공압형 인공근육을 이용한 상극구동의 동적 특성

강봉수(Bong-Soo Kang),송승(Seung Song) 대한기계학회 2009 大韓機械學會論文集A Vol.33 No.10

This paper presents dynamic characteristics of pneumatic artificial muscles. Since the actuating performance of a pneumatic muscle is closely related to the input pressure of a pneumatic muscle, the air flow model on a valve orifice and an elastic bladder of the muscle is formulated to estimate precisely the pressure variance of pneumatic muscles during deflating and inflating process. Frequency response experiments are performed with an antagonistic system consisting of two pneumatic muscles and fast pneumatic control valves. Comparing with experimental results, the proposed model yielded good performance in estimating dynamic motions of the antagonistic system as well as the pressure variance of the pneumatic artificial muscles

Jumping Motion Control of One-legged Jumping Robot with Pneumatic Muscles

Yuta ISHIYAMA,Yuya YAMAMOTO,Atsuo TAKANISHI,Hun-ok Lim 제어로봇시스템학회 2018 제어로봇시스템학회 국제학술대회 논문집 Vol.2018 No.10

This paper describes the dynamic analysis of the vertical jumping motion of a one-legged jumping robot that consists of a hip, a thigh, a shin, and a foot. The jumping robot has two kinds of pneumatic artificial muscles, the mono-articular muscle and the bi-articular muscle. The jumping robot is difficult to obtain the output force of each artificial muscle because each joint force is produced by the plural pneumatic artificial muscles. When the robot jumps, the forces can be projected to the waist. Thus, we developed a method that can calculate the magnitude and direction of the resultant of the forces, and convert the resultant force to the output force of the pneumatic muscles. Vertical jumping simulations are conducted, and the effectiveness of the mathematical modeling is verified.

공압서보밸브를 이용한 인공근육의 제어

서기원,엄태준 순천향대학교 부설 산업기술연구소 2015 순천향 산업기술연구소논문집 Vol.21 No.1

Pneumatic artificial muscle(PAM) chat consists of an elascic bladder and braided cover generates pulling force due to contraction of the tube by similar principle applied to human muscle. This is recently used to robotic system and muscle assistive devices. However, PAM control is very difficult due to non-linearity of pneumatics and compressibility of air and therefore many researchers have presently studied for improvement. This paper presents control of PAM using pneumatic servo valve. The dynamic characteristics of PAM was verified by simulation with the Runge-Kutta 4th method. Also, conjugate gradient method with least square error was applied for system identification and the transfer fiinccion was obtained. The gain and of PD control were determined by Root Locus method such chat damping ratio 0.55 was obtained. The simulation was done to predict the displacement, velocity, volume and pressure by applying PD control. Also, the experiment was carried out by applying the calibration coefficients co operate the servo valve properly. The simulation results by theoretical basis and experimental results were compared and the simulation was verified.

Low-pressure pneumatic muscles: development, phenomenological modeling, and evaluation in assistive applications through sEMG analysis

Aman Arora,Debadrata Sarkar,Amit Kumar,Soumen Sen,Shibendu Shekhar Roy 대한기계학회 2022 JOURNAL OF MECHANICAL SCIENCE AND TECHNOLOGY Vol.36 No.9

Compliant actuators have received much attention from researchers over the last two decades. Specifically, pneumatic artificial muscles (PAMs) have been used in several human-in-loop assistive and rehabilitative devices due to their inherent behavior resembling biological muscles. We presented a lucid customizable fabrication process to develop lowpressure actuated PAMs, named pneumatic silicone tube artificial muscles (pSTAMs), and to cater activity-specific actuator requirements. Two constructions of pSTAMs with varying lengths were rigorously experimented at different pressure-load conditions for their isobaric static and stiffness characterizations. Estimation of bandwidth and use of empirical correction factors in the conventional analytical models for quasi-static characterization of pSTAMs were demonstrated. Lumped parameter-based phenomenological model was employed to closely model their dynamic characteristics. A detailed integrated electromyography analysis with surface electromyography signals from the targeted muscle groups was performed to determine the efficacy of using pSTAMs in two activities.

