当前位置:文档之家› 2003 6 Position control of a Stewart platform using inverse dynamics control with approximate dynami

2003 6 Position control of a Stewart platform using inverse dynamics control with approximate dynami

2003 6 Position control of a Stewart platform using inverse dynamics control with approximate dynami
2003 6 Position control of a Stewart platform using inverse dynamics control with approximate dynami

Position control of a Stewart platform

using inverse dynamics control with

approximate dynamics

Se-Han Lee,Jae-Bok Song *,Woo-Chun Choi,Daehie Hong

Department of Mechanical Engineering,Korea University,5,Anam-dong,Sungbuk-gu,

Seoul 136-701,Korea

Abstract

Con?guration-dependent nonlinear coe?cient matrices in the dynamic equation of a robot manipulator impose computational burden in real-time implementation of tracking control based on the inverse dynamics controller (IDC).However,parallel manipulators such as a Stewart platform have relatively small workspace compared to serial manipulators.Based on the characteristics of small motion range,nonlinear coe?cient matrices can be approximated to constant ones.The modeling errors caused by such approximation are compensated for by H 1controller that treats the error as disturbance.The proposed IDC with approximate dy-namics combined with H 1control shows good tracking performance even for fast tracking control in which computation of full dynamics is not easy to implement.

ó2002Elsevier Science Ltd.All rights reserved.

Keywords:Stewart platform;Inverse dynamics control;H 1control;Approximate inverse dynamics

1.Introduction

Parallel manipulators such as a Stewart platform [1]has some advantages of high rigidity,high accuracy,and high load-carrying capacity over serial manipulators.These manipulators have found a variety of applications in ?ight and vehicle sim-ulators,high-precision machining centers,mining machines,and so on.However,they have some drawbacks of relatively small workspace and di?cult forward ki-nematics problems.

Mechatronics 13(2003)

605–619

*Corresponding author.Tel.:+82-2-3290-3363;fax:+82-2-3290-3757.

E-mail address:jbsong@korea.ac.kr (J.-B.Song).

0957-4158/03/$-see front matter ó2002Elsevier Science Ltd.All rights reserved.

doi:10.1016/S0957-4158(02)00033-8

606S.-H.Lee et al./Mechatronics13(2003)605–619

Generally,forward kinematics of a parallel manipulator is very complicated and di?cult to solve.Liu et al.[2]proposed a numerical algorithm which provided the kinematic solutions based on a set of three nonlinear simultaneous equations.On the other hand,dynamics of a parallel manipulator,which is very important to develop a controller,tends to be very complicated.Most studies on dynamics have been per-formed based on the Lagrangian formulation[3],the Newton–Euler formulation[4] and the principle of virtual work[5].The above-mentioned dynamic equations were accurate by including actuating legs having closed-loop connections to each other in its formulation,but computation of the dynamics was very time-consuming.Even with a high-speed DSP,therefore,real-time calculation was not easy to achieve in the control system.Some literature[3,4]reported simulation-based control analysis which took into account the dynamics of a Stewart platform,but little mention was made regarding the ways of dealing with computational burden in real-time imple-mentation.Fichter[6]assumed that the e?ect of leg inertia was negligible and ob-tained a simple formula for computing actuating forces for a Stewart platform,but su?cient accuracy could not be attained except when the inertia of the load was much larger than that of the actuating leg.In particular,for the case where the platform was used as a tool holder,the e?ect of leg inertia was no longer negligible and thus accurate modeling of dynamics including legs was required for control performance[7].

Parallel manipulators have some drawback of relatively small workspace in comparison with serial manipulators.This characteristic,however,enables the con?guration-dependent coe?cient matrices of the dynamic equations to be ap-proximated to constant ones without introducing large modeling errors.Based on these constant matrices,calculation of the approximated inverse dynamics becomes much simpler than the full inverse dynamics which re?ects every detail varying in time.This approximation may cause some modeling error,and deteriorate tracking performance of the controller based on the inverse dynamics.In this paper,the error caused by such approximation is treated as disturbance,and the H1controller is introduced to cope with this disturbance.Finally,an inverse dynamics controller (IDC)with approximate inverse dynamics combined with the H1controller is proposed as a position controller for a Stewart platform.

This paper presents a brief derivation of the dynamic equations and the ap-proximation process of the Stewart platform under consideration in Section 2. Section3deals with a proposed IDC with approximate dynamics combined with the H1controller.Section4shows the experimental results and compares control per-formance for various controllers including the proposed one.

