Precision tracking control of a horizontal arm coordinate measuring machine in the presence of dynamic flexibilities

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Int J Adv Manuf Technol 2006) 27: 960 968 DOI 10.1007/s00170-004-2292-3 ORIGINAL ARTICLE Tugrul Özel Precision tracking control of a horizontal arm coordinate measuring machine in the presence of dynamic flexibilities Received: 3 April 2004 / Accepted: 9 June 2004 / Published online: 23 September 2004 Springer-Verlag London Limited 2005 Abstract One of the major sources that affect measurement accuracy and limit the use of high motion speeds in coordinate measuring machines CMM) is the position error. In fact, static and dynamic probe errors are more direct factors in measuring machine accuracy, but are not the subject of this research. However the accuracy of acquisition of component position errors using a CMM in motion is also of importance, hence the dynamics of a CMM need to be considered. Therefore, this research aims to the dynamics of a horizontal arm CMM by considering drive flexibility at joints and evaluates the characteristics of the system for fine motion control purposes. Design of a precision tracking controller PTC) to perform superior tracking for enhancing the measurement accuracy and the probing speed in providing less inspection time at high motion speeds is carried out. A dynamic for the CMM is developed including drive flexibilities represented with lumped springs at the joints. Due to the non-collocated nature of the control scheme in the flexible CMM dynamics, a non-minimum phase system is observed in the proposed CMM. Using the derived CMM with joint flexibilities, tracking motion control simulations are conducted at different probing speeds for the cases where a PI controller and a feedback PTC are employed. A comparison of the PI controller with the feedback PTC is also performed. Results demonstrate that the effects of joint flexibilities on the contour error and probing speeds are significant and the PI controller is not capable of providing good accuracy during challenging tasks such as corner tracking. However, the simulation results indicated that by using the proposed feedback precision tracking controller, contour errors in corner tracking that are caused by joint flexibilities can be reduced effectively. T. Özel Department of Industrial and Systems Engineering, Rutgers, The State University of New Jersey, 96 Frelinghuysen Road, Piscataway, New Jersey, USA E-mail: ozel@rci.rutgers.edu Tel.: +1-732-4451099 Fax: +1-732-4455467 Keywords Coordinate measuring machines Precision tracking control 1 Introduction The coordinate measuring machines CMM) that are widely used in manufacturing systems pose measurement and position errors that are caused by structural vibrations and thermal conditions [1 3]. The main sources of static and quasi-static errors in accuracy of CMMs are geometric errors, stiffness and mass related errors of the components. The dynamic probe errors are a major factor in measuring machine accuracy at high speeds and fast probing as a result of high demand in shorter inspection times. It is widely reported that under high operational speeds, machine vibrations due to the effects of structural stiffness, elasticity and drive flexibility are problematic [4, 5]. Many studies in the assessment of dynamic errors of CMMs are carried out and several solutions to compensate such errors are proposed [6 8]. But static and dynamic probe errors are not the subject of this research. One of the other major sources that affects measurement accuracy and limits the use of high motion speeds in CMM is the position error. In this case, the accuracy of acquisition of component position errors using a CMM in motion are of importance, so the dynamics of a CMM need to be considered, and is the aim of this paper. Various control schemes have been developed to deal with structural vibrations and position control problems in CMMs [9 11]. However, none of these studies considered the tracking position control problem in the presence of dynamic flexibilities. Therefore, the objective of this study is to determine the effects of joint flexibilities, that are observed in the system dynamics, on tracking performance of the CMM, and to design a feedback precision tracking controller PTC). Hence, this study presents dynamic s of a horizontal arm CMM including drive flexibilities at joints, which are the cause of structural vibrations affecting CMM measurement accuracy. Design of a feedback PTC is aimed in order to improve CMM performance in fol-

