气动机械手的毕业设计翻译

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1、“软”2-自由度平面气动机械手的设计M. Van Damme, R. Van Ham, B. Vanderborght, F. Daerden, and D.Lefeber机器人和多体力学研究团队,机械工程学系, 比利时布鲁塞尔市中心的自由大学michael.vandammevub.ac.be摘要本文提出这样一个的概念，即使是重量很轻的机械手也能够直接和操作员一起，协助他处理沉重的货物。该系统的优点是：符合人类工程学、重量轻、成本低、操作简便并且能很好的保护操作人员的安全。执行机构采用了褶皱式气动人工肌肉。我们提供一种使用这种执行机构设计的机械手的小型模型，以及用于该机构的滑模控制器。关键词:

2、气动人工肌肉,滑模控制。1引言徒手搬运物料的工作,比如搬起和移动重物,或搬运重物的时候长时间保持一个姿势是导致常见的腰部疾病和其他健康问题的原因。事实上，人工搬运已与大部分腰部受伤，占所有工人伤病赔偿的16-19，同时也是所有与工作相关的赔偿的33-411。这个问题不但使得受伤工人的生活质量受到很严重影响，而且它也是一个很大的经济的支出。传统的解决方案是使用市售的机械手系统。这些系统大多采用配重，这就限制了它用于一些特定的重量负荷的工作。为了提高安全性和工人的生产力，在机器人专业领域已经在研究其他几种机器人辅助操纵的方法 2，3，4。在这些研究过程中开发的设备都是属于一些材料处理设备，这些设备

3、被称为智能辅助装置（IADS）。然而，这些设备大多是沉重的，不仅结构复杂而且造价昂贵。在本文中，我们提到的机械手初步的设计和控制，最终将结合人体工程学，操作安全，成本低，重量轻和易于操作和控制。所有这一切都可以通过布鲁塞尔自由大学的机械工程系开发的褶皱气动人工肌肉（PPAM）5执行机构来实现，这是一种一由压缩空气驱动的可收缩的装置。我们正努力实现让这个系统能做到这样一点：当操作员希望移动机器手上的重物,那么他/她就可以像没有机械手一样开始移动它。该系统通过测量肌肉压力表的压力值，可以不断估计由操作员应用的力量，并协助他/她在完成所需的负荷动作。操作员和负载（不含中介控制工具）之间的直接互动，可

4、以实现非常精确的定位。在人们眼中使用任何机械设备的主要要求就是安全。 PPAM驱动器非常有助于提高操纵系统的整体安全性：它允许轻量的工作，没有触电的危险，最重要的是，肌肉本身和它是相容的。在本文中，为了证明这种机械手而设计了一个小型的概念模型，模型由两个PPAM驱动的反肘装配链接组成，为一个滑模控制器的系统进行开发和测试。系统显示如图1。图1。机械手的规模模式2机器人的设计2.1简介我们的目标是设计一个在垂直平面内能提供帮助的机器。这意味着就两个驱动能满足自由度的要求。我们考虑了三种可能的连接配置：肘，反肘和菱形。由于设计上考虑到重量应尽可能轻，结构尽可能简单，这样的话菱形的配置显然是不适合的

5、。作为操作员将可以直接和机械手互动，这一点也非常重要，机器手臂不能妨碍到操作员的动作。出于这个原因，我们选择了肘这种配置。为了方便开发和测试，并获得与这种类型的系统的经验，我们决定先开发一个小型机器人。选择两个环节的长度是30厘米。2.2设计图2显示了逆肘配置中的两个环节的的示意图。图中还包括约定了一个惯例，本文剩余的部分是如何定义两个关节角度和如何对不同气动肌肉进行编号的。图2 逆肘的配置因为我们有四个PPAMs，有8个附着点。每个点的位置可以由两个坐标来描述。每块肌肉有两个参数（长细比和最大长度）。这意味着有一共有24个待定参数。确定最好的设计意味着需要在全球24维参数空间中发现一个最好的

6、，受到条件影响，如产能，空间冲突的情况下，避免肌肉过度负荷，确保有足够大的工作区，.这已被证明是难以计算的。因此，不同的参数进行手动选择，主要是经过广泛的计算机实验之后便于生产。2.2.1转矩特性一旦所有附着点的位置和PPAM参数能够确定下来，我们就可以判断这两个关节的扭矩特性。由于PPAM肌肉使用非线性收缩压力的关系（见5，6），那么由肌肉产生的扭矩可以写成 (1)=肌肉1和2与=肌肉3和4。方程（1）证实了在两个确定扭矩因素之间有一个明显的差别：表面压力和扭矩函数m之间的关系取决于其设计参数和两者的位置。扭矩功能表示如图3。在7中可以找到更多细节。图3扭矩功能3 控制3.1 简介我们所使用