2.Dynamic equations of a Stewart platform

In this section,the dynamic equations of a Stewart platform under consideration is brie?y derived based on the Newton–Euler approach,and its characteristics are investigated.

S.-H.Lee et al./Mechatronics13(2003)605–619607

2.1.Derivation of dynamic equations

A Stewart platform shown in Fig.1consists of a moving platform,a?xed base, and six actuating legs connecting the platform to the base.The lower?xed part of an actuating leg is connected to the base through a universal joint,while the upper moving part is connected to the platform through a spherical joint.Two actuating legs are connected together to form a spherical joint as shown in Fig.2.The moving platform frame xyz and the?xed base reference frame XYZ are attached to the platform center and the base center,respectively.Force vectors actuating on a leg are shown in Fig.3.Force balance along the leg direction for leg i is given by m u s iáa u i?F itm u s iágàs iáf iei?1;...;6Te1

T

where F i is the actuator force produced by the electric motor and ball-screw mech-anism,m u the moving part mass of the leg,s i the unit vector along the leg,g the acceleration of gravity,a u i is the moving part acceleration,and f i the actuating force acting on the platform.And árepresents the inner product.

Moment balance of the i th leg with the moment center at B i becomes

em d r d i tm u r u i T?g àL i s i ?f i àm d r d i ?a d i àm u r u i ?a u i àeI d i tI u i Ta i

àx i ?eI d i tI u i Tx i ?0e2Twhere m d is the ?xed part mass of the leg,L i is the leg length,r d i and r u i are the position vectors from B i to the mass centers of the ?xed and moving parts,I d i and I u i are the moments of inertia of the ?xed and moving parts about their mass centers,and a i ,x i are the angular velocity and angular acceleration of leg i ,respectively.

On the other hand,the velocity v P ,acceleration a P ,angular velocity x P ,and angular acceleration a P at the platform center are related kinematically to the ve-locity v Tj and acceleration a Tj at the connection points T j (j ?1;2;3)denoted by the position vector b i as follows:

v Tj ?v P tx P ?eRb j T

e3a Ta Tj ?a P ta P ?eRb j Ttx P ?f x P ?eRb j Tg e3b Twhere R is the rotation matrix to describe rotation of the moving frame xyz relative to the reference frame XYZ .Note that v P ,a P ,x P and a P are expressed in the ref-erence frame XYZ and b j is written in the platform frame xyz .Note that Rb i is now expressed in terms of the reference frame.The variables v Tj and a Tj can also be represented in terms of the leg-related variables

v Tj ?_L s i tL x i ?s i e4a T

a Tj ?€L

i s i ta i ?eL i s i Ttx i ?f x i ?eL i s i Tg t2x i ?_L i s i ej ?1for i ?1;2;j ?2for i ?3;4;j ?3for i ?5;6Te4b

T

Fig.3.Free body diagram of platform and moving part of a leg.

608S.-H.Lee et al./Mechatronics 13(2003)605–619

where _L

and €L are the leg elongation velocity and acceleration,respectively.Equating Eqs.3a,3b and 4a,4b,the angular velocity x i and angular acceleration a i of each leg can be described by the platform-related variables v P ,a P ,x P ,and a P .Based on this,the actuating force f i can be described via some matrices Q 1i ,Q 2i ,and Q 3i as follows:

f i ?Q 1i v P x P tQ 2i a P a P

tQ 3i F i e5TUsing the forces f i exerted by the six actuating legs,the following force and moment balances for a Stewart platform are obtained

m P a P ?m P g tX

6i ?1

f i e6TI P a P tx P ?eI P x P T?X 6i ?1?eRb i T?f i

e7T

where m P is the platform mass.Eqs.(6)and (7)may be combined into the following equation in the matrix-vector form

m P I 300I P a P a P ?m P g tP f i àx P ?eI P x P TtP eRb i T?f i

e8Twhere I P is the moment of inertia of the platform and I 3denotes the 3?3identity matrix.Replacing f i on the right-hand side by F i using Eq.(5),and denoting the position,velocity,and acceleration by the single vectors X ,_X ?f v T P x T P g T ,€X ?f a T P a T P g T ,the dynamic equation of a Stewart platform in task space is obtained by

M eX T€X th eX ;_X T?J T F e9T

where M eX Tis the inertia matrix,h eX ;_X

Tis the nonlinear term including Coriolis,centrifugal,and gravity force,and F ?f F 1;...;F 6g T is the actuator force vector,respectively.And J is the Jacobian matrix associated with the relation J _X ?_L ,where _L

?f _L 1;...;_L 6g T is the leg velocity vector.J ?s 1s 2ááás 6Rb 1?s 1Rb 2?s 2áááRb 6?s 6

T e10TIt is noted that J T F represents the actuating force in task space which is converted from the leg force F .