lowing challenging trajectories. The tracking performance of the designed PTC is expected to outperform a classical PI controller. At first, a simplified dynamic of a horizontal arm CMM is studied. Modeling the dynamics of the CMM is accomplished in three consecutive steps: 1) Dynamic ing of the rigid CMM body, 2) Dynamic ing of rigid CMM body with a rigid drive system, and 3) Dynamic ing of rigid CMM body with drive flexibility at joints. These s are utilized in obtaining a nominal plant for the design of the PTC. 2 Dynamic A simplified geometrical for a horizontal arm CMM is given in Fig. 1. In an earlier study, Katebi et al. [9] presented a rigid body dynamic for a horizontal arm CMM. Equations of motion with five degrees of freedom and with the dynamic coupling between probe and CMM arms are given as: T 1 = m 1 + m 2 + m 3 + m 4 + m 5 ) q 1 ) + m 5 l c5 s4 c 5 q 4 c 4 s 5 q 5 + h1 + C 1 1) ) h 1 = m 5 l c5 c 4 c 5 q 4 2 c 4c 5 q 5 2, C 1 = 0 2) T 2 = m 2 + m 3 + m 4 + m 5 ) q 2 ) + m 5 l c5 c4 c 5 q 4 s 4 s 5 q 5 + h2 + C 2 3) ) h 2 = m 5 l c5 s 4 c 5 q 4 2 2c 4c 5 q 4 q 5 s 4 c 5 q 5 2 4) C 2 = g m 2 + m 3 + m 4 + m 5 ) 5) ) T 3 = m 3 + m 4 + m 5 ) q 3 + m 5 l c5 c5 q 5 + h3 + C 3 6) h 3 = m 5 l c5 s 5 q 5 2, C 3 = 0 7) 961 ) T 4 = m 5 l c5 s4 c 5 q 1 + c 4 c 5 q 2 [ + I 114 + I 334 + I 225 s5 2 + I 335 + m 5 l 5 c 2 5 l 5 2r c5 ) + I 115 c 2 5 ] 2I 125 c 5 s 5 q 4 [I 135 s 5 + I 235 c 5 ] q 5 + h 4 + C 4 8) )] h 4 = 2 [I 225 I 115 m 5 l 5 l 5 2r c5 )) c 5 s 5 + I 125 s5 2 c2 5 q 4 q 5 + [I 235 s 5 I 235 c 5 ] q 5 2 9) C 4 = m 5 gc 4 c 5 l 5 r c5 ) = m 5 gc 4 c 5 l c5 10) ) T 5 = m 5 l c5 c4 s 5 q 1 s 4 s 5 q 2 + c 5 q 3 I135 s 5 + I 235 c 5 ) q + [I 115 + I 225 + m 5 l 5 l 5 2r c5 )] q 5 + h 5 + C 5 11) )] h 5 = [I 115 I 225 + m 5 l 5 l 2r c5 )) c 5 s 5 + I 125 c 2 5 s2 5 q 4 2 12) C 5 = m 5 gs 4 s 5 l 5 r c5 ) = m 5 gs 4 s 5 l c5 13) Since, the probe and CMM arms are not operated simultaneously, the interaction between the probe and the horizontal CMM arm can be assumed insignificant. Hence the effect of the load torque on the arm dynamics is neglected. The velocity and acceleration terms for the probe, i.e., q 4, q 5, q 4, q 5 are zero in the global motion of CMM arms. According to that legitimate assumption, the equations of motion can be easily simplified as: T 1 = m 1 + m 2 + m 3 + m 4 + m 5 ) q 1 14) T 2 = m 2 + m 3 + m 4 + m 5 ) q 2 + g m 2 + m 3 + m 4 + m 5 ) 15) T 3 = m 3 + m 4 + m 5 ) q 3 16) Hence, the dynamic of the plant is derived and the assumptions made to simplify the system are stated. It is common practice to simplify the system and use linear elements to approximate nonlinear elements so that the design and analysis can be performed with the mathematical tools available. Therefore, the uncoupled set of equations given by Eqs. 14 16 is used as a dynamic for rigid body CMM in the tracking control problem. In addition, the derivation of a mathematical for a rigid drive system, and a drive system with joint flexibilities are discussed in the following sections, respectively. 2.1 Rigid drive system for a single axis CMM joint A drive system mathematical for each CMM joint is developed to simulate single-axis linear motion due to the actuator input. An armature controlled DC-motor with motor inertia and viscous friction is assumed as the driving actuator. The consists of a gear train with overall gear ratio N, a lead screw with a pitch p, and a carrier together with a prismatic link that exerts load inertia and viscous friction that need to be overcome by a DC-motor. The schematic diagram of the electromechanical is shown in Fig. 2. A transfer function for the linear motion of the prismatic link with respect to the input supply voltage can be written by using the circuit equation of the DC-servomotor: Fig. 1. Kinematical of a horizontal arm coordinate measuring machine e a e b = L a di a dt + R a i a 17)

