Alleviation of Delay in Tele-Surgical Operations using Markov Approach based Smith Predictor

2022 ◽  
Vol 9 (3) ◽  
pp. 0-0
Keyword(s):  
Networked Control System ◽  
Smith Predictor ◽  
Packet Dropout ◽  
Control Loop ◽  
Total Delay ◽  
Predictive Controller ◽  
Error Estimations ◽  
Simulation Results ◽  
Day By Day ◽  
Surgical Operations

The acceptance of tele-robotics and teleoperations through networked control system (NCS) is increasing day-by-day. NCS involves the feedback control loop system wherein the control components such as actuators and sensors are controlled and allowed to share their feedback over real time network with distributed users spread geographically. The performance and surgical complications majorly depend upon time delay, packet dropout and jitter induced in the system. The delay of data packet to the receiving side not only causes instability but also affect the performance of the system. In this article, author designed and simulate the functionality of a model-based Smith predictive controller. The model and randomized error estimations are employed through Markov approach and Kalman techniques. The simulation results show a delay of 49.926ms from master controller to slave controller and 79.497ms of delay from sensor to controller results to a total delay of 129.423ms. This reduced delay improve the surgical accuracy and eliminate the risk factors to criticality of patients’ health.

scholarly journals COVID-19 Diagnosis Using Capsule Network and Fuzzy C -Means and Mayfly Optimization Algorithm

2021 ◽  
Vol 2021 ◽  
pp. 1-11
Author(s):  
Ali Farki ◽  
Zahra Salekshahrezaee ◽  
Arash Mohammadi Tofigh ◽  
Reza Ghanavati ◽  
Behdad Arandian ◽  
...  
Keyword(s):  
State Of The Art ◽  
Optimal Method ◽  
X Ray ◽  
Suggested Technique ◽  
Improve Accuracy ◽  
Sensitivity Rate ◽  
Chest X Ray ◽  
Therapeutic Measures ◽  
Simulation Results ◽  
Day By Day

The COVID-19 epidemic is spreading day by day. Early diagnosis of this disease is essential to provide effective preventive and therapeutic measures. This process can be used by a computer-aided methodology to improve accuracy. In this study, a new and optimal method has been utilized for the diagnosis of COVID-19. Here, a method based on fuzzy C -ordered means (FCOM) along with an improved version of the enhanced capsule network (ECN) has been proposed for this purpose. The proposed ECN method is improved based on mayfly optimization (MFO) algorithm. The suggested technique is then implemented on the chest X-ray COVID-19 images from publicly available datasets. Simulation results are assessed by considering a comparison with some state-of-the-art methods, including FOMPA, MID, and 4S-DT. The results show that the proposed method with 97.08% accuracy and 97.29% precision provides the highest accuracy and reliability compared with the other studied methods. Moreover, the results show that the proposed method with a 97.1% sensitivity rate has the highest ratio. And finally, the proposed method with a 97.47% F 1 -score rate gives the uppermost value compared to the others.

scholarly journals Performance Evaluation of Co-Design of Discrete Event Networked Controlled DC Motor System

2018 ◽  
Vol 7 (3.12) ◽  
pp. 968
Author(s):  
Ankur Jain ◽  
B K. Roy
Keyword(s):  
Packet Loss ◽  
Controller Design ◽  
Discrete Event ◽  
Dc Motor ◽  
Networked Control System ◽  
Control Technique ◽  
Network Link ◽  
Time Domains ◽  
Simulation Results ◽  
Transient And Steady State

In this paper, we have designed a control technique for a networked DC motor in the presence of networked delay, packet loss, and jitter. We have used the predicted states for the controller design to achieve the transient and steady-state objectives. A networked compensator is designed to overcome the network constraints. The network link is modelled using the queue server mechanism which can assimilate a lot of features of the network. The proposed technique can also be applied to various other applications. The analysis of the networked control system is done in frequency and time domains. The simulation results are presented to test the performance of the proposed control technique. 

