Design and Validation of a MR-compatible Pneumatic Manipulandum

The combination of functional MR imaging and novel robotic tools may provide unique opportunities to probe the neural systems underlying motor control and learning. Here, we describe the design and validation of a MR-compatible, 1 degree-of-freedom pneumatic manipulandum along with experiments demonstrating its safety and efficacy. We first validated the robot\u27s ability to apply computer-controlled loads about the wrist, demonstrating that it possesses sufficient bandwidth to simulate torsional spring-like loads during point-to-point flexion movements. Next, we verified the MR-compatibility of the device by imaging a head phantom during robot operation. We observed no systematic differences in two measures of MRI signal quality (signal/noise and field homogeneity) when the robot was introduced into the scanner environment. Likewise, measurements of joint angle and actuator pressure were not adversely affected by scanning. Finally, we verified device efficacy by scanning 20 healthy human subjects performing rapid wrist flexions against a wide range of spring-like loads. We observed a linear relationship between joint torque at peak movement extent and perturbation magnitude, thus demonstrating the robot\u27s ability to simulate spring-like loads in situ. fMRI revealed task-related activation in regions known to contribute to the control of movement including the left primary sensorimotor cortex and right cerebellum

Hybrid Motor System for High Precision Position Control of a Heavy Load Plant

The lift up or press process with high precision position control is an important application in industries. An example of the process lift up and press is the process of a machine tool for drilling, milling, or injection. It is difficult to design the mechanism and controller to control the position of the base table accuracy because it needs to control the base position of the system with the weight varying in a large range. Also, the friction in the system would vary in a large range. This lead to low performance of the system in some range of load. Therefore, the new design system utilizes a DC motor and ball screw and pneumatic actuator to create the hybrid motor system for applying to the lift up and press system. The pneumatic actuator is designed to support the heavy load and the DC motor and ball screw is designed to control the position. Then, the developed hybrid motor can be used to improve the performance of the system. The simulation and experiment results show that the developed system can improve the rise time, setting time, and steady state error. Then, the time response of the system with heavy load look similar to the time response of the system with light load. Moreover, the developed hybrid motor technique can apply to the applications such as to control the 3D powder painter tank base position, and the silicon injection system, the 3D print head, which is a challenge system due to the high friction in tube

Development of a Hybrid Powered 2D Biped Walking Machine Designed for Rough Terrain Locomotion

Biped robots hold promise as terrestrial explorers because they require a single discrete foothold to place their next step. However, biped robots are multi-input multi-output dynamically unstable machines. This makes walking on rough terrain difficult at best. Progress has been made with non-periodic rough terrain like stairs or inclines with fully active walking machines. Terrain that requires the walker to change its gait pattern from a standard walk is still problematic. Most walking machines have difficulty detecting or responding to the small perturbations induced by this type of terrain. These small perturbations can lead to unstable gait cycles and possibly a fall. The Intelligent Systems and Automation Lab at the University of Kansas has built a three legged 2D biped walking machine to be used as a test stand for studying rough terrain walking. The specific aim of this research is to investigate how biped walkers can best maintain walking stability when acted upon by small perturbations caused by periodic rough terrain. The first walking machine prototype, referred to as Jaywalker has two main custom actuation systems. The first is the hip ratchet system. It allows the walker to have either a passive or active hip swing. The second is the hybrid parallel ankle actuator. This new actuator uses a pneumatic ram and stepper motor in parallel to produce an easily controlled high torque output. In open loop control it has less than a 1° tracking error and 0.065 RPM velocity error compared to a standard stepper motor. Step testing was conducted using the Jaywalker, with a passive hip, to determine if a walker with significant leg mass could walk without full body actuation. The results of testing show the Jaywalker is ultimately not capable of walking with a passive hip. However, the walking motion is fine until the terminal stance phase. At this point the legs fall quickly towards the ground as the knee extends the shank. This quick step phenomenon is caused by increased speeds and forces about the leg and hip caused by the extension of the shank. This issue can be overcome by fully actuating the hip, or by adding counterbalances to the legs about the hip

