronous Motor ◽  
Synchronous Motor ◽  
Single Chip

Targeting development of control system of a permanent magnet synchronous motor applied to high precision requirement, A strategy is researched to develop a single chip with built-in sensor-less control algorithm which is used as the control core of PMSM control system, the composition of the hardware and the realization of software of the chip are designed, and the simulation experiment is carried out to verify feasibility and rationality of the control strategy as well.

Knowledge Recommendation System for Human-Robot Collaborative Disassembly Using Knowledge Graph

2021 ◽  
Author(s):  
Yang Hu ◽  
Yiwen Ding ◽  
Feng Xu ◽  
Jiayi Liu ◽  
Wenjun Xu ◽  
...  
Keyword(s):  
Recommendation System ◽  
Industrial Robots ◽  
Knowledge Graph ◽  
Disassembly Process ◽  
Knowledge Based ◽  
Manufacturing Efficiency ◽  
Human Operators ◽  
Traditional Manufacturing ◽  
Human Robot Collaboration

Abstract In recent years, more and more attention has been paid to Human-Robot Collaborative Disassembly (HRCD) in the field of industrial remanufacturing. Compared with the traditional manufacturing, HRCD helps to improve the manufacturing flexibility with considering the manufacturing efficiency. In HRCD, knowledge could be obtained from the disassembly process and then provides useful information for the operator and robots to execute their disassembly tasks. Afterwards, a crucial point is to establish a knowledge-based system to facilitate the interaction between human operators and industrial robots. In this context, a knowledge recommendation system based on knowledge graph is proposed to effectively support Human-Robot Collaboration (HRC) in disassembly. A disassembly knowledge graph is constructed to organize and manage the knowledge in the process of HRCD. After that, based on this, a knowledge recommendation procedure is proposed to recommend disassembly knowledge for the operator. Finally, the case study demonstrates that the developed system can effectively acquire, manage and visualize the related knowledge of HRCD, and then assist the human operator to complete the disassembly task by knowledge recommendation, thus improving the efficiency of collaborative disassembly. This system could be used in the human-robot collaboration disassembly process for the operators to provide convenient knowledge recommendation service.

Performance improvement of direct torque control for induction motor drive via fuzzy logic-feedback linearization

2019 ◽  
Vol 38 (2) ◽  
pp. 672-692 ◽  
Author(s):  
Abdelkarim Ammar
Keyword(s):  
Fuzzy Logic ◽  
Robust Control ◽  
Feedback Linearization ◽  
Control Algorithm ◽  
Direct Torque Control ◽  
Torque Control ◽  
Motor Drive ◽  
Induction Motor Drive ◽  
Content Type ◽  
Control Approach

Purpose This paper aims to propose an improved direct torque control (DTC) for the induction motor’s performance enhancement using dual nonlinear techniques. The exact feedback linearization is implemented to create a linear decoupled control. Besides, the fuzzy logic control approach has been inserted to generate the auxiliary control input for the feedback linearization controller. Design/methodology/approach To improve the DTC for induction motor drive, this work suggests the incorporation of two nonlinear approaches. As the classical feedback linearization suffers while the presence of uncertainties and modeling inaccuracy, it is recommended to be associated to another robust control approach to compensate the uncertainties of the model and make a robust control versus the variations of the machine parameters. Therefore, fuzzy logic controllers will be integrated as auxiliary inputs to the feedback linearization control law. Findings The simulation and the experimental validation of the proposed control algorithm show that the association of dual techniques can effectively achieve high dynamic behavior and improve the robustness against parameters variation and external disturbances. Moreover, the space vector modulation is used to preserve a fixed switching frequency, reduce ripples and low switching losses. Practical implications The theoretical, simulation and experimental studies prove that the proposed control algorithm can be used on different AC machines for variable speed drive applications such as oil drilling, traction systems and wind energy conversion systems. Originality/value The proposed DTC strategy has been developed theoretically and realized through simulation and experimental implementation. Different operation conditions have been conducted to check the ability and robustness of the control strategy, such as steady state, speed reversal maneuver, low-speed operation and parameters variation test with load application.

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