2.2.Characteristics of dynamic equations

The dynamic equation (9)of a Stewart platform has the following characteristics.The inertia matrix M eX Tis dependent only on the con?guration of the platform and the nonlinear term h eX ;_X

Tdepends on both the position and velocity of the platform.Because the workspace of a Stewart platform is relatively small,the S.-H.Lee et al./Mechatronics 13(2003)605–619609

variable X and its function M eX Tvaries in a small range as well.The inertia matrix,therefore,can be assumed to be constant with introduction of some modeling error.

On the other hand,the nonlinear term h ,which includes Coriolis,centrifugal,and gravity force,requires most computational burden in the inverse dynamics calcu-lation.It can be described by [8]

h eX ;_X T?_X T H 1eX T_X ..._X T H 6eX T_X

8><>:9>=>;tG eX Te11Twhere H i eX Tis the 6?6square matrix,and G eX Tis the 6?1gravity force vector.If H i eX Tcan be assumed to be constant as H i eX T%H c i ,h eX ;_X

Tcan be approximated by

h eX ;_X T?^h e_X TtD h ;where ^h e_X T?_X T H c1_X ..._X T H c6_X

8><>:9>=>;tG eX Te12TNote that the gravitational term G eX Tcan be accurately computed since the variable X can be obtained accurately by the high-resolution optical encoder.With this ap-proximation,the complicated inverse dynamics computation is accomplished by relatively simple operations.

The modeling error introduced as a result of this approximation depends on the types of tasks.In general,the larger change in con?guration,the greater error will be generated.Suppose that the platform center is to follow a given circular track (refer to Section 4.1for details).The maximum singular values of H i eX Tin Eq.(11)and the di?erence D H i between H i eX Tand the constant matrix H c i are illustrated in Fig.4.Since the elements of H i eX Trepresent the coe?cients which map the quadratic ve-locities into force or torque,the singular values of H i eX Talso have the same

di-610S.-H.Lee et al./Mechatronics 13(2003)605–619

mension.It is observed that r max eD H i Tis less than 10%of r max eH i eX TT.In Eq.(12),therefore,the nonlinear term requiring most computation time in the inverse dynamics calculation can be reduced to multiplication operations of the constant matrices and the velocities detected by the sensor.

The constant matrix H c i is determined properly depending on the task trajectories.For example,for tracking of a circular trajectory,these matrices can be computed o?-line for the con?guration at the center of the circle and then these matrices are used in real-time calculation.

3.Controller design of a parallel manipulator

3.1.Inverse dynamics controller

The IDC [9],or also called computed-torque controller,which is a popular po-sition controller for a serial manipulator is considered in this research as a main position control scheme.The IDC produces good control performance with accurate modeling of the manipulator.When the modeling is not su?ciently accurate,how-ever,its performance is not generally acceptable.

Fig.5illustrates the IDC based on the dynamic equation (9).As shown in the ?gure,the inner loop computing the inverse dynamics makes the manipulator act as a linear model.The conventional inverse dynamics control law is described by

F ?F c tF h

e13Twhere

F c ?J àT M €X ref tK P eX ref àX TtK D e_X ref à_X TtK I Z eX ref àX Td t

F h ??J àT h eX ;_X

T e14Twhere X ref is the reference trajectory that the platform center is to follow,and K P ,K D ,and K I are the constant controller gain matrices.Note that the term F c is the control force used to track the reference trajectory,while the term F h is used to linearize the plant by canceling nonlinearity.Substitution of Eq.(14)into (9)

yields

S.-H.Lee et al./Mechatronics 13(2003)605–619611

M €X th ?M €X ref tK P eX ref àX TtK D e_X ref à_X TtK I Z eX ref àX Td t

th

e15TThe nonlinear terms h on both sides in Eq.(15)cancel out and thus the following error equation is obtained:€e tK D _e tK P e tK I Z e d t ?0e16Twhere e ?X ref àX represents the error.The matrices K P ,K D ,and K I are determined so that the error vector may approach zero asymptotically.