962 Fig. 2. Schematic diagram of the rigid joint where the induced voltage is proportional to the angular velocity with a back-emf constant given as e b = K g θ m 18) and motor torque directly proportional to the armature current with a torque constant T m = K t i a 19) The DC-servomotor torque-load relation can be obtained as T m NT L = J m θ m + B m θ m 20) and the load torque can be written in terms of the load shaft position as, T L = J link θ L + B L θ L, 21) where J link = link_mass)p2 and p is the pitch of the lead screw. 2π) 2 The angular displacement of the load shaft and linear displacement of a single link are, θ L = Nθ m and q = θ L p = pnθ m. By taking Laplace transforms of Eqs. 18 21 and substituting into Eq. 17, the transfer function of linear link displacement for input voltage can be written as, qs) e a s) = K t pn J eff L a s 3 + B eff L a + J eff R a )s 2 + B eff R a + K g K t )s, where the effective inertia and the viscous friction are given as, 22) J eff = J m + N 2 J L, 23) B eff = B m + N 2 B L. 24) The block diagram representation of the above is shown in Fig. 3. Fig. 4. Block diagram of the single-axis position control of the rigid joint 2.2 Feedback control of the rigid joint drive by using the load shaft position The tacho generator that uses encoder output in a velocity loop, along with a tacho gain k v and a tacho amplifier gain k, provides velocity feedback in a DC-servomotor system. The position feedback control of above drive system can be carried out by employing a PI controller in which a load shaft position is provided as a feedback signal. The block diagram for the overall control system is shown in Fig. 4. 2.3 Drive system for a single axis CMM with joint flexibility In order to investigate the effects of joint flexibility in the proposed single axis drive system, a flexible joint is developed. Due to backlashes, drive compliance, and trust bearing at the torque transmission, a joint flexibility is added to the rigid as two lumped springs to both the rotor and load sides. An armature controlled DC-motor with motor inertia and viscous friction is assumed as a driving actuator. A gear train with overall gear ratio N, lead screw with a pitch p, a carrier along with a CMM link, which has load inertia and viscous friction that have to be driven by a DC-motor. The schematic diagram of electromechanical is shown in Fig. 5. The transfer function for the linear motion of a prismatic link with respect to input supply voltage in the flexible joint can also be derived by using circuit equation of DC-servomotor e a e b = L a di a dt + R a i a 25) Fig. 3. Block diagram for the rigid joint drive where back emf, e b = K g θ m and motor torque T m = K t i a.the DC-motor torque-load relation can be written in both the DCmotor and the load side as T m = J m θ m + B m θ m + k s θm θ l ) 26)

963 Fig. 5. Schematic diagram of the flexible joint 0 = J l θ l + B l θ l + k ) s θ l θ m 27) where J l = 1 N 2 J link, B l = 1 N 2 B l, k s = link_mass)p 2 2π) 2 k lk m k l +N 2 k m, and J link = D m s) = J m s 2 + B m s + k s 28) D l s) = J l s2 + B l s + k s 29) By defining Eqs. 28 and 29 and by taking Laplace transforms of Eqs. 26 and 27 and by substituting into Eq. 25, the transfer function of the linear link displacement for input voltage in flexible joint s can be obtained and written as qs) e a s) = where Ktks p N As 5 + Bs 4 + Cs 3 + Ds 2 + Es 30) A = J m J l L a B = [ J m B l + J l B m) La + J m J l ] C = [ J m k s + B m B l + J l k s) La + J m B l + J l B ) m Ra + J l K ] t K g D = [ B m k s + B l k s) La + J m k s + B m B l + J l k ) s Ra + B l K ] t K g E = B m k s + B l k s) Ra + k s K t K g 31) The block diagram representation of this is given in Fig. 6. 