scholarly journals A 4-DOF Upper Limb Exoskeleton for Physical Assistance: Design, Modeling, Control and Performance Evaluation

2021 ◽  
Vol 11 (13) ◽  
pp. 5865
Author(s):  
Muhammad Ahsan Gull ◽  
Mikkel Thoegersen ◽  
Stefan Hein Bengtson ◽  
Mostafa Mohammadi ◽  
Lotte N. S. Andreasen Struijk ◽  
...  
Keyword(s):  
Upper Limb ◽  
Tracking Control ◽  
Degrees Of Freedom ◽  
Control Method ◽  
Mechanical Design ◽  
Trajectory Tracking Control ◽  
Upper Limb Exoskeleton ◽  
And Performance ◽  
Physically Disabled People ◽  
Human Upper Limb

Wheelchair mounted upper limb exoskeletons offer an alternative way to support disabled individuals in their activities of daily living (ADL). Key challenges in exoskeleton technology include innovative mechanical design and implementation of a control method that can assure a safe and comfortable interaction between the human upper limb and exoskeleton. In this article, we present a mechanical design of a four degrees of freedom (DOF) wheelchair mounted upper limb exoskeleton. The design takes advantage of non-backdrivable mechanism that can hold the output position without energy consumption and provide assistance to the completely paralyzed users. Moreover, a PD-based trajectory tracking control is implemented to enhance the performance of human exoskeleton system for two different tasks. Preliminary results are provided to show the effectiveness and reliability of using the proposed design for physically disabled people.

scholarly journals Trajectory tracking control of two degrees-of-freedom helicopter based on Udwadia–Kalaba theory

2018 ◽  
Vol 10 (11) ◽  
pp. 168781401880893
Author(s):  
Yinfei Zhu ◽  
Han Zhao ◽  
Hao Sun ◽  
Kang Huang ◽  
Yinghui Dong
Keyword(s):  
Trajectory Tracking ◽  
Tracking Control ◽  
Degrees Of Freedom ◽  
Control Method ◽  
Initial Conditions ◽  
Control Cost ◽  
Trajectory Tracking Control ◽  
Constraint Force ◽  
Two Degrees Of Freedom ◽  
High Control

In this article, by using Lagrange energy method, we establish the dynamical model of a two degrees-of-freedom helicopter, which is subject to holonomic constraints. A control method based on Udwadia–Kalaba theory is proposed to achieve the trajectory tracking control of the 2-degrees-of-freedom helicopter. Different from traditional methods, this method could solve the constraint force of the mechanical system without adding additional parameters such as Lagrange multipliers. When initial conditions are compatible, we can use the nominal control which is based on Udwadia–Kalaba equation to control 2-degrees-of-freedom helicopter in real time. But when initial conditions have incompatibility, the simulation result could produce divergence phenomenon. To solve the trajectory tracking control problem of 2-degrees-of-freedom helicopter under incompatible initial conditions, a modified controller is proposed. We also make simulation contrast by different control methods to validate the effectiveness and superiority of the modified controller. Simulation results show that the modified controller can drive the 2-degrees-of-freedom helicopter to perfectly track the desired trajectory with less control cost and high control accuracy.

scholarly journals Hybrid Impedance-Admittance Control for Upper Limb Exoskeleton Using Electromyography

2020 ◽  
Vol 10 (20) ◽  
pp. 7146
Author(s):  
Lucas D. L. da Silva ◽  
Thiago F. Pereira ◽  
Valderi R. Q. Leithardt ◽  
Laio O. Seman ◽  
Cesar A. Zeferino
Keyword(s):  
Upper Limb ◽  
Degrees Of Freedom ◽  
Control Method ◽  
Hybrid Control ◽  
Impedance Control ◽  
Robotic Arm ◽  
Average Error ◽  
Acceptable Error ◽  
Upper Limb Exoskeleton ◽  
Input Signals

Exoskeletons are wearable mobile robots that combine various technologies to enable limb movement with greater strength and endurance, being used in several application areas, such as industry and medicine. In this context, this paper presents the development of a hybrid control method for exoskeletons, combining admission and impedance control based on electromyographic input signals. A proof of concept of a robotic arm with two degrees of freedom, mimicking the functions of a human’s upper limb, was built to evaluate the proposed control system. Through tests that measured the discrepancy between the angles of the human joint and the joint of the exoskeleton, it was possible to determine that the system remained within an acceptable error range. The average error is lower than 4.3%, and the robotic arm manages to mimic the movements of the upper limbs of a human in real-time.

scholarly journals Bio-Inspired Conceptual Mechanical Design and Control of a New Human Upper Limb Exoskeleton

Robotics ◽  
2021 ◽  
Vol 10 (4) ◽  
pp. 123
Author(s):  
Narek Zakaryan ◽  
Mikayel Harutyunyan ◽  
Yuri Sargsyan
Keyword(s):  
Upper Limb ◽  
Mechanical Design ◽  
Artificial Muscle ◽  
Design Parameters ◽  
Upper Limb Exoskeleton ◽  
System A ◽  
Rehabilitation Robots ◽  
Point Control ◽  
And Control ◽  
Human Upper Limb