7、的褶皱气动人工肌肉，它的控制器的设计并不简单。在设计控制器时所遇到的困难包括以下内容：机械臂及其驱动器具有很强的非线性系统。PPAMs上的测量也表明在力-压力特性上略有滞后。这使得当仅仅提供压力测量值的情况下难以估算它的驱动力。驱动器的压力表压力可以采取一个比较长的时间来实现（大约需要100毫秒较大的压力来进行操作）。执行机构的外观和数据（细长）不是很知名。在本文中，我们描述了一个滑动模式的方法控制系统。3.2 P-方法必须计算执行器输出，以减少数量，P的方法适用于6,8。这涉及到平均压力，使用一对针对性的肌肉和控制器，通过一个肌肉增加一个（p +p）并且另一个肌肉减去一个（P-P），来计算压

8、力差P。的选择影响符合，同时P可以用于判断关节位置。驱动机构自己处理压力都是通过现成的比例压力调节阀内部的PID控制器来进行控制的。3.3 控制器2自由度平面机械臂的动力学模型是众所周知的，并且可以写成： （2）其中 为关节角度的载体，H是惯性矩阵，C是离心力矩阵（离心力和科里奥利力）和G是引力的载体。 为代表执行器的扭矩矢量，可以写成： （3）肌肉i与压力表的压力 （i= 1.4),还有与肌肉的扭矩功能 （见2.2.1节）。压力表的压力是由压力调节阀来控制的。为简单起见，我们为一阶系统的阀门进行建模。 P的方法相结合，这给了我们以下的阀门模型： （4）将P1和P2分别输入上下臂关节。并且结合

9、方程（2），（3）和（4），这样就为我们提供了完整的控制系统来进行建模。这个系统不是一个允许直接应用滑模控制技术 9中所述的技术（SISO系统）是假设系统的形式为 ，它的状态向量为，x为输出的标量和U为输入的标量。因此，状态向量只包含输出和第n-1个衍生物，和一个具有区分输入输出量的n次方出现（这意味着该系统具有严格的相对次数n10）。我们的系统的状态向量还包含压力表的压力，这当然没有系统的关节角度（输出）的衍生物。的形式，正如在实例9中的介绍。为了解决这个问题，我们把两个（耦合）SISO系统组成的系统，把他们写成： （5） （6）与i= 1，2（上臂1，下臂2）， 的状态向量， 标量输入和

10、的系统的输出。现在，我们可以改变这些系统在10中描述的的一般使用程序形式。坐标分别写成 ， ， ， 与 满足 代表了F 关于h的李导数。，我们就可以得到以下两个系统（i = 1，2）：跟 、 和 一起。为了设计滑模控制器可以使得这些系统跟踪各自所需的输出轨迹 ，我们使用 来定义滑动面 ： （7） （8）从上述公式（7）（8）当中，我们已经确定了一个事实，即这两个系统有严格的相对程度3（见10），这意味着 和 。选择系数 和 以便凑成赫尔维茨 一个有正系数并且根是为负数，或者有成对的共轭负实部的多项式。多项式 。如果轨迹的滑动面（如SI= 0），错误往往会呈指数性的消失。通过选择控制规律，在初始

11、条件有限的时间内使滑动面的吸引，我们可以实现我们的控制目标。其中的一种可能性是（见10）：如果K是大到足以克服系统的不确定性和扰动，si将在有限时间内趋于零。为了减少抖振，引入边界层，并且（见9）将sgn(si)替换为sat(si/i)，i是一个由边界层的宽度决定的常数。3.4 结果为了评估以及为滑模控制器的跟踪性能提供建议，滑膜控制器被用来跟踪一个处在X-Y空间圆圈。需要在5秒内进行轨迹跟踪。为了处理抖振，必须要有一个重大边界层（1= 4，2= 3），当然这会增加一些跟踪误差。由此产生的路径如图4所示。图4 空间跟踪路径。4 结论提出了一个小规模的，轻盈褶气动人工肌肉驱动的机械臂设计。还对滑