2.4 Feedback control of the flexible joint drive system by using the load shaft position The tacho generator that uses encoder output in a velocity loop along with a tacho gain k v and a tacho amplifier gain k provides velocity feedback in a DC-servomotor system. The position feedback control of above drive system can be carried out by employing a PI controller in which load shaft position is provided as the feedback signal. The block diagram for the overall control system is shown in Fig. 7. Fig. 6. Block diagram for the flexible joint drive Fig. 7. Block diagram of the single-axis position control of the flexible joint Table 1. Characteristics of the axis drive system R a = 0.086 ohm L a = 0.0258 H = v s/a) K g = 0.89 back-emf v/rad/s K t = 0.65104 motor constant lbf ft/a B m = 0.071354 lbf ft/a J m = 0.002083 slug ft 2 N = 0.15 gear ratio J L = 0.2slug ft 2 B L = 0.0187 lbf ft 2 /s k m = 9.271 spring constant lbf ft/rad p = 0.15 pitch k l = 9.271 spring constant lbf ft/rad m 1 = 15 slug m 3 = 8slug m 2 = 10 slug m 4 = 0.8slug m 5 = 0.2slug k v = 0.011 tacho velocity gain k = 50 amplifier gain T = 0.004 second sampling time Characteristics of the axis drive system of a horizontal arm CMM are given in Table 1. 3 Design of a precision tracking controller The coordinate measuring machines require high position control precision just like any other manufacturing machinery. Tracking control of the machines to achieve precision positioning with minimum errors has been an attractive field of study for the researchers. Digital control algorithms including crosscoupled control [12], zero-phase error tracking control [13] and precision tracking control [14] are widely utilized in designing tracking controllers in high-speed motion machines [15 17]. In this study, a precision tracking controller is designed.

964 In a position control system, a feedback Q c z 1 ) and a feedforward Q f z 1 ) controller can be presented with a block diagram shown in Fig. 8, where r is the input trajectory, d is disturbance, and y is output trajectory. The mathematical of the plant under control can be written as, G z 1) = Ĝ z 1) 1 + z 1)) and ω) <lω) where nominal plant is denoted as Ĝ z 1), and structural uncertainties are denoted as z 1). The output signal y can be derived as, y = Q f z 1) Q c z 1 ) G z 1) 1 + Q c z 1 ) G z 1) r 1 + 1 + Q c z 1 ) G z 1) G z 1) d. 32) The complementary sensitivity function without any uncertainty can be defined as CS 0 z 1) = Q c z 1 ) Ĝ z 1) 1 + Q c z 1 ) Ĝ. 33) z 1) A direct design approach presented by Xia and Menq [14] is used to design the desired feedback controller according to a complementary sensitivity function, CS 0 z 1 ). In that respect, a target complementary function was selected as CS 0 z 1) = 0.2z 1 1 0.8z 1 ). 34) Therefore, the feedback precision tracking controller PTC) can then be given as Q c z 1) = CS 0 z 1 ) 1 CS 0 z 1 ) Ĝ 1 z 1). 35) The plant of the rigid drive system becomes G rig z 1) = 0.00076765z 1 + 0.0029404z 2 + 0.000720139z 3 1 2.6665z 1 + 2.54698z 2 + 2.54697z 3 0.880463z 4. 36) The zeros in this system are z 1 = 3.5674 non-minimum phase zero) and z 2 = 0.262964. Since z 1 is an unacceptable zero in the nominal, the inverse of the nominal cannot be implemented directly in the feedback controller [14]. A bi-casual inverse, non-casual step m is set zero, and casual step n Fig. 8. Block diagram of the single axis tracking control system Fig. 9. Block diagram of the proposed tracking control scheme is chosen as 1. The designated target function is employed. The feedback controller is now Q crig z 1) 0.2 1 2.6665z 1 + 2.54698z 2 + 2.54697z 3 ) 0.880463z 4) 0.7248 + 0.2752z 1) = z 3 1 z 1) 1 + 0.262964z 1) 37) and the plant of the flexible drive system becomes, 10 4 0.0034z 1 + 0.0836z 2 + 0.2005z 3 ) G flx z 1) +0.0756z 4 + 0.0028z 5) = 1 4.4475z 1 + 8.0883z 2 7.5779z 3 ) +3.681z 4 0.7438z 5 38) The zeros of that system become z 1 = 21.7301, z 2 = 2.1904 non-minimum phase zeros), z 3 = 0.4131 and z 4 = 0.0417. Notice that z 1 and z 2 are unacceptable zeros in the nominal. A bi-casual inverse, non-casual step m is set zero, and casual step n is chosen as 1 and the designated target function is employed. The feedback controller is now Q cflx z 1) 0.2 1 4.4475z 1 + 8.0883z 2 7.5779z 3 ) +3.681z 4.7438z 5).5216 +.478452z 1) = z 4 1 z 1) 1 +.4131z 1) 1 +.0417z 1) 39) The block diagram of the proposed feedback loop is shown in Fig. 9. 