Safe operation, energy efficiency, versatility and kinematic compatibility are the most important aspects in the design of rehabilitation exoskeletons. This paper focuses on the conceptual bio-inspired mechanical design and equilibrium point control (EP) of a new human upper limb exoskeleton. Considering the upper limb as a multi-muscle redundant system, a similar over-actuated but cable-driven mechatronic system is developed to imitate upper limb motor functions. Additional torque adjusting systems at the joints allow users to lift light weights necessary for activities of daily living (ADL) without increasing electric motor powers of the device. A theoretical model of the “ideal” artificial muscle exoskeleton is also developed using Hill’s natural muscle model. Optimal design parameters of the exoskeleton are defined using the differential evolution (DE) method as a technique of a multi-objective optimization. The proposed cable-driven exoskeleton was then fabricated and tested on a healthy subject. Results showed that the proposed system fulfils the desired aim properly, so that it can be utilized in the design of rehabilitation robots. Further studies may include a spatial mechanism design, which is especially important for the shoulder rehabilitation, and development of reinforcement learning control algorithms to provide more efficient rehabilitation treatment.

Robust finite-time trajectory tracking control for a space manipulator with parametric uncertainties and external disturbances

2021 ◽  
pp. 095441002110147
Author(s):  
Qijia Yao
Keyword(s):  
Trajectory Tracking ◽  
Finite Time ◽  
Tracking Control ◽  
Disturbance Observer ◽  
Control Method ◽  
Parametric Uncertainties ◽  
External Disturbances ◽  
Trajectory Tracking Control ◽  
Space Manipulator ◽  
Tracking Controller

Space manipulator is considered as one of the most promising technologies for future space activities owing to its important role in various on-orbit serving missions. In this study, a robust finite-time tracking control method is proposed for the rapid and accurate trajectory tracking control of an attitude-controlled free-flying space manipulator in the presence of parametric uncertainties and external disturbances. First, a baseline finite-time tracking controller is designed to track the desired position of the space manipulator based on the homogeneous method. Then, a finite-time disturbance observer is designed to accurately estimate the lumped uncertainties. Finally, a robust finite-time tracking controller is developed by integrating the baseline finite-time tracking controller with the finite-time disturbance observer. Rigorous theoretical analysis for the global finite-time stability of the whole closed-loop system is provided. The proposed robust finite-time tracking controller has a relatively simple structure and can guarantee the position and velocity tracking errors converge to zero in finite time even subject to lumped uncertainties. To the best of the authors’ knowledge, there are really limited existing controllers can achieve such excellent performance under the same conditions. Numerical simulations illustrate the effectiveness and superiority of the proposed control method.

scholarly journals Postural Synergy-Based Exoskeleton Reproducing Natural Human Movements to Improve Upper Limb Motor Control after Stroke

2020 ◽  
Author(s):  
Chang He ◽  
Cai-Hua Xiong ◽  
Ze-Jian Chen ◽  
Wei Fan ◽  
Xiao-Lin Huang
Keyword(s):  
Motor Control ◽  
Upper Limb ◽  
Degrees Of Freedom ◽  
Response Rate ◽  
Human Movement ◽  
Interaction Force ◽  
Human Anatomy ◽  
Clinical Trial Registration ◽  
Upper Limb Exoskeleton ◽  
Human Movements

Abstract Background: Upper limb exoskeletons have drawn significant attention in neurorehabilitation because of anthropomorphic mechanical structure analogous to human anatomy. Whereas, the training movements are typically underorganized because most exoskeletons only control the movement of the hand in space, without considering rehabilitation of joint motion, particularly inter-joint postural synergy. The purposes of this study were to explore the application of a postural synergy-based exoskeleton (Armule) reproducing natural human movements for robot-assisted neurorehabilitation and to preliminarily assess its effect on patients' upper limb motor control after stroke. Methods: We developed a novel upper limb exoskeleton based on the concept of postural synergy, which provided five degrees of freedom (DOF) , natural human movements of the upper limb. Eight participants with hemiplegia due to a first-ever, unilateral stroke were recruited and included. They participated in exoskeleton therapy sessions 45 minutes/day, 5 days/week for 4 weeks, with passive/active training under anthropomorphic trajectories and postures. The primary outcome was the Fugl-Meyer Assessment for Upper Extremities (FMA-UE). The secondary outcomes were the Action Research Arm Test(ARAT), modified Barthel Index (mBI) , and exoskeleton kinematic as well as interaction force metrics: motion smoothness in the joint space, postural synergy error, interaction force smoothness, and the intent response rate. Results: After the 4-weeks intervention, all subjects showed significant improvements in the following clinical measures: the FMA-UE ( p =0.02), the ARAT ( p =0.003), and the mBI score ( p <0.001). Besides, all subjects showed significant improvements in motion smoothness ( p =0.004), postural synergy error ( p =0.014), interaction force smoothness ( p =0.004), and the intent response rate ( p =0.008). Conclusions: The subjects were well adapted to our device that assisted in completing functional movements with natural human movement characteristics. The results of the preliminary clinical intervention indicate that the Armule exoskeleton improves individuals’ motor control and activities of daily living (ADL) function after stroke, which might be associated with kinematic and interaction force optimization and postural synergy modification during functional tasks. Clinical trial registration: ChiCTR, ChiCTR1900026656; Date of registration: October 17, 2019. http://www.chictr.org.cn/showproj.aspx?proj=44420