From a practical point of view,the IDC is hard to implement,since it requires long computation time for the inverse dynamics.If the approximate dynamics are used in which all the coe?cient matrices are assumed to be constant,then the computation time can be reduced drastically with some modeling error introduced.In the case of the DSP running at the 50MHz speed,the proposed approximate dynamics requires less than 1ms,while full dynamics computation needs about 25ms.

3.2.H 1controller

As the approximated model inevitably has some modeling error,stability of the whole control system cannot be guaranteed.Adaptive control [10]and sliding mode control [11]schemes can be employed to cope with the modeling errors.However,the adaptive control scheme also requires computation burden and has to provide persistently exiting signals to the system to identify system parameters.As for the sliding mode control scheme,a sharp change in control input may generate chat-tering and thus induce unnecessary vibration of the system.Although a boundary layer can be introduced to compensate for the chattering problem,slight reduction in performance is unavoidable and the design parameters for the boundary layer is hard to determine.

In this research,the H 1controller is adopted to compensate for the modeling error which is intentionally introduced in the process of approximating the model for a reduction in computation time.Since the range of maximum operating speeds of the parallel manipulator is known,the uncertainty dependent on velocity is also known.The PID controller is employed for tracking in the feedforward manner and the H 1controller is added to compensate for the modeling error.This 2DOF con-troller with the PID and H 1controllers is illustrated in Fig.6.

The H 1controller has a role of attenuating not only the disturbance caused by modeling uncertainty,but also the mismatch error caused by the feedforward PID controller.It is noticed that the feedforward controller part does not a?ect stability of the control system,because it has no feedback.

The dynamic equation (9)can be represented in state space as follows.Substi-tuting of Eq.(13)into (9)and replacing the nonlinear term h of full dynamics by the approximated term ^h on the right-hand side yields

612S.-H.Lee et al./Mechatronics 13(2003)605–619

M eX T€X th eX ;_X T?J T F c t^h e17T

Therefore,the nonlinear terms on both side of Eq.(17)cannot cancel out exactly,thus leading to some mismatch error D h .Substituting Eq.(12)into (17)gives

€X ?M à1J T F c àM à1D h e18T

By introducing a new state vector Z ?f X T _X

T g T ,the following state equation is obtained _Z ?0I 600 Z t0M à1

J T F c à0M à1 D h e19Twhere I 6denotes the 6?6identity matrix.

If the inertia matrix M and Jacobian matrix J are assumed to be constant and D h is considered as disturbance,Eq.(18)can be represented by

_Z ?AZ tBu e20Twhere the matrices A and B correspond to the coe?cient matrices of Eq.(18),u is the actuating force J T F c in task space.

In Fig.7showing the generalized plant,W e es Tand W d es Trepresent the weighting function matrices associated with the tracking error and disturbance,respectively.Because the tracking error should be zero at steady state,the weighting function for the tracking error includes a pure integrator.The disturbance is generated

through

S.-H.Lee et al./Mechatronics 13(2003)605–619613

approximation of the inverse dynamics computation and the operating bandwidth of the parallel manipulator is usually below 10Hz.Taking all these factors into ac-count,the weighting functions are selected as W d ?W d es Tááá0.........0áááW d es T264375;W e ?W e es Tááá0..

.......0áááW e es T

264375;e21Twhere W d es T?d 0=es t20p T,W e es T?e 0=s ,where d 0and e 0are the constants a?ecting tracking performance.The controller K es Tattenuates the closed-loop H 1norm magnitude to less than c via the selected weighting function matrices.W e eI tPK Tà1f àPW d I g 1

Fig.8shows the 6universal-prismatic-spherical Stewart platform designed and built in the laboratory for the experiment.It can operate within the ranges of ?0.2m in the X -and Y -axes,?0.1m in the Z -axis,?25°in roll and pitch,and ?30°in yaw.The controller is divided into two parts;the high-level controller based on PC monitors the platform and performs analysis of the experimental results,while the low-level controller based on the TMS320C31DSP carries out both computation of the inverse dynamics and forward kinematics and implementation of the motor control algorithm.Fig.9shows geometry of the platform and the base of the Stewart platform.

4.1.Inverse dynamics control with full dynamics

Fig.8shows the experimental results where the platform center is forced to follow the reference circular trajectory with a radius of 0.02m in the XY plane at a rela-tively slow frequency of 0.2Hz.Two types of controllers are compared;one is

the

Fig.8.Schematic of experimental setup.