공압인공근육을 가진 내부형 연속체로봇의 기구식

강봉수(Bong Soo Kang) 대한기계학회 2016 大韓機械學會論文集A Vol.40 No.3

본 연구에서는 공압인공근육을 구동부로 가지는 내부형 연속체로봇의 기구학을 제시한다. 연속체 로봇 단일마디는 세 개 인공근육의 병렬구조로 구성되며, 각 인공근육은 가해지는 공기압력에 의해서 독립적으로 수축하여 근육의 한쪽이 부착된 기준 마디절에 대해서 근육의 다른쪽이 연결된 원격의 마디절의 공간상 운동이 발생한다. 인공근육의 굽힘형상을 고려하여 원격 마디절 중심에서의 방위와 위치를 예측하는 기구식을 유도하였으며, 단일 마디를 여러 층으로 적층하였을 때 로봇 말단장치에서의 방위와 위치도 변환행렬의 곱으로 제시한다. 그리고 인공근육의 길이/압력 변화에 따른 말단장치에서의 속도를 계산하는 자코비안 행렬을 구동부의 위치배열을 고려하여 유도하였고 실제 실험을 통해서 제시한 기구식의 유효성을 검증하였다. This study presents the kinematics of an intrinsic continuum robot actuated by pneumatic artificial muscles. The single section of a developed continuum robot consisted of three muscles in parallel. The contraction of each muscle according to applied air pressure produced spatial motions of a distal plate with respect to a base plate. Based on the bending behaviors of artificial muscles, the orientation and position of the end-effector of a continuum robot were formulated using a transformation matrix. The orientation and position was also determined for a single section of the distal plate. A Jacobian matrix relating the contraction rate or the pressure rate of the muscles to the velocity vector of the end-effector was calculated considering the assembled position of actuators between neighboring sections of the robot. Experimental results showed that the motions of the intrinsic continuum robot were accurately estimated by the proposed kinematics.

딥러닝을 이용한 공압형 인공근육의 모델링 및 정밀제어에 대한 연구

이재승(Jae Seung Lee),김경모(Kyeong Mo Kim),강봉수(Bong Soo Kang) 대한기계학회 2021 大韓機械學會論文集A Vol.45 No.1

본 연구에서는 특성데이타를 가지고 딥러닝 기법을 이용하여 수학적 모델링이 어려운 공압형 인공근육의 동특성을 정확하게 모델링하였다. 제안된 신경망 모델은 학습이 완료된 가중치로 구동력을 빠른 시간에 계산하므로 모델에 기초한 피드포오드 제어기법에 활용이 가능하다. 그리고 신경망 모델을 실시간 제어에 적용하기 위해서 딥러닝이 수행되는 파이썬 프로그램을 서버로 기계시스템의 운동제어를 수행하는 랩뷰 프로그램을 클라이언트로 사용하는 분산된 제어기법을 제시하였다. 실제 공압형 인공근육으로 구동되는 동적시스템에 제안된 제어기법을 적용하여 우수한 궤적추종성능을 보였다. In this study, the dynamic behaviors of pneumatic artificial muscles, which cannot be easily mathematically modeled were accurately predicted using a deep learning technique with characteristic data. As the proposed neural network model calculates the driving force with the weights of the neural network trained off-line, it can be applied to a model-based feedforward control scheme in real-time. In addition, a distributed control architecture, where a Python program for deep learning had the role of a server and a LabVIEW program for motion control had the role of a client, was implemented to a dynamic system driven by a single pneumatic artificial muscle. Experimental results showed that the proposed server/client control architecture with the deep learning model could yield a higher performance in trajectory following.