4 Tracking control simulations Comparison of the feedback PTC with the PI controller in CMM motion control is also studied. Thus, a feedforward controller was not designed. An input trajectory in the form of a sharp corner was given for the CMM arms. Simulations of the CMM motion are performed for a given two-axis sharp corner trajectory at a conservative speed of 3.33 mm/s, and then higher speeds of 37.5 mm/s and 93.8 mm/s, respectively. The contour error, defined as the position error normal to the input trajectory, at each sampling time is calculated and results are presented. By using the rigid joint drive system, tracking control simulations are carried out for both the PI controller and the feedback PTC, Q c z 1 ). The graphics for input and output trajectories and the contour error vs. time are given in Fig. 10, at

965 Fig. 10. Simulation results for the PI controller by using the rigid joint Fig. 11. Simulation results for the feedback PTC by using the rigid joint speeds of 37.5mm/s and 93.8mm/s for the rigid joint CMM. As shown in Fig. 10, the PI controller is capable of providing a fair tracking control except around the sharp corner. During corner tracking the maximum contour error is about 1.7mm at the speed of 37.5mm/s and about 4.4 mm at the speed of 93.8 mm/s. However, the feedback PTC provides less contour error during a sharp corner tracking. In this case, maximum contour error is about 0.7 mm at a speed of 37.5mm/s and1.7mm at a speed of 93.8mm/s as shown from Fig. 11.

966 Fig. 12. Simulation results for the feedback PTC by using the flexible joint Fig. 13. Simulation results for the feedback controllers by using the flexible joint

967 Fig. 14. Control effort of the feedback controllers at a low speed when considering the flexible joint Fig. 15. Control effort of the feedback controllers at a high speed when considering the flexible joint Simulation results for the CMM s end point positions by using flexible joint drive system are shown in Fig. 12. In this case, the PI controller s ability in tracking control of a given corner trajectory is poor even at a conservative speed of 3.33 mm/s. During corner tracking, the response of the system is oscillatory and the contour error is large. The results are more dramatic when the traveling speed of the CMM is increased to 37.5mm/s. At a speed of 3.33 mm/s, the PI controller barely handles the corner tracking with a maximum contour error of 3.25 mm, but at higher speeds, the proper tracking of sharp corners can not be accomplished by using a PI controller alone. The maximum contour error is more than 10 mm when using the PI controller. However, the feedback PTC provides better tracking with 0.12 mm and 1.2 mm as maximum contour error at the speeds

968 of 3.33 mm/s and 37.5 mm/s, respectively. The feedback PTC also provides fair tracking at a speed of 93.8mm/s asshownin Fig. 13. The control effort for both the PI controller and the feedback PTC are also studied when considering the flexible joint drive system in the CMM. The control effort of the PI controller is about 0.0013 V at the speed of 3.33 mm/s. However, it is much higher when the feedback PTC is employed. As shown in Fig. 14, the maximum control effort occurs at the corner tracking and is about 5.3 V at a speed of 3.33 mm/s. The more the speed is increased, the more the control effort is required at tracking sharp corners. Consequently, the system with feedback PTC results in high and oscillating control effort at a speed of 37.5mm/s as indicated in Fig. 15. q i linear displacements for joints 1, 2, 3 and angular displacements for joints 4, 5 q i linear velocities for joints 1, 2, 3 and angular velocities for joints 4, 5 q i linear accelerations for joints 1, 2, 3 and angular accelerations for joints 4, 5 r ci center of mass for link i s i sin q i T k load torque of link k T m torque developed by the dc motor θ l angular displacement of the lead screw θ m angular displacement of the dc motor shaft Acknowledgement The author greatly acknowledges Professor C. H. Menq of the Department of Mechanical Engineering, Ohio State University, for the design of the precision tracking controller. 