614S.-H.Lee et al./Mechatronics 13(2003)605–619

IDC with full dynamics based on the control law of Eq.(13)and the other is a simple PID controller.The full inverse dynamics computation requires about 25ms,so that the IDC with full dynamics has a long sampling period of 30ms.Since the reference trajectory also has relatively low speed,the tracking performance is not adversely a?ected because of this long sampling period.On the other hand,the simple PID controller that ignores the nonlinear term h eX ;_X

Tof the dynamic equations carries out the following control action only with output errors.

F ?J àT M €X ref tK P eX ref àX TtK D e_X ref à_X TtK I Z eX ref àX Td t e23T

where the integral action in Eq.(23)compensates for ignorance of the nonlinear term to some extent.The two controllers show little di?erence in their responses as shown in Fig.

10.

S.-H.Lee et al./Mechatronics 13(2003)605–619615

Fig.11shows the experimental results where the platform center is to track the circular trajectory with a radius of 0.02m in the XY plane at a relatively fast fre-quency of 2.5Hz (12.5times faster than in Fig.10).It is observed that the IDC with full dynamics shows better performance than the simple PID controller which pro-duces a large tracking error.However,even the IDC cannot generate the truly cir-cular trajectory.The reason is that the sampling period of 30ms is not su?ciently shorter than the trajectory period of 400ms,so the control inputs for accurate tracking cannot be

provided.

616S.-H.Lee et al./Mechatronics 13(2003)605–619

S.-H.Lee et al./Mechatronics13(2003)605–619617 4.2.Proposed inverse dynamics controller

The control scheme proposed in this paper is similar to the IDC with full dy-namics(see Section4.1),but it employs the approximate inverse dynamics together with H1control to compensate for the modeling error.This proposed control scheme will be called the IDC with approximate dynamics below.

In the case of slow tracking as in Fig.10,the proposed control scheme shows little di?erence compared to the IDC with full dynamics.In the case of fast tracking as in Fig.11,however,the IDC with approximate dynamics shows better performance than that with full dynamics as illustrated in Fig.12.It is observed in the

magni?ed

618S.-H.Lee et al./Mechatronics13(2003)605–619

picture that the IDC with approximate dynamics has much shorter sampling period (5ms)than the IDC with full dynamics and thus generates smoother trajectory. Furthermore,the control signal shown in Fig.13is smoother and has less?uctuation than the IDC with full dynamics.

Fig.14shows the experimental results where the platform center is to track the rectangular trajectory at a speed of0.5Hz.It is noted that the rectangular trajectory contains high-frequency components around the corners.It is observed in Fig.14 that the IDC with full dynamics produces generally large tracking error.A partic-ularly large tracking error is generated around the corners,because it cannot faithfully track the corner with high-frequency components due to its long sampling period.On the contrary,the proposed IDC with approximate dynamics shows rel-atively good tracking performance both along the straight-line portion and at the corners.In summary,the proposed controller can track the high-frequency reference command better than the conventional one.

5.Conclusions

A Stewart platform has a drawback of small workspace,but this feature enables the con?guration-dependent coe?cient matrices of the dynamic equations to be approximated to constant ones without introducing large modeling errors.By this approximation,the computation time for the inverse dynamics can be signi?cantly reduced.

About10%modeling error caused by such approximation can be treated as disturbance,and is compensated for by the H1controller,thus leading to a stable control system.The proposed IDC with approximate dynamics combined with the H1controller shows better responses than that with full dynamics and the simple PID controller as the tracking speed increases.Also it provides better tracking performance for high-frequency reference commands.The proposed controller can be realized on-line in a single DSP running at the50Hz speed.Investigation of the proposed controller is under way for various trajectories and tasks. Acknowledgements

This research was supported by the Basic Research Program of the Korea Science and Engineering Foundation(1999-1-304-003).

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S.-H.Lee et al./Mechatronics13(2003)605–619619 [3]Lebret G,Liu K,Lewis FL.Dynamic analysis and control of a Stewart platform manipulator.

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[4]Dasgupta B,Mruthyunjaya TS.Closed-form dynamic equations of the general Stewart platform

through the Newton–Euler approach.Mech Mach Theory1998;33(7):993–1012.

[5]Zhang C,Song S.An e?cient method for inverse dynamics of manipulators based on the virtual work

principle.J Robotic Syst1993;10(5):605–27.

