Design and Experimental Evaluation of a Robust Force Controller for a 6-Link Electro-Hydraulic Manipulator Via H_∞ Control Theory

KyoungKwan Ahn,ByungRyong Lee,SoonYong Yang 대한기계학회 2003 JOURNAL OF MECHANICAL SCIENCE AND TECHNOLOGY Vol.17 No.7

Uninterrupted power supply has become indispensable during the maintenance task of active electric power lines as a result of today's highly information-oriented society and increasing demand of electric utilities. This maintenance task has the risk of electric shock and the danger of falling from high place. Therefore it is necessary to realize an autonomous robot system using electro-hydraulic manipulators because hydraulic manipulators have the advantage of electric insulation and power/mass density. Meanwhile an electro-hydraulic manipulator using hydraulic actuators has many nonlinear elements, and its parameter fluctuations are greater than those of an electrically driven manipulator. So it is relatively difficult to realize not only stable contact work but also accurate force control for the autonomous assembly tasks using hydraulic manipulators. In this paper, the robust force control of a 6-link electro-hydraulic manipulator system used in the real maintenance task of active electric lines is examined in detail. A nominal model for the system is obtained from experimental frequency responses of the system, and the deviation of the manipulator system from the nominal model is derived by a multiplicative uncertainty. Robust disturbance observers for force control are designed using this information in an H_∞ framework, and implemented on the two different setups. Experimental results show that highly robust force tracking by a 6-link electro-hydraulic manipulator could be achieved even if the stiffness of environment and the shape of wall change.

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

KyoungKwan AHN,TU Diep Cong Thanh 대한기계학회 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<br/> 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.<br/> To overcome this problem, a switching algorithm of the control parameter using a learning vector quantization neural network (L VQNN) 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.

Intelligent Switching Control of Pneumatic Cylinders by Learning Vector Quantization Neural Network

Ahn KyoungKwan,Lee ByungRyong The Korean Society of Mechanical Engineers 2005 JOURNAL OF MECHANICAL SCIENCE AND TECHNOLOGY Vol.19 No.2

The development of a fast, accurate, and inexpensive position-controlled pneumatic actuator that may be applied to various practical positioning applications with various external loads is described in this paper. A novel modified pulse-width modulation (MPWM) valve pulsing algorithm allows on/off solenoid valves to be used in place of costly servo valves. A comparison between the system response of the standard PWM technique and that of the modified PWM technique shows that the performance of the proposed technique was significantly increased. A state-feedback controller with position, velocity and acceleration feedback was successfully implemented as a continuous controller. A switching algorithm for control parameters using a learning vector quantization neural network (LVQNN) has newly proposed, which classifies the external load of the pneumatic actuator. The effectiveness of this proposed control algorithm with smooth switching control has been demonstrated through experiments with various external loads.

Automatic Assembly Task of Electric Line Using 6-Link Electro-Hydraulic Manipulators

Kyoungkwan Ahn,ByungRyong Lee,SoonYong Yang 대한기계학회 2002 JOURNAL OF MECHANICAL SCIENCE AND TECHNOLOGY Vol.16 No.12

Uninterrupted power supply has become indispensable during the maintenance task of active electric power lines as a result of today's highly information-oriented society and increasing demand of electric utilities. The maintenance task has the risk of electric shock and the danger of falling from high place. Therefore it is necessary to realize an autonomous robot system using electro-hydraulic manipulator because hydraulic manipulators have the advantage of electric insulation. Meanwhile it is relatively difficult to realize autonomous assembly tasks particularly in the case of manipulating flexible objects such as electric lines. In this report, a discrete event control system is introduced for automatic assembly task of electric lines into sleeves as one of the typical task of active electric power lines. In the implementation of a discrete event control system, LVQNN (linear vector quantization neural network) is applied to the insertion task of electric lines to sleeves. In order to apply these proposed control system to the unknown environment, virtual learning data for LVQNN is generated by fuzzy inference. By the experimental results of two types of electric lines and sleeves, these proposed discrete event control and neural network learning algorithm are confirmed very effective to the insertion tasks of electric lines to sleeves as a typical task of active electric power maintenance tasks.

Comparative Study of Modeling and Identification of the Pneumatic Artificial Muscle (PAM) Manipulator Using Recurrent Neural Networks

KyoungKwan Ahn,Ho Pham Huy Anh 대한기계학회 2008 JOURNAL OF MECHANICAL SCIENCE AND TECHNOLOGY Vol.22 No.7

The paper deals with the PAM manipulator modeling and identification based on autoregressive recurrent neural networks. For the first time, the most powerful types of neural-network-based nonlinear autoregressive models, namely, NNARMAX, NNOE and NNARX models, will be applied comparatively to the PAM manipulator identification. Furthermore, the evaluation of different nonlinear neural network auto-regressive models of the PAM manipulator with different number of neurons in hidden layer is completely discussed. On this basis, the merits of each identified model of the highly nonlinear PAM manipulator have been analyzed and compared. The results show that the nonlinear NNARX model yields better performance and higher accuracy than the other nonlinear NNARMAX and NNOE model schemes. These results can be applied to model and identify not only the PAM manipulator but also to control other nonlinear and time-varying industrial systems.