12、动模跟踪系统控制器提出了建议，并提出初步跟踪结果。关于抖振的问题，只要能够限制跟踪精度可以达到需求。参考文献1. W.S. Marras, K.P. Granata, K.G. Davis, W.G. Allread, and M.J. Jorgensen (1999) Effects of box features on spine loading during warehouse order selecting. Ergonomics, vol. 42, no. 7, pp. 980996.2. Kevin M. Lynch and Caizhen Liu (2000) Designing

13、 Motion Guides for Ergonomic Collaborative Manipulation. IEEE International Conference on Robotics and Automation.3. H. Kazerooni (1996) The human power amplifier technology at the University of California, Berkeley. Journal of Robotics and Autonomous Systems, vol. 19, pp. 179187.4. Jae H. Chung (20

14、02) Control of an operator-assisted mobile robotic system. Robotica, vol. 20, no. 4, pp. 439446.5. Daerden F. and Lefeber D. (2001) The concept and design of pleated pneumatic artificial muscles. International Journal of Fluid Power, vol. 2, no. 3, pp. 4150.6. Frank Daerden (1999) Conception and Rea

15、lization of Pleated Pneumatic Artificial Muscles and their Use as Compliant Actuation Elements. Ph.D. thesis, Vrije Universiteit Brussel.7. Van Damme M., Daerden F., and Lefeber D. (2005) A pneumatic manipulator used in direct contact with an operator. In Proceedings of the 2005 IEEE International C

16、onference on Robotics and Automation, Barcelona, Spain, pp. 45054510.8. Daerden F., Lefeber D., Verrelst B., and Van Ham R. (2001) Pleated pneumatic artificial muscles: actuators for automation and robotics”. In IEEE/ASME International Conference on Advanced Intelligent Mechatronics, Como, Italy, pp

17、. 738743.9. J.-J. Slotine and W. Li (1991) Applied Nonlinear Control. Prentice Hall.10. Sastry, S. (1999) Nonlinear Systems Analysis,Stability and Control. Springer.英文原版Design of a “Soft” 2-DOF Planar Pneumatic ManipulatorM. Van Damme, R. Van Ham, B. Vanderborght, F. Daerden, and D.LefeberRobotics a

18、nd Multibody Mechanics Research Group, Department of Mechanical Engineering, Vrije Universiteit Brussel, Belgium michael.vandammevub.ac.beAbstractThis paper presents the concept of a lightweight manipulator that can interact directly with an operator in order to assist him in handling heavy loads. T

19、he advantages of the system, ergonomics, low weight, low cost, ease of operation and operator safety are a consequence of the use of Pleated Pneumatic Artificial Muscles as actuators. The design of a smalls cale model of such a manipulator using these actuators is presented, as well as a sliding mod

20、e controller for the system.Keywords: Pneumatic artificial muscles, sliding mode control.1 IntroductionManual material handling tasks such as lifting and carrying heavy loads, or maintaining static postures while supporting loads are a common cause of lower back disorders and other health problems.

21、In fact, manual material handling has been associated with the majority of lower back injuries, which account for 16-19% of all workers compensation claims, while being responsible for 33-41% of all work-related compensations 1. The problem has an important impact on the quality of life of affected

22、workers, and it presents an important economic cost.The traditional solution is using a commercially available manipulator system. Most of these systems use a counterweight, which limits their use to handling loads of a specific mass.In order to increase safety and productivity of human workers, sev

23、eral other approaches to robot-assisted manipulation have been studied in the robotics community 2, 3, 4. The devices developed in the course of these studies belong to a class of materials handling equipment called Intelligent Assist Devices (IADs). Most of these systems, however, are heavy, comple

24、x and expensive.In this paper we present the initial design and control of a manipulator that will eventually combine ergonomics, operator safety, low cost, low weight and ease of operation. All of this can be achieved through the use of an actuator, developed at the Department of Mechanical Enginee

25、ring at the Vrije Universiteit Brussel: the Pleated Pneumatic Artificial Muscle (PPAM) 5, a contractile device operated by pressurized air.We are working towards a system that behaves as follows: when the operator wants to move a load attached to the manipulator, he/she starts moving it as if there

26、were no manipulator. By measuring the muscle gauge pressures, the system continuously estimates the forces applied by the operator and assist him/her in accomplishing the desired load movement. The direct interaction between operator and load (without intermediary control tools) allows for very prec

27、ise positioning.The main requirement for any mechanical device that is used in the immediate environment of people is safety. The PPAM actuators greatly contribute to the overall safety of the manipulator system: they allow for a lightweight construction, there is no danger of electrocution and, mos

