scholarly journals The use of a cascaded Kinect and electromyography gesture decoding algorithm in an initial robot-aided hand neurorehabilitation

2018 ◽  
Vol 10 (1) ◽  
pp. 168781401775196 ◽  
Author(s):  
Ping Wang ◽  
Yabo Wang ◽  
He Huang ◽  
Feng Ru ◽  
Quan Pan
Keyword(s):  
Control Algorithm ◽  
Motion Tracking ◽  
Simulation Experiment ◽  
Tracking Error ◽  
Torque Control ◽  
Tracking Accuracy ◽  
Rehabilitation Robots ◽  
Machine Interface ◽  
Repetitive Activities ◽  
Active Assistance

In order to improve the neurological recovery of hand neurorehabilitation, target-oriented, intensive, repetitive activities of daily living are used, such as training with recognition of hand gestures during robot-aided exercise. In this article, a cascade control algorithm integrating electromyography bio-feedback into hand gesture recognition is proposed. The outer loop is the trajectory motion tracking with Kinect-based gesture decoding classifier, and the inner loop is torque control with electromyography bio-feedback in the real time. This proposed method improves the tracking accuracy. The tracking error is effectively reduced from 70.56 to 28.07 in the simulation experiment. The initial test proves that the proposed method with additional torque control allows active assistance on the human–machine interface of other rehabilitation robots in future.

scholarly journals Fuzzy Torque Control of the Bionic Flexible Manipulator Actuated by Pneumatic Muscle Actuators

2019 ◽  
Vol 32 (1) ◽  
Author(s):  
Kai Liu ◽  
Yining Chen ◽  
Jiaqi Xu ◽  
Yang Wu ◽  
Yonghua Lu ◽  
...  
Keyword(s):  
Trajectory Tracking ◽  
Control Algorithm ◽  
Kinematic Model ◽  
Torque Control ◽  
Tracking Performance ◽  
Flexible Manipulator ◽  
Strong Nonlinearity ◽  
Tracking Accuracy ◽  
Pneumatic Muscle ◽  
Computed Torque

Abstract A bionic flexible manipulator driven by pneumatic muscle actuator (PMA) can better reflect the flexibility of the mechanism. Current research on PMA mainly focuses on the modeling and control strategy of the pneumatic manipulator system. Compared with traditional electro-hydraulic actuators, the structure of PMA is simple but possesses strong nonlinearity and flexibility, which leads to the difficulty in improving the control accuracy. In this paper, the configuration design of a bionic flexible manipulator is performed by human physiological map, the kinematic model of the mechanism is established, and the dynamics is analyzed by Lagrange method. A fuzzy torque control algorithm is designed based on the computed torque method, where the fuzzy control theory is applied. The hardware experimental system is established. Through the co-simulation contrast test on MATLAB and ADAMS, it is found that the fuzzy torque control algorithm has better tracking performance and higher tracking accuracy than the computed torque method, and is applied to the entity control test. The experimental results show that the fuzzy torque algorithm can better control the trajectory tracking movement of the bionic flexible manipulator. This research proposes a fuzzy torque control algorithm which can compensate the error more effectively, and possesses the preferred trajectory tracking performance.

scholarly journals Real-Time Tumor Motion Tracking in 3D Using Planning 4D CT Images during Image-Guided Radiation Therapy

Algorithms ◽  
2018 ◽  
Vol 11 (10) ◽  
pp. 155
Author(s):  
Jang-Hwan Choi ◽  
Sooyeul Lee
Keyword(s):  
Real Time ◽  
Motion Tracking ◽  
Tracking Error ◽  
Structural Similarity ◽  
Tracking Accuracy ◽  
Image Guided Radiation Therapy ◽  
Tumor Tracking ◽  
Respiratory Phase ◽  
4D Computed Tomography ◽  
Using Data

