scholarly journals A Human-Inspired Control Strategy for Improving Seamless Robot-To-Human Handovers

2021 ◽  
Vol 11 (10) ◽  
pp. 4437
Author(s):  
Paramin Neranon ◽  
Tanapong Sutiphotinun
Keyword(s):  
Control System ◽  
Control Strategy ◽  
Impedance Control ◽  
Human Interaction ◽  
Robotic Control ◽  
Natural Manner ◽  
Object Handover ◽  
Overall Performance ◽  
Survey Responses ◽  
Test Outcomes

One of the challenging aspects of robotics research is to successfully establish a human-like behavioural control strategy for human–robot handover, since a robotic controller is further complicated by the dynamic nature of the human response. This paper consequently highlights the development of an appropriate set of behaviour-based control for robot-to-human object handover by first understanding an equivalent human–human handover. The optimized hybrid position and impedance control was implemented to ensure good stability, adaptability and comfort of the robot in the object handover tasks. Moreover, a questionnaire technique was employed to gather information from the participants concerning their evaluations of the developed control system. The results demonstrate that the quantitative measurement of performance of the human-inspired control strategy can be considered acceptable for seamless human–robot handovers. This also provided significant satisfaction with the overall control performance in the robotic control system, in which the robot can dexterously pass the object to the receiver in a timely and natural manner without the risk of harm or injury by the robot. Furthermore, the survey responses were in agreement with the parallel test outcomes, demonstrating significant satisfaction with the overall performance of the robot–human interaction, as measured by an average rating of 4.20 on a five-point scale.

Research on a Pneumatic Miniature Robotic Control System Based on Improved Single Neural Network PID Control

2011 ◽  
Vol 105-107 ◽  
pp. 2157-2161
Author(s):  
Wen Li ◽  
Xiang Yu Dai
Keyword(s):  
Neural Network ◽  
Control System ◽  
Control Strategy ◽  
Pid Control ◽  
Learning Rule ◽  
Step Response ◽  
Weighting Coefficient ◽  
Robotic Control ◽  
Neural Network Pid ◽  
Single Neural Network

Pneumatic miniature robotic control system usually adopts PID (Proportion Integration Differentiation) control strategy at present. To cope with the limitations of the basic PID control strategy, an improved single neural network PID control strategy is put forward in this paper. The control strategy is a single neuron adaptive controller with adjusting weighting coefficient, the weighting coefficient is realized according to the Hebb learning rule with supervisory. Both simulation and experimental results indicate that steady state error of the system equal to zero in the step-response curve, this scheme is a feasible control method for the 3-dof pneumatic miniature robotic control system.

A Pneumatic Miniature Robotic Control System Based on Improved Single Neural Network PID Control

2013 ◽  
Vol 347-350 ◽  
pp. 733-738
Author(s):  
Wen Li ◽  
Hong Min Li
Keyword(s):  
Neural Network ◽  
Control System ◽  
Control Strategy ◽  
Pid Control ◽  
Control Method ◽  
Adaptive Controller ◽  
Weighting Coefficient ◽  
Robotic Control ◽  
Neural Network Pid ◽  
Single Neural Network

At present pneumatic miniature robotic control system usually adopts PID control strategy. The basic PID control strategy has its limitations. To cope with this problem, a lot of methods to optimize this strategy have been researched. In the paper an improved single neural network PID control strategy is put forward. The control strategy is a single neuron adaptive controller with adjusting weighting coefficient. Both simulation and experimental results indicate that this scheme is a feasible control method for the 3-dof pneumatic miniature robotic control system.

scholarly journals A Unified Control Strategy of Distributed Generation for Grid-Connected and Islanded Operation Conditions Using an Artificial Neural Network

2021 ◽  
Vol 13 (11) ◽  
pp. 6388
Author(s):  
Karim M. El-Sharawy ◽  
Hatem Y. Diab ◽  
Mahmoud O. Abdelsalam ◽  
Mostafa I. Marei
Keyword(s):  
Neural Network ◽  
Artificial Neural Network ◽  
Control System ◽  
Distributed Generation ◽  
Control Strategy ◽  
Current Control ◽  
Operating Conditions ◽  
Pi Controllers ◽  
Artificial Neural ◽  
The Stability

This article presents a control strategy that enables both islanded and grid-tied operations of a three-phase inverter in distributed generation. This distributed generation (DG) is based on a dramatically evolved direct current (DC) source. A unified control strategy is introduced to operate the interface in either the isolated or grid-connected modes. The proposed control system is based on the instantaneous tracking of the active power flow in order to achieve current control in the grid-connected mode and retain the stability of the frequency using phase-locked loop (PLL) circuits at the point of common coupling (PCC), in addition to managing the reactive power supplied to the grid. On the other side, the proposed control system is also based on the instantaneous tracking of the voltage to achieve the voltage control in the standalone mode and retain the stability of the frequency by using another circuit including a special equation (wt = 2πft, f = 50 Hz). This utilization provides the ability to obtain voltage stability across the critical load. One benefit of the proposed control strategy is that the design of the controller remains unconverted for other operating conditions. The simulation results are added to evaluate the performance of the proposed control technology using a different method; the first method used basic proportional integration (PI) controllers, and the second method used adaptive proportional integration (PI) controllers, i.e., an Artificial Neural Network (ANN).