28、t important of all, the muscles are inherently compliant.In this paper, the design of a small-scale proof-of-concept model of such a manipulator, consisting of two PPAM actuated links in inverse elbow configuration, is presented and a sliding-mode controller for the system is developed and tested. T

29、he system is shown in Fig. 1.Fig. 1. The manipulator scale model.2 Manipulator design2.1 IntroductionThe goal is to design a machine that will provide assistance in the vertical plane. This means that two actuated degrees of freedom are sufficient. Three possible link configurations were considered:

30、 elbow, inverse-elbow and rhombic. Since the design should be as lightweight and simple as possible, the rhombic configuration isnt suitable. As operator and manipulator will be interacting directly, its important that the manipulator doesnt obstruct the operators movements. For this reason, the elb

31、ow-up configuration was chosen.For easier development and testing, and to gain experience with this type of system, we decided to develop a small-scale manipulator first. The length of both links was chosen to be 30 cm.2.2 DesignFig. 2 shows a schematic representation of the two links in inverse elb

32、ow configuration. The conventions used in the rest of this document regarding to how both joint angles are defined and how the different pneumatic muscles are numbered are also included in the figure.Fig. 2. The inverse elbow configuration.Since we have four PPAMs, there are eight attachment points.

33、 The location of each of these points can be described by two coordinates. Each muscle has two parameters (slenderness and maximum length). This means there are a total of 24 parameters to be determined. Determining the best design means finding a global optimum in a 24- dimensional parameter space,

34、 subject to conditions such as producibility, absence of space conflicts, avoiding excessive muscle loading, ensuring a large enough working area,. This has proven to be computationally intractable. Therefore, the different parameters were chosen manually, mainly with ease of production in mind, aft

35、er extensive computer experiments.2.2.1 Torque characteristicsOnce all attachment point locations and PPAM parameters are known, we can determine the torque characteristics of both joints. Using the nonlinear force-pressure-contraction relation of the PPAM muscle (see 5, 6), torque generated by a mu

36、scle can be written as (1)with = for muscles 1 and 2 and = for muscles 3 and 4. Equation (1) provides a clear separation between the two factors that determine torque: gauge pressure and a torque function m, that depends on the design parameters and the position. The torque functions are shown in Fi

37、g. 3. More details can be found in 7.Fig. 3. Torque functions.3 Control3.1 IntroductionWhen using pleated pneumatic artificial muscles, controller design is not straightforward. Difficulties encountered when designing a controller include the following: Both the manipulator and its actuators are str

38、ongly nonlinear systems. Measurements on PPAMs also show a slight hysteresis in the force-pressure characteristic. This makes it hard to estimate actuator force when only pressure measurements are available. Actuator gauge pressures can take a relatively long time to settle (around 100 ms for large

39、pressure steps). Actuator paramters (slenderness) are not very well known.In this paper, we describe a sliding mode approach to control the system.3.2 p - approachTo reduce the number of actuator outputs that have to be calculated, the p-approach was used 6, 8. This involves choosing an average pres

40、sure pm for both muscles of an antagonistic pair, and having the controller calculate a pressure difference p that is added in one muscle (p+p) and subtracted in the other (pp). The choice of pm influences compliance while p determines joint position. The control of the actuator pressures themselves

41、 is handled by off the shelf proportional pressure regulating valves with internal PID controllers.3.3 ControllerThe dynamical model of a 2-DOF planar arm is well known, and can be written as (2)where q = q1 q2T is the vector of joint angles, H is the inertia matrix, C is the centrifugal matrix (cen

42、trifugal and coriolis forces) and G is the gravitational force vector. is a vector representing the actuator torques, and can be written as (3)with pi (i = 1. . . 4) the gauge pressure in muscle i, and mi the torquefunction associated with that muscle (see section 2.2.1).The gauge pressures are dete

43、rmined by the pressure regulating valves. For simplicity, we model the valves as first order systems. Combined with the p-approach, this gives us the following valve model: (4)p1 and p2 are the inputs for upper and lower arm joints, respectively. Combining equations (2), (3) and (4) gives us the com

44、plete model of the system to be controlled.This system is not in a form that allows direct application of sliding mode control techniques1, such as described in for instance 9. To solve this, we treat the system as consisting of two (coupled) SISO systems, writing them as(5)(6)with i = 1, 2 (1 for u

45、pper arm, 2 for lower arm), xi = qi qi p2i1 p2i the state vector, ui = pi the scalar input and yi = hi(xi) = qi the system output. We can now transform these systems to the normal form using a procedure described in 10. Written in the coordinates i1 = hi (xi), i2 = Lfihi (xi), i3 = Lfi (Lfihi) (xi)