Intelligent Switching Control of Pneumatic Cylinders by Learning Vector Quantization Neural Network

KyoungKwan Ahn,ByungRyoung Lee 대한기계학회 2005 JOURNAL OF MECHANICAL SCIENCE AND TECHNOLOGY Vol.19 No.2

The development of a fast, accurate, and inexpensive position-controlled pneumatic actuator that may be applied to various practical positioning applications with various external loads is described in this paper A novel modified pulse-width modulation (MPWM) valve pulsing algorithm allows on/off solenord valves to be used in place of costly servo valves A comparison between the system response of the standard PWM technique and that of the modified PWM technique shows that the performance of the proposed technique was significantly Increased A state-feedback controller with position, velocity and acceleration feedback was successfully Implemented as a continuous controller A switching algorithm for control parameters using a learning vector quantization neural network (LVQNN) has newly proposed, which classifies the external load of the pneumatic actuator The effectiveness of this proposed control algorithm with smooth switching control has been demonstrated through experiments with various external loads.

A New Design of Wave Energy Generator Using Hydrostatic Transmission

안경관(Ahn, Kyoungkwan),딩광졍(Dinh, Quangtruong),윤종일(Yoon, Jongil) 한국신재생에너지학회 2010 한국신재생에너지학회 학술대회논문집 Vol.2010 No.11

An innovative design of a floating-buoy wave energy converter (WEC) using hydrostatic transmission (HST), named HSTWEC, is presented in this paper. The system is designed to convert ocean wave fluctuation into electricity by using the HST circuit and an electric generator. Based on the floating-buoy concept, the wave forces the sub-buoy to move up and down. Consequently, the electric power can be obtained from the generator in both the moving directions of the sub-buoy through the HST circuit as shown in Fig. 1. In order to investigate the HSTWEC operations, a mathematical model of the system is indispensible. In addition, the method to control the HSTWEC, including: pump displacement control, tension adjustment control and ballast weight control, is also discussed in this paper. Finally, the design concept as well as simulation results indicated that this HSTWEC design is an effective solution and possible to fabricate for wave energy generation.

MR Brake를 이용한 공압근육매니퓰레이터의 지능제어

안경관(KyoungKwan Ahn),T. D. C. Thanh,안영공(YoungKong Ahn) 한국소음진동공학회 2005 한국소음진동공학회 학술대회논문집 Vol.2005 No.5

GA 를 이용한 전기유압식 가변펌프의 압력제어

안경관(KyoungKwan Ahn),현장환(JangHwan Hyun),조용래(YongRae Cho),오범승(BoemSueng oh) Korean Society for Precision Engineering 2004 한국정밀공학회지 Vol.21 No.9

This study presents a genetic algorithm-based method for optimizing control parameters in the pressure control of electro-hydraulic pump with variable displacement. Genetic algorithms are general-purpose optimization methods based on natural evolution and genetics and search the optimal control parameters maximizing a measure that evaluates the performance of a system. Four control gains of the PI-PD cascade controller for an electro-hydraulic pressure control system are optimized using a genetic algorithm in the experiment. Optimized gains are confirmed by inspecting the fitness distribution which represents system performance in gain spaces. It is shown that genetic algorithm is an efficient scheme in optimizing control parameters of the pressure control of electro-hydraulic pump with variable displacement.

수정 하후변환을 이용한 전선의 중심위치의 인식

안경관 울산대학교 2002 공학연구논문집 Vol.33 No.1

최근 정보사용기기의 급증으로 전력을 안정적으로 공급하는 것이 무엇보다도 중요하다. 특히 안정적인 전력공급을 위하여 활선보수공사를 자율적으로 실현하기 위해 로봇의 자율 제어 기술이 필수적으로 요구되어지고 있다. 본 연구에서는 활선보수공사의 대표작업중 전선의 삽입작업을 대상으로하여, 본 작업을 자율적으로 수행하기 위해 필요한 전선의 3차원 중심위치를 신속, 정확하게 인식하는 알고리즘을 제안한다. 본 연구에서는 기존의 하후변환을 수정하여 2차원 평면에서 전선의 중심위치를 인식하는 알고리즘을 제안하고, 나아가 이를 바탕으로 전선의 3차원 중심 위치를 인식하기 위하여 계산법을 제안한다. 이를 상기 대표작업중 전선의 중심위치의 인식에 응용하여 제안한 인식법의 유효성을 확인하였다. Nowadays it is strongly requested to supply electric power safely and uninterruptedly. For this purpose, a 6-link electro-hydraulic dual-armed manipulator has been developed to realize the maintenance task of active electric power distribution lines autonomously. In order to realize these tasks autonomously, the three dimensional position of target object must be recognized accurately and rapidly. In this report, the insertion task of an electric line into a sleeve is selected as the typical task of the maintenance of active electric power distribution lines and a modified Hough transform method and optimal target position calculation method are newly proposed in order to recognize the center position of the electric line. By the proposed modified Hough transform, the center position of the electric line can be recognized without respect to the noise of image and the shape of electric lines.