Recurrent neuro-fuzzy model of pneumatic artificial muscle position

Mahdi Chavoshian,Mostafa Taghizadeh 대한기계학회 2020 JOURNAL OF MECHANICAL SCIENCE AND TECHNOLOGY Vol.34 No.1

In this paper, a dynamic neuro-fuzzy system is proposed toward modeling the pneumatic artificial muscle, which are widely used in robotics and rehabilitation. To benefit from the outstanding advantages of the pneumatic actuators such as high softness and low weightto-force ratio, efficient control of the actuator force as well as its displacement is essential. Attaining a comprehensive model with a satisfactory accuracy in the entire course of the muscle is the most important challenge regarding utilization of the pneumatic artificial muscle in a wide range of the applications. Therefore, an adaptive neuro-fuzzy inference system has been developed for pneumatic artificial muscle modeling. The subtractive clustering method is applied to reduce the number of fuzzy rules without loss of accuracy. To verify the effectiveness of the proposed modeling approach, an experimental setup has been constructed using a vertically suited pneumatic artificial muscle which holds a mass. Input-output data are collected for training and testing the recurrent neuro-fuzzy model. The experimental results demonstrate the desirable performance of the proposed adaptive neuro-fuzzy inference system method in modeling the pneumatic artificial muscle as well as its superiority compared to the mathematical model.

Performance Improvement of Pneumatic Artificial Muscle Manipulators Using Magneto-Rheological Brake

Ahn, Kyoung-Kwan,Cong Thanh, TU Diep,Ahn, Young-Kong The Korean Society of Mechanical Engineers 2005 JOURNAL OF MECHANICAL SCIENCE AND TECHNOLOGY Vol.19 No.3

A novel pneumatic artificial muscle actuator (PAM actuator), which has achieved increased popularity to provide the advantages such as high strength and high power/weight ratio, low cost, compactness, ease of maintenance, cleanliness, readily available and cheap power source, inherent safety and mobility assistance to humans performing tasks, has been regarded during the recent decades as an interesting alternative to hydraulic and electric actuators. However, some limitations still exist, such as the air compressibility and the lack of damping ability of the actuator bring the dynamic delay of the pressure response and cause the oscillatory motion. Then it is not easy to realize the performance of transient response of pneumatic artificial muscle manipulator (PAM manipulator) due to the changes in the external inertia load with high speed. In order to realize satisfactory control performance, a variable damper-Magneto­Rheological Brake (MRB), is equipped to the joint of the manipulator. Superb mixture of conventional PID controller and a phase plane switching control method brings us a novel controller. This proposed controller is appropriate for a kind of plants with nonlinearity, uncertainties and disturbances. The experiments were carried out in practical PAM manipulator and the effectiveness of the proposed control algorithm was demonstrated through experiments, which had proved that the stability of the manipulator can be improved greatly in a high gain control by using MRB with phase plane switching control method and without regard for the changes of external inertia loads.

Improvement of the Control Performance of Pneumatic Artificial Muscle Manipulators Using an Intelligent Switching Control Method

Ahn, Kyoung-Kwan,Thanh, TU Diep Cong The Korean Society of Mechanical Engineers 2004 JOURNAL OF MECHANICAL SCIENCE AND TECHNOLOGY Vol.18 No.8

Problems with the control, oscillatory motion and compliance of pneumatic systems have prevented their widespread use in advanced robotics. However, their compactness, power/weight ratio, ease of maintenance and inherent safety are factors that could be potentially exploited in sophisticated dexterous manipulator designs. These advantages have led to the development of novel actuators such as the McKibben Muscle, Rubber Actuator and Pneumatic Artificial Muscle Manipulators. However, some limitations still exist, such as a deterioration of the performance of transient response due to the changes in the external inertia load in the pneumatic artificial muscle manipulator. To overcome this problem, a switching algorithm of the control parameter using a learning vector quantization neural network (LVQNN) is newly proposed. This estimates the external inertia load of the pneumatic artificial muscle manipulator. The effectiveness of the proposed control algorithm is demonstrated through experiments with different external inertia loads.

공압 인공근육 구동장치의 선형화모델 기반 궤적추적제어

장지성(J. S. Jang),지상원(S. W. Ji),강보식(B. S. Kang) 한국동력기계공학회 2005 한국동력기계공학회 학술대회 논문집 Vol.- No.-

In this study, a position control algorithm being applied to a pneumatic artificial muscle driving apparatus is proposed. The position control algorithm is composed of a feedback controller and a feedforward controller. The feedback controller which feeds back position, velocity and acceleration is derived from the linear model of pneumatic artificial muscle driving apparatus. The feedforward controller is designed to improve position trajectory tracking performance. The effectiveness of the designed controller is proved by experimental results.