[6]Fichter EF.A Stewart platform-based manipulator:general theory and practical construction.Int J

Robotics Res1986;5(2):157–82.

[7]Zhiming J.Study of the e?ect of leg inertia in Stewart platforms.In:International Conference on

Robotics and Automation.1993.p.121–6.

[8]Craig JJ.Adaptive control of mechanical manipulators.Addison-Wesley;1988.

[9]Asada H,Slotine JJE.Robot analysis and control.John Wiley and Sons;1985.

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mode control.In:International Conference on Robotics and Automation.1998.p.2716–21.

2000年1月大学英语六级考试试题及解答

2000年1月大学英语六级考试试题及解答 PartⅠ Listening Comprehension (20 minutes) Section A Directions: In this section, you will hear 10 short conversations. At the end of each conversation, a question will be asked about what was said. Both the conversation and the question will be spoken only once. After each question there will be a pause. During (he pause, you must read the four choices marked A), B), C) and D), and decide which is the best answer. Then mark the corresponding letter on the Answer Sheet with a single line through the centre. Example: You will hear: You will read: A) 2 hours. B) 3 hours. C) 4 hours. D) 5 hours. From the conversation we know that the two are tawe know that the two are talking about some work they will start at 9 o'clock in the morning and have to finish at 2 in the afternoon. Therefore. D) “5 hours”is the correct answer. You should choose [D] on the Answer Sheet and mark it with a single line trough the centre. Sample Answer [A][B][C][D] 1. A) To cancel his trip. B) To go to bed early. C) To catch a later flight. D) To ask for a wake - up call. 2. A) They have different opinions as to what to do next. B) They have to pay for the house by installments. C) They will fix a telephone in the bathroom. D) The man's attitude is more sensible than the woman's. 3. A) She will save the stamps for the man's sister. B) She will no longer get letters from Canada. C) She can't give the stamps to the man's sister. D) She has given the stamps to the man's roommates. 4. A) Visiting the Brownings. B) Writing a postcard. C) Looking for a postcard. D) Filling in a form. 5. A) The man should work with somebody else. B) The man should meet his partner's needs. C) They should come to a compromise. D) They should find a better lab for the project. 6. A) She can't finish her assignment, either. B) She can't afford a computer right now. C) The man can use her computer. D) The man should buy a computer right away. 7. A) The visiting economist has given several lectures. B) The guest lecturer's opinion is different from Dr. Johnson's. C) Dr. Johnson and the guest speaker were schoolmates. D) Dr. Johnson invited the economist to visit their college.

2015年6月大学英语六级真题及答案(第三套)

2015年6月英语六级真题及答案(第三套) Part I Writing (30 minutes) Directions: For this part, you are allowed 30 minutes to write an essay commenting on the saying “If you cannot do great things, do small things in a great way. ’’You can cite examples to illustrate your point of view. You should write at least l50 words but no more than 200 words. 注意: 此部分试题请在答题卡1上作答。 Part II Listening Comprehension (30 minutes) Section A Directions: In this section, you will hear 8 short conversations and 2 long conversations. At the end of each conversation, one or, more questions will be asked about what was said. Both the conversation and the questions will be spoken only once. After each question there will be a pause. During the pause, you must read the four choices marked A, B, C and D and decide which is the best answer. Then mark the corresponding letter on Answer Sheet, with a single line through the centre. 注意: 此部分试题请在答题卡1上作答。 1.A. The man might be able to play in the World Cup. B. The man’s football career seems to be at an end. C. The man was operated on a few weeks. D. The man is a fan of world famous football players. 2.A. Work out a plan to tighten his budget. B. Find out the opening hours of the cafeteria. C. Apply for a senior position in the restaurant. D. Solve his problem by doing a part time job. 3.A.A financial burden. B. A good companion. C. A real nuisance. D.A well trained pet. 4.A. The errors will be corrected soon. B. The woman was mistaken herself. C. The computing system is too complex. D. He has called the woman several times. 5.A. He needs help to retrieve his files. B. He has to type his paper once more. C. He needs some time to polish his paper. D. He will be away for a two-week conference. 6.A. They might have to change their plan. B. He has got everything set for their trip. C. He has a heavier workload than the woman. D. They could stay in the mountains until June 8. 7.A. They have to wait a month to apply for a student loan. B. They can find the application forms in the brochure. C. They are not eligible for a student loan. D. They are not late for a loan application.

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