scholarly journals A New Weight Compensation Model Considering Joint Misalignments Monitored by a Feedforward Impedance Control Method Applied To an Active Upper-Limb Exoskeleton

Author(s):  
Dorian VERDEL ◽  
Simon Bastide ◽  
Nicolas Vignais ◽  
Olivier Bruneau ◽  
Bastien Berret

Abstract Background Active exoskeletons are promising devices for improving rehabilitation procedures in patients. In particular, exoskeletons implementing human limb's weight support (WS) are interesting to restore some mobility in patients with muscle weakness. Using active exoskeletons should result in accurate and generic WS but its effect on human motor control will critically depend on the position of the user within the exoskeleton and the characteristics of the control law. Methods The present study aims at improving WS of the upper limb by providing a weight model considering joint misalignments and a control law including feedforward terms learned from a prior population-based analysis. Three experiments are respectively conducted on 29, 17 and 19 participants who performed posture maintenance and pointing movements with the forearm in the sagittal plane. The first two experiments were used to build an accurate WS control law and the third experiment was conducted to compare the effects of different WS control laws on human movement and assess their quality. During these three experiments, kinematic data and eletromyographic activity of elbow flexors and extensors were measured. Interaction forces were measured with a force/torque sensor placed between the human segment and the robot link. Results The introduction of joint misalignments in the WS model allowed to drastically reduce the model errors in terms of weight estimation. The use of a feedforward architecture based on model and errors learned during experiments, coupled to a force feedback, allowed to reduce model tracking errors in both static and dynamic conditions during vertical movements, which induce substantial variations of gravitational torques. Overall, WS did not affect the general kinematic motion parameters of the participants and decreased the activity of antigravity muscles (flexors). However, WS increased the activation of extensors because weight is usually exploited by humans to accelerate a limb downward. Conclusion A new weight compensation model considering joint misalignments was introduced and data showed their prominent role on WS accuracy and homogeneity. Three WS control laws were compared and results indicated that classical control methods were not sufficient to provide an accurate tracking of the weight model during dynamic vertical movements but that introducing simple feedforward terms learned from previous measures could significantly improve WS accuracy. Accordingly, WS reduced significantly activity in flexors in both static and dynamic conditions. Nevertheless, WS tended to increase the activity of extensors, which might be an important factor in a rehabilitation perspective. Indeed, if the present WS control law will be very helpful to allow patients accelerating the arm upward despite some muscle weakness, it may have an opposite effect when accelerating the arm downward. A partial WS controller could thus be more appropriate in rehabilitation applications.

2021 ◽  
Author(s):  
Dorian VERDEL ◽  
Simon Bastide ◽  
Nicolas Vignais ◽  
Olivier Bruneau ◽  
Bastien Berret

Abstract Active exoskeletons are promising devices for improving rehabilitation procedures in patients and preventing musculoskeletal disorders in workers. In particular, exoskeletons implementing human limb’s weight support are interesting to restore some mobility in patients with muscle weakness and help in occupational load carrying tasks. The present study aims at improving weight support of the upper limb by providing a weight model considering joint misalignments and a control law including feedforward terms learned from a prior population-based analysis. Three experiments, for design and validation purposes, are conducted on a total of 65 participants who performed posture maintenance and elbow flexion/extension movements. The introduction of joint misalignments in the weight support model significantly reduced the model errors, in terms of weight estimation, and enhanced the estimation reliability. The introduced control architecture reduced model tracking errors regardless of the condition. Weight support significantly decreased the activity of antigravity muscles, as expected, but increased the activity of elbow extensors because gravity is usually exploited by humans to accelerate a limb downwards. These findings suggest that an adaptive weight support controller could be envisioned to further minimize human effort in certain applications.