46、= L2fi hi (xi), i (xi) with i (xi) satisfying Lgii (xi) 0 2, we get the following two systems (again, i = 1, 2): with bi (i, i) = L3 fi hi (xi), ai (i, i) = LgiL2 fi hi (xi) and ri (i, i) = Lfii (xi).To design a sliding mode controller that makes these systems track their respective desired output t

47、rajectories yim (t) = qim (t), we use ei0 (t) = yim (t) yi (t) to define the sliding surfaces si (xi, t):(7) (8)In going from (7) to (8), we have used the fact that both systems have strict relative degree 3 (see 10), which implies Lgiqi = 0 and LgiLfiqi =1 The technique outlined in 9 (for a SISO sy

48、stem) supposes the system is in the form x(n) = f(x)+b(x)u, with state vector x = hx x x(n1)iT , x being the scalar output and u the scalar input. Thus, the state vector only contains the output and its first n1 derivatives, and one has to differentiate the output n times for the input to appear (wh

49、ich means the system has strict relative degree n 10). Our systems state vector also contains the gauge pressures, which are of course no derivatives of the joint angles (outputs) of the system.2 Lfh (x) = hxf stands for the Lie derivative of h with respect to f. 0. The coefficients i0 and i1 are ch

50、osen so that the polynomials p2 + i1p + i0 are Hurwitz3. If the trajectory is on the sliding surface (if si = 0), the error will tend to zero exponentially. By selecting a control law that makes the sliding surface attractive to the initial conditions in finite time, we can achieve our control objec

51、tive. One possibility is (see 10):If K is large enough to overcome system uncertainty and perturbations, si will tend to zero in finite time. To reduce chattering, a boundary layer (see 9) is introduced by replacing sgn (si) with sat(si/i), whereand i are constants determining the width of the bound

52、ary layers.3.4 ResultsTo evaluate the tracking performance of the proposed sliding mode controller, it was used to track a circle in xy space. The desired trajectory was tracked in a period of 5 seconds. In order to deal with chattering, significant boundary layers were necessary (1 = 4, 2 = 3), whi

53、ch of course increases tracking error. The resulting path is shown in Fig. 4.Fig. 4. Spatial tracking behaviour.3 A polynomial with real positive coefficients and roots which are either negative or pairwise conjugate with negative real parts.4 ConclusionThe design of a small-scale, lightweight manip

54、ulator actuated by Pleated Pneumatic Artificial Muscles was presented. A sliding mode tracking controller for the system was also proposed, and initial tracking results were presented. The problem of chattering limits the tracking precision that can be achieved.References1. W.S. Marras, K.P. Granata

55、, K.G. Davis, W.G. Allread, and M.J. Jorgensen (1999) Effects of box features on spine loading during warehouse order selecting. Ergonomics, vol. 42, no. 7, pp. 980996.2. Kevin M. Lynch and Caizhen Liu (2000) Designing Motion Guides for Ergonomic Collaborative Manipulation. IEEE International Confer

56、ence on Robotics and Automation.3. H. Kazerooni (1996) The human power amplifier technology at the University of California, Berkeley. Journal of Robotics and Autonomous Systems, vol. 19, pp. 179187.4. Jae H. Chung (2002) Control of an operator-assisted mobile robotic system. Robotica, vol. 20, no.

57、4, pp. 439446.5. Daerden F. and Lefeber D. (2001) The concept and design of pleated pneumatic artificial muscles. International Journal of Fluid Power, vol. 2, no. 3, pp. 4150.6. Frank Daerden (1999) Conception and Realization of Pleated Pneumatic Artificial Muscles and their Use as Compliant Actuat

58、ion Elements. Ph.D. thesis, Vrije Universiteit Brussel.7. Van Damme M., Daerden F., and Lefeber D. (2005) A pneumatic manipulator used in direct contact with an operator. In Proceedings of the 2005 IEEE International Conference on Robotics and Automation, Barcelona, Spain, pp. 45054510.8. Daerden F.

59、, Lefeber D., Verrelst B., and Van Ham R. (2001) Pleated pneumatic artificial muscles: actuators for automation and robotics”. In IEEE/ASME International Conference on Advanced Intelligent Mechatronics, Como, Italy, pp. 738743.9. J.-J. Slotine and W. Li (1991) Applied Nonlinear Control. Prentice Hall.10. Sastry, S. (1999) Nonlinear Systems Analysis,Stability and Control. Springer.