Modelling and Simulation of Self-regulating Pneumatic Valves

In conventional aircraft energy systems, self-regulating pneumatic valves (SRPVs) are used to control the pressure and mass flow of the bleed air. The dynamic behavior of these valves is complex and dependent on several physical phenomena. In some cases, limit cycles can occur, deteriorating performance. This paper presents a complex multi-physical model of SRPVs implemented in Modelica. First, the working-principle is explained, and common challenges in control-system design-problems related to these valves are illustrated. Then, a Modelica-model is presented in detail, taking into account several physical domains. It is shown, how limit cycle oscillations occurring in aircraft energy systems can be reproduced with this model. The sensitivity of the model regarding both solver options and physical parameters is investigated

A Study on Active/Passive Pneumatic Actuators for Assistive Systems

The need for intelligent assistive devices is growing. Due to advances in medicine, people are living longer and able to recover from severe neurological incidents, resulting in an increased population with neuromuscular weakness. In workplaces such as assembly lines, there is a high possibility of work-related fatigue or injury, such as when workers squat down or lift their arms during their work tasks. Assistive devices could help remedy loss of strength on their extremities as well as keep the work environment safe and productive, allowing these growing segments of the population in need of the devices to live more self-sufficient, productive, and higher-quality lives.In the design of assistive systems, an important design goal is prolonged operational time, which requires the minimum usage of energy. Energy consumption can be reduced by modifying the mechanical characteristics of assistive systems according to the dynamic characteristics of the human body, which vary considerably between tasks. This dissertation investigates 1) the design of actuators with adjustable mechanical impedance, 2) control strategies to search for, and adjust to, a suitable mechanical impedance for assistance and 3) sensing technologies for classifying the tasks in which the human engages.The first part of this dissertation characterizes a pneumatic variable stiffness actuator named an Active/Passive Pneumatic Actuator (AP2A). The actuator consists of an air cylinder and an array of solenoid valves. These valves and the corresponding switching algorithms tune the chamber pressures and make the AP2A function as a mechanical spring with desired stiffness. The actuator has a low mechanical impedance compared to geared motors, which enables it to achieve efficient interaction. Control strategies of an assistive system with the AP2A are discussed in the second part. This control framework utilizes the characteristics of the AP2A to provide assistance when necessary and to operate transparently (i.e., neither to assist nor to disturb the users) otherwise. Energy consumed by the AP2A and the assisted system is minimized by solving an optimal control problem. Finally, an estimator is introduced to detect assistive timing for the assistive system with the AP2A. This estimator utilizes physiological signals such as surface electromyogram and prior knowledge of a muscular model, classifying if the user is under the specified condition to be assisted by the AP2A. It demonstrates that the user's effort can be saved, also reducing the number of procedures to collect training data for the estimator before using assistive systems. The performance of the actuator, the controller, and the estimator proposed in this dissertation are verified through experiments.From the above, this dissertation contributes to developing the AP2A that provides assistance and saves energy usage of assistive systems by working as a mechanical spring with stiffness optimized for achieving effective interaction under specific conditions. This actuator supports assistive devices that can be deployed in the real world, properly assisting the users when needed

Study on control of a robotic orthosis actuated by pneumatic artificial muscle for gait rehabilitation

芝浦工業大学2019年

Disturbance-Estimated Adaptive Backstepping Sliding Mode Control of a Pneumatic Muscles-Driven Ankle Rehabilitation Robot.

A rehabilitation robot plays an important role in relieving the therapists' burden and helping patients with ankle injuries to perform more accurate and effective rehabilitation training. However, a majority of current ankle rehabilitation robots are rigid and have drawbacks in terms of complex structure, poor flexibility and lack of safety. Taking advantages of pneumatic muscles' good flexibility and light weight, we developed a novel two degrees of freedom (2-DOF) parallel compliant ankle rehabilitation robot actuated by pneumatic muscles (PMs). To solve the PM's nonlinear characteristics during operation and to tackle the human-robot uncertainties in rehabilitation, an adaptive backstepping sliding mode control (ABS-SMC) method is proposed in this paper. The human-robot external disturbance can be estimated by an observer, who is then used to adjust the robot output to accommodate external changes. The system stability is guaranteed by the Lyapunov stability theorem. Experimental results on the compliant ankle rehabilitation robot show that the proposed ABS-SMC is able to estimate the external disturbance online and adjust the control output in real time during operation, resulting in a higher trajectory tracking accuracy and better response performance especially in dynamic conditions