5 Conclusions This paper presents a tracking control problem for a horizontal arm coordinate measuring machine when a rigid structure with dynamic flexibility at joints and the drive systems are considered. A classical feedback PI controller fails to provide precision tracking at the sharp corners during high-speed movements of the CMM. Therefore, another digital controller is proposed and designed to track challenging trajectories at higher speeds. The designed feedback precision tracking controller provided finetracking control. However, tracking control simulations showed that PTC requires larger control effort with respect to a PI controller to be able to keep the contour error small. List of symbols B l equivalent viscous-friction coefficient of the lead screw B m equivalent viscous-friction coefficient of the dc servomotor c i cos q i e a armature voltage of the dc servomotor e b back e.m.f. of the dc servomotor g gravitational acceleration i a armature current of the dc servomotor I ijk i, j)th element of inertia matrix of link k J l equivalent moment of inertia of the lead screw J m equivalent moment of inertia of the dc servomotor k s lumped spring constant representing dc servomotor flexibilities k l lumped spring constant representing lead screw flexibilities k tacho amplifier gain in the dc servomotor k v tacho gain in the dc servomotor K t torque constant of the dc servomotor K g back e.m.f. constant of the dc servomotor L a armature inductance m i mass of the links of the coordinate measuring machine N gear ratio at each joint p pitch of the lead screw at each joints References 1. Harvie A 1986) Factors affecting component measurement on coordinate measuring machines. Precis Eng 81)13 18 2. Sutherland AT, Wright DA 1987) Optimizing a servo system for a coordinate measuring machine. Precis Eng 91):222 228 3. Weekers WG, Schellekens PHJ 1995) Assessment of dynamic errors of CMMs for fast probing. Ann CIRP 441):469 474 4. Lim CP, Menq CH 1994) CMM feature accessibility and path generation. Int J Prod Res 323):597 618 5. Lu E, Ni J, Huang ZG, Wu SM 1992) An integrated lattice filter adaptive control system for time varying CMM structural vibration control. Proceedings of ASME 1992 winter meeting PED, vol 55 6. van Vliet WP, Schellekens PHJ 1998) Development of a fast mechanical probe for coordinate measuring machines. Precis Eng 223):141 152 7. Mu YH, Ngoi BKA 1999) Dynamic error compensation of coordinate measuring machines for high-speed measurement. Int J Adv Manuf Technol 15:810 814 8. Dong C, Zhang C, Wang B, Zhang G 2002) Prediction and compensation of dynamic errors for coordinate measuring machines. ASME J Manuf Sci Eng 124:509 514 9. Katebi MR, Lee T, Grimble MJ 1993) Optimal control design for fast coordinate measuring machine. Control Eng Pract 15):797 806 10. Katebi MR, McIntyre J, Lee T, Grimble MJ 1993) Integrated process and control design for fast coordinate measuring machine. Mechatronics 33):343 368 11. Shi J, Ni J 1996) Supervisory adaptive control for the structural vibration of a coordinate measuring machine. Int J Adv Manuf Technol 11:240 248 12. Koren Y 1980) Cross-coupled biaxial computer controls for manufacturing systems. ASME J Dyn Syst Meas Control 1021):140 149 13. Tomizuka M 1987) Zero phase error tracking algorithm for digital control. ASME J Dyn Syst Meas Control 109:65 68 14. Xia Z, Menq CH 1995) Precision tracking control of non-minimum phase systems with zero phase error. Int J Control 614):791 806 15. Guo L, Tomizuka M 1997) High-speed and high-precision motion control with an optimal hybrid feedforward controller. IEEE/ASME Trans on Mechatron 22):110 122 16. Zhong Q, Shi Y, Mo J, Huang S 2002) A linear cross-coupled control system for high-speed machining. Int J Adv Manuf Technol 19:558 563 17. Liu Y, Li C, Wang D, Guo X 2003) Tracking control and reference trajectory generation in a LOM system. Int J Adv Manuf Technol 219):637 643