Design of an admittance control with inner robust position control for a robot-assisted rehabilitation system RehabRoby

2011 ◽  
Author(s):  
Fatih Ozkul ◽  
Duygun Erol Barkana
Keyword(s):  
Position Control ◽  
Admittance Control ◽  
Robot Assisted ◽  
Rehabilitation System

Design of admittance controller with sliding mode based on disturbance observer for elbow joint actuated by pneumatic muscles

2020 ◽  
Vol 47 (5) ◽  
pp. 657-667
Author(s):  
Binrui Wang ◽  
Jiqing Huang ◽  
Guoyang Shen ◽  
Dijian Chen
Keyword(s):  
Sliding Mode Control ◽  
Elbow Joint ◽  
Disturbance Observer ◽  
Position Control ◽  
Sliding Mode ◽  
Admittance Control ◽  
Compliance Control ◽  
Content Type ◽  
Joint Compliance ◽  
Active Compliance

Purpose Active compliance control is the key technology for Tri-Co robots (coexisting–cooperative–cognitive robots) to interact with the environment and people. This study aims to make the robot arm shake hands compliantly with people; the paper proposed two closed-loop-compliant control schemes for the dynamic identification of cascade elbow joint. Design/methodology/approach The active compliance control strategy consists of inner and outer loops. The inner loop is the position control using sliding mode control with disturbance observer (SMCDO), in which a new saturation function is designed to replace the traditional signal function of sliding mode control (SMC) law so as to mitigate chatter. The outer loop is the admittance control to regulate the dynamic behaviours of the elbow joint, i.e. its impedance. The simulation is carried out to verify the performance of the proposed control scheme. Findings The results show that the chatter of traditional SMC can be effectively eliminated by using SMCDO with this saturation function. In addition, for the handshake task, the value of threshold force and elbow joint compliance is defined. Then, the threshold force tests, impact tests and elbow-joint compliance tests are carried out. The results show that, in the impedance model, the elbow joint compliance only depends on the stiffness parameters, not on the position control loop. Practical implications The effectiveness of the admittance control based on SMCDO can improve the adaptability of industrial manipulator in different working environments to some degree. Originality/value The admittance control with SMCDO completed trajectory tracking has higher accuracy than that based on SMC.

scholarly journals Adaptive Admittance Control Scheme with Virtual Reality Interaction for Robot-Assisted Lower Limb Strength Training

Machines ◽  
2021 ◽  
Vol 9 (11) ◽  
pp. 301
Author(s):  
Musong Lin ◽  
Hongbo Wang ◽  
Jianye Niu ◽  
Yu Tian ◽  
Xincheng Wang ◽  
...  
Keyword(s):  
Virtual Reality ◽  
Strength Training ◽  
Lower Limb ◽  
Adaptive Controller ◽  
Admittance Control ◽  
Robot Assisted ◽  
Interaction Forces ◽  
Control Scheme ◽  
Lower Limb Strength ◽  
Mobility Difficulty

Muscle weakness is the primary impairment causing mobility difficulty among stroke survivors. Millions of people are unable to live normally because of mobility difficulty every year. Strength training is an effective method to improve lower extremity ability but is limited by the shortage of medical staff. Thus, this paper proposes a robot-assisted active training (RAAT) by an adaptive admittance control scheme with virtual reality interaction (AACVRI). AACVRI consists of a stiffness variable admittance controller, an adaptive controller, and virtual reality (VR) interactions. In order to provide human-robot reality interactions corresponding to virtual scenes, an admittance control law with variable stiffness term was developed to define the mechanics property of the end effector. The adaptive controller improves tracking performances by compensating interaction forces and dynamics model deviations. A virtual training environment including action following, event feedback, and competition mechanism is utilized for improving boring training experience and engaging users to maintain active state in cycling training. To verify controller performances and the feasibility of RAAT, experiments were conducted with eight subjects. Admittance control provides desired variable interactions along the trajectory. The robot responds to different virtual events by changing admittance parameters according to trigger feedbacks. Adaptive control ensures tracking errors at a low level. Subjects were maintained in active state during this strength training. Their physiological signals significantly increased, and interaction forces were at a high level. RAAT is a feasible approach for lower limb strength training, and users can independently complete high-quality active strength training under RAAT.

Modeling and Simulation of Human Walking With Wearable Powered Assisting Device

2013 ◽  
Author(s):  
Siniša Slavnić ◽  
Adrian Leu ◽  
Danijela Ristić-Durrant ◽  
Axel Gräser
Keyword(s):  
Modeling And Simulation ◽  
System Development ◽  
Simulation Software ◽  
Human Walking ◽  
Robot Assisted ◽  
Motion Data ◽  
Rehabilitation System ◽  
Software Modules ◽  
Assisting Device ◽  
Multi Body

For the purpose of developing robot-assisted human walking systems, human and robot walking dynamics are modeled using models of different complexity depending on simulation scenarios in different phases of robotic system development and selected walking parameters to be analyzed. This paper addresses the early modeling and simulation phase of the development of a novel mobile robot-assisted gait rehabilitation system to be used as a demonstrator for a cognitive robot control architecture currently under development. For simulation purposes dynamical models of walking human and powered orthosis are developed in multi-body simulation software (MSC Adams) using the LifeMod plug-in while the control algorithms are developed in Matlab. The paper introduces a novel ROS (Robot Operating System) based communication established between the real system software modules and the simulation environment. The performance evaluation was performed by running the simulation with motion data which were obtained using marker-based motion capture system and which were implemented as ROS node.

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