Author(s):  
Dorian Verdel ◽  
Simon Bastide ◽  
Nicolas Vignais ◽  
Olivier Bruneau ◽  
Bastien Berret

Active exoskeletons are promising devices for improving rehabilitation procedures in patients and preventing musculoskeletal disorders in workers. In particular, exoskeletons implementing human limb’s weight support are interesting to restore some mobility in patients with muscle weakness and help in occupational load carrying tasks. The present study aims at improving weight support of the upper limb by providing a weight model considering joint misalignments and a control law including feedforward terms learned from a prior population-based analysis. Three experiments, for design and validation purposes, are conducted on a total of 65 participants who performed posture maintenance and elbow flexion/extension movements. The introduction of joint misalignments in the weight support model significantly reduced the model errors, in terms of weight estimation, and enhanced the estimation reliability. The introduced control architecture reduced model tracking errors regardless of the condition. Weight support significantly decreased the activity of antigravity muscles, as expected, but increased the activity of elbow extensors because gravity is usually exploited by humans to accelerate a limb downwards. These findings suggest that an adaptive weight support controller could be envisioned to further minimize human effort in certain applications.


Robotica ◽  
2016 ◽  
Vol 35 (8) ◽  
pp. 1732-1746 ◽  
Author(s):  
Loris Roveda ◽  
Nicola Pedrocchi ◽  
Federico Vicentini ◽  
Lorenzo Molinari Tosatti

SUMMARYLight-weight manipulators are used in industrial tasks mounted on mobile platforms to improve flexibility. However, such mountings introduce compliance affecting the tasks. This work deals with such scenarios by designing a controller that also takes into account compliant environments. The controller allows the tracking of a target force using the estimation of the environment stiffness (EKF) and the estimation of the base position (KF), compensating the robot base deformation. The closed-loop stability has been analyzed. Observers and the control law have been validated in experiments. An assembly task is considered with a standard industrial non-actuated mobile platform. Control laws with and without base compensation are compared.


Robotica ◽  
2013 ◽  
Vol 31 (8) ◽  
pp. 1275-1283 ◽  
Author(s):  
V. I. Gervini ◽  
E. M. Hemerly ◽  
S. C. P. Gomes

SUMMARYThe design of control laws for flexible manipulators is known to be a challenging problem, when using a conventional actuator, i.e., a motor with gear. This is due to the friction of the nonlinear actuator, which causes torque dead zone and stick-slip behavior, thereby hampering the good performance of the control system. The torque needed to attenuate the vibrations, although calculated by the control law, is consumed by the friction inside the actuator, rendering it ineffective to the flexible structure control. Nonlinear friction varies with different operational conditions of the actuator and a friction compensation mechanism based on these models cannot always keep a good performance. This study proposes a new control strategy using wavelet network to friction compensation. Experimental results obtained with a flexible manipulator attest to the good performance of the proposed control law.


Author(s):  
Kazuhiko Hiramoto ◽  
Taichi Matsuoka ◽  
Katsuaki Sunakoda

A scheduling strategy of multiple semi-active control laws for various earthquake disturbances is proposed to maximize the control performance. Generally, the semi-active controller for a given structural system is designed as a single control law and the single control law is used for all the forthcoming earthquake disturbances. It means that the general semi-active control should be designed to achieve a certain degree of the control performance for all the assumed disturbances with various time and/or frequency characteristics. Such requirement on the performance robustness becomes a constraint to obtain the optimal control performance. We propose a scheduling strategy of multiple semi-active control laws. Each semi-active control law is designed to achieve the optimal performance for a single earthquake disturbance. Such optimal control laws are scheduled with the available data in the control system. As the scheduling mechanism of the multiple control laws, a command signal generator (CSG) is defined in the control system. An artificial neural network (ANN) is adopted as the CSG. The ANN-based CSG works as an interpolator of the multiple control laws. Design parameters in the CSG are optimized with the genetic algorithm (GA). Simulation study shows the effectiveness of the approach.


