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1、徐州工程学院毕业设计外文翻译学生姓名学院名称机电工程学院专业名称机械设计制造及其自动化指导教师2011年5月27日英文原文Adaptive robust posture control of a parallel manipulator driven by pneumatic musclesKeywords:Pneumatic muscleParallel manipulatorAdaptive controlNonlinear robust controlAbstractRather severe parametric uncertainties and uncertain nonlinea
2、rities exist in the dynamic modeling of a parallel manipulator driven by pneumatic muscles. Those uncertainties not only come from the time-varying friction forces and the static force modeling errors of pneumatic muscles but also from the inherent complex nonlinearities and unknown disturbances of
3、the parallel manipulator. In this paper, a discontinuous projection-based adaptive robust control strategy is adopted to compensate for both the parametric uncertainties and uncertain nonlinearities of a three-pneumatic-muscles-driven parallel manipulator to achieve precise posture trajectory tracki
4、ng control. The resulting controller effectively handles the effects of various parameter variations and the hard-to-model nonlinearities such as the friction forces of the pneumatic muscles. Simulation and experimental results are obtained to illustrate the effectiveness of the proposed adaptive ro
5、bust controller. 2008 Elsevier Ltd. All rights reserved.1. IntroductionPneumatic muscle is a new type of flexible actuator similar to human muscle. It is usually made up of a rubber tube and crossweave sheath material. Pneumatic muscles have the advantages of cleanness, cheapness, light-weight, easy
6、 maintenance, and the higher power/weight and power/volume ratios when compared with pneumatic cylinders (Ahn, Thanh, & Yang, 2004). The basic working principle of a pneumatic muscle is as follows: when the rubber tube is inflated, the cross-weave sheath experiences lateral expansion, resulting in a
7、xial contractive force and the movement of the end point position of the pneumatic muscle. Thus, the position or force control of a pneumatic muscle along its axial direction can be realized by regulating the inner pressure of its rubber tube. The parallel manipulator driven by pneumatic muscles (PM
8、DPM) studied in this paper is a new application of pneumatic muscles.It consists of three pneumatic muscles connecting the moving arm of the parallel manipulator to its base platform as shown in Fig. 1. By controlling the lengths of three pneumatic muscles,three degrees-of-freedom (DOF) rotation mot
9、ion of the parallel manipulator can be realized. Such a parallel manipulator combines the advantages of compact structure of parallel mechanisms with the adjustable stiffness and high power/volume ratio of pneumatic muscles, which will have promising wide applications in robotics,industrial automati
10、on, and bionic devices.Many researchers have investigated the precise position control of pneumatic muscles during the past several years.Most of them dealt with the control of single or antagonistic pneumatic muscles. Specifically, Bowler, Caldwell, and Medrano-Cerda (1996), employed an adaptive po
11、le-placement scheme to control a bi-directional pneumatic muscle actuator system, for use on a 7-DOF anthropomorphic robot arm. Cai and Yamaura (1996)presented a sliding mode controller for a manipulator driven by artificial muscle actuators. Kimura, Hara, Fujita, and Kagawa(1997), applied the feedb
12、ack linearization method to the position control of a single-input pneumatic system with a third-order dynamics including the pressure dynamics. Kimoto and Ito (2003)added nonlinear robust compensations to a linear controller in order to stabilize the system globally and achieve robustness to uncert
13、ain nonlinearities. Carbonell, Jiang, and Repperger (2001),Chan, Lilly, Repperger, and Berlin (2003), Repperger, Johnson, andPhillips (1998) and Repperger, Phillips, and Krier (1999), proposed several methods such as fuzzy backstepping, gain-scheduling,variable structure and fuzzy PD+I for a SISO pn
14、eumatic muscle system with a second-order dynamics to achieve asymptotic position tracking. Lilly (2003), Lilly and Quesada (2004) and Lilly and Yang (2005), applied the sliding mode control technique with boundary layer to control pneumatic muscle actuators arranged in bicep and tricep configuratio
15、ns. Tian, Ding, Yang, and Lin(2004), adopted the RPE algorithm to train neural networks for modeling and controlling an artificial muscle system. Hildebrandt,Sawodny, Neumann, and Hartmann (2002); Sawodny, Neumann,and Hartmann (2005), presented a cascade controller for a twoaxis planar articulated r
16、obotic arm driven by four pneumatic muscles.As reviewed above, some of the researchers designed robust controllers without considering the pressure dynamics, while the effect of pressure dynamics is essential for the precise control of pneumatic muscles (Carbonell et al., 2001; Chan et al., 2003; Lilly, 2003; Lilly & Quesada, 2004; Lilly & Yang, 2005; Repperger et al., 1998,1999). Some of the researchers developed