scholarly journals Research on an Improved Sliding Mode Sensorless Six-Phase PMSM Control Strategy Based on ESO

Electronics ◽  
2021 ◽  
Vol 10 (11) ◽  
pp. 1292
Author(s):  
Hanying Gao ◽  
Guoqiang Zhang ◽  
Wenxue Wang ◽  
Xuechen Liu
Keyword(s):  
Control System ◽  
Control Strategy ◽  
Sliding Mode ◽  
High Reliability ◽  
Permanent Magnet Synchronous Motor ◽  
Torque Ripple ◽  
Estimation Accuracy ◽  
Switching Function ◽  
Motor Speed ◽  
Rotor Position

The six-phase motor control system has low torque ripple, low harmonic content, and high reliability; therefore, it is suitable for electric vehicles, aerospace, and other applications requiring high power output and reliability. This study presents a superior sensorless control system for a six-phase permanent magnet synchronous motor (PMSM). The mathematical model of a PMSM in a stationary coordinate system is presented. The information of motor speed and position is obtained by using a sliding mode observer (SMO). As torque ripple and harmonic components affect the back electromotive force (BEMF) estimated value through the traditional SMO, the function of the frequency-variable tracker of the stator current (FVTSC) is used instead of the traditional switching function. By improving the SMO method, the BEMF is estimated independently, and its precision is maintained under startup or variable-speed states. In order to improve the estimation accuracy and resistance ability of the observer, the rotor position error was taken as the disturbance term, and the third-order extended state observer (ESO) was constructed to estimate the rotational speed and rotor position through the motor mechanical motion equation. Finally, the effectiveness of the method is verified by simulation and experiment results. The proposed control strategy can effectively improve the dynamic and static performance of PMSM.

scholarly journals Design of an Integrated Vehicle Chassis Control System with Driver Behavior Identification

2015 ◽  
Vol 2015 ◽  
pp. 1-12 ◽  
Author(s):  
Bing Zhu ◽  
Yizhou Chen ◽  
Jian Zhao ◽  
Yunfu Su
Keyword(s):  
Control System ◽  
Control Strategy ◽  
Driver Behavior ◽  
Stability Performance ◽  
Integrated Chassis Control ◽  
Yaw Moment Control ◽  
Chassis Control ◽  
Lane Change Test ◽  
Behavior Characteristics ◽  
Vehicle Chassis

An integrated vehicle chassis control strategy with driver behavior identification is introduced in this paper. In order to identify the different types of driver behavior characteristics, a driver behavior signals acquisition system was established using the dSPACE real-time simulation platform, and the driver inputs of 30 test drivers were collected under the double lane change test condition. Then, driver behavior characteristics were analyzed and identified based on the preview optimal curvature model through genetic algorithm and neural network method. Using it as a base, an integrated chassis control strategy with active front steering (AFS) and direct yaw moment control (DYC) considering driver characteristics was established by model predictive control (MPC) method. Finally, simulations were carried out to verify the control strategy by CarSim and MATLAB/Simulink. The results show that the proposed method enables the control system to adjust its parameters according to the driver behavior identification results and the vehicle handling and stability performance are significantly improved.

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.

Scalable Architecture and Structure of Modules for Distributed Process Control System in Industrial Greenhouse Comp

2021 ◽  
Vol 22 (10) ◽  
pp. 527-536
Author(s):  
K. D. Krestovnikov ◽  
A. A. Erashov ◽  
A. N. Bykov
Keyword(s):  
Control System ◽  
Human Interaction ◽  
Wireless Data ◽  
Automated Control ◽  
Control Module ◽  
Artificial Lighting ◽  
Wireless Data Transmission ◽  
Sensor Module ◽  
Distributed Process ◽  
Combined Sensor

With the growth of the population, the issue of food supply of cities with high-quality agricultural crops becomes urgent. Supply problems arising from this can be solved with the use of industrial greenhouse complexes with artificial lighting and groundless technologies. The development of these complexes makes the task of developing a control system to automate the cultivation processes urgent. Real industrial greenhouse complexes have a significant number of operations with the direct participation of personnel, which can be automated: control of the greenhouse microclimate, lighting, watering and preparation of the nutrient solution composition. This paper presents the architecture of a distributed control system for industrial greenhouse complexes. The system is built on a modular basis and is divided into three levels. The developed architecture is based on the use of standard modules, which makes the control system flexible and scalable. The paper also presents the basic design ratios, with the help of which it is possible to determine the required number of modules for the three levels of the proposed architecture. The use of wireless data transmission between modules based on LoRa technology allows you to abandon the laying of an information bus and at the same time deploy the system over large areas. Control of the system and its parameters is possible through direct human interaction with the interface of the control module or through remote interaction through the cloud. The architecture includes 3 types of executive modules, one combined sensor module and a control module. Each of the executive modules functions according to a given algorithm, and its parameters are controlled by a control module, based on a given growing program and information from sensors. This feature allows you to increase the reliability of the system and continue working in the event of a loss of communication with the cloud, as well as to exclude emergencies in the event of a loss of communication between the modules. The developed solutions make it possible to adapt the proposed control system for greenhouse complexes of various configurations and growing principles.

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