In this paper we propose a novel method for tracking the respiratory phase and 3D tumor position in real time during treatment. The method uses planning four-dimensional (4D) computed tomography (CT) obtained through the respiratory phase, and a kV projection taken during treatment. First, digitally rendered radiographs (DRRs) are generated from the 4DCT, and the structural similarity (SSIM) between the DRRs and the kV projection is computed to determine the current respiratory phase and magnitude. The 3D position of the tumor corresponding to the phase and magnitude is estimated using non-rigid registration by utilizing the tumor path segmented in the 4DCT. This method is evaluated using data from six patients with lung cancer and dynamic diaphragm phantom data. The method performs well irrespective of the gantry angle used, i.e., a respiration phase tracking accuracy of 97.2 ± 2.5%, and tumor tracking error in 3D of 0.9 ± 0.4 mm. The phantom study reveals that the DRRs match the actual projections well. The time taken to track the tumor is 400 ± 53 ms. This study demonstrated the feasibility of a technique used to track the respiratory phase and 3D tumor position in real time using kV fluoroscopy acquired from arbitrary angles around the freely breathing patient.

Decoupling motion tracking control for 4WD autonomous vehicles based on the path correction

2021 ◽  
pp. 095440702110159
Author(s):  
Yinghong Yu ◽  
Yinong Li ◽  
Yixiao Liang ◽  
Ling Zheng ◽  
Yue Ren
Keyword(s):  
Autonomous Vehicles ◽  
Motion Tracking ◽  
Tracking Error ◽  
Inverse System ◽  
Tracking Accuracy ◽  
Dynamic Coupling ◽  
Long Distance ◽  
Correction Model ◽  
Decoupling Method ◽  
The Neural Network

Since one control loop input disturbs the control of another loop, the dynamic coupling of the longitudinal and lateral directions adversely affects the motion tracking accuracy of autonomous vehicles. With the ability to minimize the interactions between the longitudinal and lateral dynamics, the inverse system learned by the neural network is an effective way to decouple vehicle dynamics. After tracking the vehicle states projected from the desire motion, the dynamic decoupling and the motion tracking are both realized. However, the accumulation of vehicle state tracking errors causes the stable yaw tracking error and the lateral tracking divergence. To solve the accompanying problem, a path correction model is designed to periodically update the desired vehicle states. Moreover, the applicability of the inverse system decoupling method is improved in this paper, because the method usually adopted in distributed drive electric vehicles is applied to four-wheel driving vehicles representing the traditional driving form. Simulation results indicate that the decoupling motion tracking method with the path correction model is suitable for long-distance and complex conditions and has the highest comprehensive tracking accuracy compared with the integrated MPC (model predictive control) and the pure pursuit in the dynamic coupling conditions.

scholarly journals Resonance Avoidance Control Algorithm for Semi-Submersible Floating Offshore Wind Turbine

Energies ◽  
2021 ◽  
Vol 14 (14) ◽  
pp. 4138
Author(s):  
Kwansu Kim ◽  
Hyunjong Kim ◽  
Hyungyu Kim ◽  
Jaehoon Son ◽  
Jungtae Kim ◽  
...  
Keyword(s):  
Wind Turbine ◽  
Control Algorithm ◽  
Torque Control ◽  
Offshore Wind ◽  
Offshore Wind Turbine ◽  
Resonance Problem ◽  
Exclusion Zone ◽  
Mean Power ◽  
Floating Offshore Wind Turbine ◽  
Avoidance Control

In this study, a resonance avoidance control algorithm was designed to address the tower resonance problem of a semi-submersible floating offshore wind turbine (FOWT) and the dynamic performance of the wind turbine, floater platform, and mooring lines at two exclusion zone ranges were evaluated. The simulations were performed using Bladed, a commercial software for wind turbine analysis. The length of simulation for the analysis of the dynamic response of the six degrees of freedom (DoF) motion of the floater platform under a specific load case was 3600 s. The simulation results are presented in terms of the time domain, frequency domain, and using statistical analysis. As a result of applying the resonance avoidance control algorithm, when the exclusion zone range was ±0.5 rpm from the resonance rpm, the overall performance of the wind turbine was negatively affected, and when the range was sufficiently wide at ±1 rpm, the mean power was reduced by 0.04%, and the damage equivalent load of the tower base side–side bending moment was reduced by 14.02%. The tower resonance problem of the FOWT caused by practical limitations in design and cost issues can be resolved by changing the torque control algorithm.