ELIMINATION OF TIME DELAY IN DIGITAL CONTROL LOOP OF SWITCHING DC–DC CONVERTERS

2008 ◽  
Vol 17 (03) ◽  
pp. 525-537
Author(s):  
MINGZHI HE ◽  
JIANPING XU
Keyword(s):  
Time Delay ◽  
Digital Control ◽  
Experimental System ◽  
Power Supplies ◽  
Duty Ratio ◽  
Control Loop ◽  
Transient Performance ◽  
Switching Power ◽  
Simulation Results ◽  
Switching Power Supplies

Time delay introduced by sampling and calculation exists between the perturbation and the duty ratio updating in the digital control loop. This time delay degrades the transient performance of digital control switching power supplies. By overcoming the sampling and calculation time effect and to calibrate the ripple that occurs during switching cycles, new control algorithm is proposed in this paper to improve the transient performance of switching power supplies by eliminating the time delay in the control loop. Simulation results show the improvement of load transient performance by the proposed algorithms. Experimental system is also set up to verify the analysis and computer simulation results.

Modeling and Simulation of Nonlinear Networked Control System Based on Fuzzy Control

2012 ◽  
Vol 426 ◽  
pp. 368-371
Author(s):  
Sheng Li Song ◽  
Y. Chen ◽  
S.J. Huang ◽  
L.H Yang ◽  
R. He
Keyword(s):  
Control System ◽  
Nonlinear Problem ◽  
Control Method ◽  
Fuzzy Controller ◽  
Good Control ◽  
Networked Control System ◽  
Networked Control ◽  
Packet Dropout ◽  
Data Packet Dropout ◽  
Nonlinear Networked Control System

In the nonlinear networked control system (NCS), the conventional control method is difficult to achieve good control performance, due to the nonlinear problem associated with the disturbance factors, such as network induced time delay and data packet dropout. Considering this situation, this paper is aimed to propose a nonlinear networked control system based on T-S fuzzy model, which does not rely on specific network parameters or mathematical model. The nonlinear problem and the uncertainties of network can be both processed by the designed fuzzy controller. Then this approach is applied to nonlinear motor servo system, simulation of the example model is implemented in Matlab/Simulink associated with True Time toolbox. The results show that the proposed method not only is convenient for modeling, but also upgrade the performance of control system.

scholarly journals Switched Quantization Level Control of Networked Control Systems with Packet Dropouts

2014 ◽  
Vol 2014 ◽  
pp. 1-8 ◽  
Author(s):  
Shuo Wang ◽  
Mei Yu ◽  
Hangfei Wang ◽  
Wen Tan
Keyword(s):  
Networked Control Systems ◽  
Networked Control System ◽  
Switched System ◽  
Networked Control ◽  
Disturbance Attenuation ◽  
Packet Dropout ◽  
Level Control ◽  
Quantization Level ◽  
Dynamic Output Feedback Controller ◽  
Disturbance Attenuation Level

This paper investigates the relationship between the maximum allowable dropout bound and the quantization density. Networked Control System (NCS) is described as a time-delay switched system with constrained switching signals. A switched dynamic output feedback controller with prescribed disturbance attenuation level is designed via a cone complement linearization approach. A novel stability criterion is obtained by switched system theory. Furthermore, finding an appropriate quantization density used when packet dropout occurs is converted to an optimization problem.

Model-predictive reference trajectory planning for redundant pneumatic collaborative robots

2020 ◽  
Vol 68 (5) ◽  
pp. 360-374
Author(s):  
Annika Mayer ◽  
Daniel Müller ◽  
Adrian Raisch ◽  
Oliver Sawodny
Keyword(s):  
Nonlinear Model ◽  
Joint Space ◽  
Reference Trajectory ◽  
Control Loop ◽  
Collaborative Robots ◽  
Model Control ◽  
Continuum Robot ◽  
Predictive Controller ◽  
Human Operators ◽  
Working Day

AbstractCollaborative robots have the potential to simplify the working day of the future. The goal in the development of these robots is to assist human operators by handling all sorts of tasks. A common underlying problem is to move the robot’s tool center point in a desired way. In this work we consider the generation of a feasible trajectory in joint space given a reference in task space. This is done at the example of the Bionic Handling Assistant (BHA), a compliant, redundant and pneumatically driven continuum robot. The trajectory for the BHA is obtained using a model control loop (MCL) which internally realizes a nonlinear model predictive controller (NMPC). We simplify the high dimensional and nonlinear model of the BHA to a computational efficient model which still covers the major effects of the original dynamics. This results not only in a feasible trajectory but also enables the model control loop to be real-time applicable. The proposed method is validated in simulation.

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