Dynamic trajectory-tracking control method of robotic transcranial magnetic stimulation with end-effector gravity compensation based on force sensors

2018 ◽  
Vol 45 (6) ◽  
pp. 722-731
Author(s):  
ZeCai Lin ◽  
Wang Xin ◽  
Jian Yang ◽  
Zhang QingPei ◽  
Lu ZongJie
Keyword(s):  
Neural Networks ◽  
Trajectory Tracking ◽  
Tracking Control ◽  
Magnetic Stimulation ◽  
Control Method ◽  
Gravity Compensation ◽  
Trajectory Tracking Control ◽  
End Effector ◽  
Content Type ◽  
Dynamic Trajectory

Purpose This paper aims to propose a dynamic trajectory-tracking control method for robotic transcranial magnetic stimulation (TMS), based on force sensors, which follows the dynamic movement of the patient’s head during treatment. Design/methodology/approach First, end-effector gravity compensation methods based on kinematics and back-propagation (BP) neural networks are presented and compared. Second, a dynamic trajectory-tracking method is tested using force/position hybrid control. Finally, an adaptive proportional-derivative (PD) controller is adopted to make pose corrections. All the methods are designed for robotic TMS systems. Findings The gravity compensation method, based on BP neural networks for end-effectors, is proposed due to the different zero drifts in different sensors’ postures, modeling errors in the kinematics and the effects of other uncertain factors on the accuracy of gravity compensation. Results indicate that accuracy is improved using this method and the computing load is significantly reduced. The pose correction of the robotic manipulator can be achieved using an adaptive PD hybrid force/position controller. Originality/value A BP neural network-based gravity compensation method is developed and compared with traditional kinematic methods. The adaptive PD control strategy is designed to make the necessary pose corrections more effectively. The proposed methods are verified on a robotic TMS system. Experimental results indicate that the system is effective and flexible for the dynamic trajectory-tracking control of manipulator applications.

Prescribed performance trajectory tracking control of dynamic positioning ship under input saturation

2020 ◽  
pp. 014233122092888
Author(s):  
Yuanhui Wang ◽  
Haibin Wang ◽  
Mingyu Fu
Keyword(s):  
Trajectory Tracking ◽  
Tracking Control ◽  
Degrees Of Freedom ◽  
Input Saturation ◽  
Small Neighborhood ◽  
Performance Criteria ◽  
Dynamic Positioning ◽  
Trajectory Tracking Control ◽  
Prescribed Performance ◽  
Control Scheme

This paper investigates concentrates on the trajectory tracking control problem of dynamic positioning (DP) ship, in the presence of the time-varying disturbance and input saturation. Firstly, a simplified mathematical model of three degrees of freedom is established. According to the characteristics of the DP ship, an adaptive backstepping controller which combine the prescribed performance function with disturbance observer is proposed. The control scheme can guarantee the transient and steady state performance of the trajectory tracking and meet the prescribed performance criteria. In addition, an auxiliary dynamic system is introduced into the controller to deal with the input saturation problem of the actuator, so that the DP ship can accomplish the task of trajectory tracking under the condition of actuator constraint. Subsequently, in combination of barrier Lyapunov function (BLF), it is proved that the DP system can stabilize and converge rapidly to the small neighborhood of the equilibrium point, which can achieve the prescribed performance. Finally, the effectiveness of the DP control law is demonstrated by a series of simulation experiments.

Nonlinear and Machine-Learning-Based Station-Keeping Control of an Unmanned Surface Vehicle

2020 ◽  
Author(s):  
Armando J. Sinisterra ◽  
Alexandrea Barker ◽  
Siddhartha Verma ◽  
Manhar R. Dhanak
Keyword(s):  
Machine Learning ◽  
Tracking Control ◽  
Situational Awareness ◽  
Control Method ◽  
Sliding Mode ◽  
Control Technique ◽  
Station Keeping ◽  
Trajectory Tracking Control ◽  
Ongoing Work ◽  
Machine Learning Approach

Abstract This study is part of ongoing work on situational awareness and autonomy of a 16’ WAM-V USV. The objective of this work is to determine the potential and merits of application of two different station-keeping controllers for a fixed-pose motion control of the USV. The assessment includes performance and power consumption metrics tested under harsh environmental disturbances to evaluate the robustness of the control methods. The first is a nonlinear trajectory-tracking control method based on the sliding-mode control technique, while the second method uses a machine-learning approach based on Deep Reinforcement Learning. Results from both the approaches are compared for various case studies.

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