scholarly journals Implementation and intelligent gain tuning feedback–based optimal torque control of a rotary parallel robot

2021 ◽  
pp. 107754632110191
Author(s):  
Farzam Tajdari ◽  
Naeim Ebrahimi Toulkani
Keyword(s):  
Real Time ◽  
Tracking Error ◽  
Parallel Robot ◽  
Torque Control ◽  
Test Bed ◽  
Linear Quadratic ◽  
Control Effort ◽  
The Real ◽  
Unknown Disturbances ◽  
Quadratic Integral

Aiming at operating optimally minimizing error of tracking and designing control effort, this study presents a novel generalizable methodology of an optimal torque control for a 6-degree-of-freedom Stewart platform with rotary actuators. In the proposed approach, a linear quadratic integral regulator with the least sensitivity to controller parameter choices is designed, associated with an online artificial neural network gain tuning. The nonlinear system is implemented in ADAMS, and the controller is formulated in MATLAB to minimize the real-time tracking error robustly. To validate the controller performance, MATLAB and ADAMS are linked together and the performance of the controller on the simulated system is validated as real time. Practically, the Stewart robot is fabricated and the proposed controller is implemented. The method is assessed by simulation experiments, exhibiting the viability of the developed methodology and highlighting an improvement of 45% averagely, from the optimum and zero-error convergence points of view. Consequently, the experiment results allow demonstrating the robustness of the controller method, in the presence of the motor torque saturation, the uncertainties, and unknown disturbances such as intrinsic properties of the real test bed.

scholarly journals An intelligent method for solar flare observation

2012 ◽  
Vol 8 (S294) ◽  
pp. 503-504
Author(s):  
Jia Ben Lin ◽  
Juan Guo ◽  
Yuan Yong Deng
Keyword(s):  
Fine Structure ◽  
Solar Flare ◽  
Real Time ◽  
Structure Data ◽  
Control Algorithm ◽  
Simulation Experiment ◽  
Hard Disk ◽  
Solar Observatory ◽  
Explosive Phase

AbstractTo capture the fine structure of the flare kernel during it's explosive phase, we design a real time flare onset detecting algorithm named Near Saturation Area Threshold(NSAT), And an automatic CCD parameters control algorithm for the observing software. All the data from CCD, 48f/s, could be saved to the hard disk, and the GPS time of the flare onset also be saved in the log. These methods could avoid the data overflow and grab the fine structure data of the flare kernel. The simulation experiment works well and the software will be put into use in Huairou Solar Observatory soon.

Iterative learning control algorithm for sensor fault nonlinear systems

2020 ◽  
pp. 1-8
Author(s):  
Zimian Lan
Keyword(s):  
Nonlinear Systems ◽  
Iterative Learning Control ◽  
Control Algorithm ◽  
Tracking Error ◽  
Learning Control ◽  
Open Loop ◽  
Iterative Learning ◽  
Sensor Fault ◽  
Initial State ◽  
Control Gain

In this paper, we propose a new iterative learning control algorithm for sensor faults in nonlinear systems. The algorithm does not depend on the initial value of the system and is combined with the open-loop D-type iterative learning law. We design a period that shortens as the number of iterations increases. During this period, the controller corrects the state deviation, so that the system tracking error converges to the boundary unrelated to the initial state error, which is determined only by the system’s uncertainty and interference. Furthermore, based on the λ norm theory, the appropriate control gain is selected to suppress the tracking error caused by the sensor fault, and the uniform convergence of the control algorithm and the boundedness of the error are proved. The simulation results of the speed control of the injection molding machine system verify the effectiveness of the algorithm.

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.

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