2014 ◽  
Vol 14 (3) ◽  
pp. 96-109 ◽  
Author(s):  
Faculty of Automatics, Technical Un Enev

Abstract In this paper, two feedback linearizing control laws for the stabilization of the Inertia Wheel Pendulum are derived: a full-state linearizing controller, generalizing the existing results in literature, with friction ignored in the description and an inputoutput linearizing control law, based on a physically motivated definition of the system output. Experiments are carried out on a laboratory test bed with significant friction in order to test and verify the suggested performance and the results are presented and discussed. The main point to be made as a consequence of the experimental evaluation is the fact that actually the asymptotic stabilization was not achieved, but rather a limit cycling behavior was observed for the full-state linearizing controller. The input-output linearizing controller was able to drive the pendulum to the origin, with the wheel speed settling at a finite value


Author(s):  
Rush D. Robinett ◽  
David G. Wilson

This paper develops a distributed decentralized control law for collective robotic systems. The control laws are developed based on exergy/entropy thermodynamic concepts and information theory. The source field is characterized through second-order accuracy. The proposed feedback control law stability for both the collective and individual robots are demonstrated by selecting a general Hamiltonian based solution developed as Fisher Information Equivalency as the vector Lyapunov function. Stability boundaries and system performance are then determined with Lyapunov’s direct method. A robot collective plume tracing numerical simulation example demonstrates this decentralized exergy/entropy collective control architecture.


Entropy ◽  
2019 ◽  
Vol 21 (8) ◽  
pp. 751 ◽  
Author(s):  
Sajede Harraz ◽  
Shuang Cong

In this paper, we propose a Lyapunov-based state feedback control for state transfer based on the on-line quantum state estimation (OQSE). The OQSE is designed based on continuous weak measurements and compressed sensing. The controlled system is described by quantum master equation for open quantum systems, and the continuous measurement operators are derived according to the dynamic equation of system. The feedback control law is designed based on the Lyapunov stability theorem, and a strict proof of proposed control laws are given. At each sampling time, the state is estimated on-line, which is used to design the control law. The simulation experimental results show the effectiveness of the proposed feedback control strategy.


Actuators ◽  
2020 ◽  
Vol 9 (3) ◽  
pp. 63 ◽  
Author(s):  
João Falcão Carneiro ◽  
João Bravo Pinto ◽  
Fernando Gomes de Almeida

Pneumatic linear peristaltic actuators can offer some potential advantages when compared with conventional ones. The low cost, virtually unlimited stroke and easy implementation of curved motion profiles are among those benefits. On the downside, these actuators suffer high mechanical stress that can lead to short service life and increased leakage among chambers during the actuator lifetime. One way to cope with this problem is to impose the force—instead of the displacement—between rollers, as this has been shown to improve the endurance of the hose while reducing leakage during the actuator lifetime. This paper presents closed control loop results using such a setup. Previous studies with linear peristaltic actuators have revealed that, although it is possible to reach zero steady state error to constant references with closed loop control, the dynamic response obtained is very slow. This paper is mainly focused on this topic, namely on the development of several control laws to improve the dynamic performance of the system while avoiding limit cycles. The new developed control law leads to an average time of 1.67 s to reach a 0.1 mm error band in an experiment consisting of a series of 16 steps ranging from 0.02 to 0.32 m in amplitude.


2014 ◽  
Vol 519-520 ◽  
pp. 741-746 ◽  
Author(s):  
Guo Jiang Sun ◽  
Jin Hui Li ◽  
Shi Ming Chen ◽  
Yun Feng Dong

Traditional optimization algorithms can only optimize parameters in control laws. Machine learning method can optimize parameters and evolve satellite attitude control law automatically under certain criterion. Single axis satellite attitude simulation system with noise was built up, which included satellite attitude dynamic model, sensors and actuators model. The control laws inputs were attitude error, attitude errors integral and angular velocity error, and outputs were actuators control instructions. Control laws fitness function was an attitude errors statistical function. With suitable function set selected for genetic programming (GP) and parse tree used to represent a control law expression, GP was used to evolve control law expression automatically. Simulation result shows that this method can evolve control law with uncertainties noise better. The evolved control law response and control precision are better than PID, and it can be used in satellite attitude control.


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