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Robotic Tower Crane Modeling and Control (RTCMC) with LQR-DRO and LQR-LEIC for Linear and Nonlinear Payload Swing Minimization

Thein Moe Win(1*), Timothy Hesketh(2), Raymond Eaton(3)

(1) School of Electrical Engineering & Telecommunication, University of New South Wales, Australia
(2) School of Electrical Engineering & Telecommunication, University of New South Wales, Australia
(3) School of Electrical Engineering & Telecommunication, University of New South Wales, Australia
(*) Corresponding author



Fast and accurate positioning and swing minimization of payloads in large standing tall tower crane operation are challenging as well as conflicting tasks. Juggling the trolley back-and-forth manually by crane operator to suppress payload swing can make time consuming and cause fatigue and subsequently cause the crane collapse as well risk the whole working environment. Motivated by Robotic Tower Crane Modeling Control (RTCMC), this work investigates solutions where swing suppression is critical for highly nonlinear trolley-tower-payload crane operation and therefore this work proposes a range of issues in implementing RTCMC. Firstly, recent work of SimMechanics-visualized RTC model and its optimized mathematical linear model are briefly introduced for further controller designs. Secondly, to actively reject the disturbances caused by undesired source of inputs or unknown dynamics, LQR-Disturbance Rejection Observer (DRO) Control with Luenberger-based Extended State Observer is introduced. This research further examines the combination of error space approach with estimator, from which it is argued that the LQR-Estimator-Integral Control (LEIC) and LEIC-Antiwindup for linear model are necessary to achieve robust tracking. Finally, in order to achieve robust tracking control of highly nonlinear trolley translation-payload swing working environment fueled by wind disturbance, LQR-DRO control with torque compensator actuation is implemented on the interaction joints between trolley and payload cables. Proposed RTCMC demonstrated the ability to iteratively achieve desired trolley translation-loadswing geometry. Under this iterative method, all weighting Q-R matrices, Observer gains (L) matrix, and uncertainties gains have adapted to deferent input conditions until pre-specified trajectories of trolley-loadswing are achieved. Evidence of improvements in linear model controls using (LQR-DRO, LQR-LEIC, and LEIC-Antiwindup), and in nonlinear RTCMC using (LQR-DRO) are presented. Control solutions in this research focused on simplicity of implementation: general and straightforward reference-tracking control methods are preferred over Tower crane-tailored formulation. The benefit is that, the proposed RTCMC has potential applications to other types of crane operations and global crane research.
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Robotic Tower Crane Modeling Control; Disturbance Rejection Observer; LQR-Estimator-Integral Control; Linear; Nonlinear

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F. Ju, Y.S. Choo, F.S. Cui, Dynamic response of tower crane induced by the pendulum motion of the payload, International Journal of Solids and Structures, Volume 43, Issue 2, January 2006, Pages 376-389, ISSN 0020-7683,

Lagerev, A., Lagerev, I., Milto, A., Tool for Preliminary Dynamics and Stress Analysis of Articulating Cranes, (2014) International Review on Modelling and Simulations (IREMOS), 7 (4), pp. 644-652.

Lagerev, A., Lagerev, I., Milto, A., Preliminary Dynamics and Stress Analysis of Articulating Non-Telescoping Boom Cranes Using Finite Element Method, (2015) International Review on Modelling and Simulations (IREMOS), 8 (2), pp. 223-226.

Thein Moe Win, Tim Hesketh, and Ray Eaton. Construction Tower Crane SimMechanics-Visualized Modelling Tower Vibration Impact on Payload Swing Analysis and LQR Swing Control, (2014) International Review on Modeling and Simulations (IREMOS), 7 (6), pp. 979-994.

Zhiqiang Gao, Active Disturbance Rejection Control: A Paradigm Shift in Feedback Control System Design Center for Advanced Control Technologies, Proceeding of the 2006 American Control Conference, Minneapolis, Volume 9 (Issue 2): 2399-2405, June 14-16, 2006

H. Sano, K. Sato, K Ohishi, and T. Miyazaki. Robust Design of Vibration Suppression Control System for Crane Using Say Angle Observer Considering Friction Disturbance, Electrical Engineering Conference in Japan, Vol. 184, No. 3, pp. 36–46, Nagoya, Japan, Jan. 2013.

Manuel Olivares a, Pedro Albertos, Linear control of the flywheel inverted pendulum, ELSEVIER Journal of ISA Transactions, Volume 53 (Issue 1): 1396-1403, January 2014.

Lal B. Prasad, B. Tyagi, and Hari O. Gupta, Optimal Control of Nonlinear Inverted Pendulum System Using PID Controller and LQR: Performance Analysis Without and With Disturbance Input, International Journal of Automation and Computing, Volume 11 (Issue 6): 661-670, December 2014.

Abdelhadi Elharfi, Feedback Controller Stabilizing Vibrations of a Flexible Cable Related to an Overhead Crane, Mathematical Problems in Engineering Research, Hindawi, Volume 1, 1-12, August 2010.

] Martin Böck and Andreas Kugi, Real-time Nonlinear Model Predictive Path-Following Control of a Laboratory Tower Crane, IEEE Transactions on the Control Systems Technology Journal, Volume 22 (Issue 4): 1461-1473, July 2014.

Dongkyoung Chwa, Real Nonlinear Tracking Control of 3-D Overhead Cranes Against the Initial Swing Angle and the Variation of Payload Weight, IEEE Transactions on the Control Systems Technology Journal, Volume 17 (Issue 4): 876-883, July 2009.

Thein Moe Win, Tim Hesketh, and Ray Eaton. SimMechanics Visualization of Experimental Model Overhead Crane, Its Linearization And Reference Tracking-LQR Control, AIRCC International Journal of Chaos, Control, Modeling and Simulation (IJCCMS), Volume 2 (Issue 3):1-16, September 2013.

G. F. Franklin and J.D. Powell, Feedback Control of Dynamics Systems, (Prentice Hall, 2002, Chapter 7: State-Space Design

J,Han, Active Disturbance Rejection Control, IEEE Transactions on Industrial Eletronics, Volume 56 (Issue 3), 900-906, August 2006

Magdi S. Mahmoud and Yuanquing Xia, Applied Control System Design, Chapter 7: (7.8: Integral Control and Robust Tracking) Springer, 2012, pg: 440-446

G. F. Franklin and J.D. Powell, Feedback Control of Dynamics Systems, (Prentice Hall, 2002, Chapter 9: Control System Design.

Richard M. Murray, Optimization-Based Control, Control and Dynamical Systems, (California Institute of Technology Press, 2010, Chapter 5: Kalman Filtering).

G. F. Franklin and J.D. Powell, Feedback Control of Dynamics Systems, (Prentice Hall, 1991, Chapter 3: Basic Principles of Feedback.

Harris, T.J. and Yu, W, Controller assessment for a class of nonlinear systems, ELSEVIER Journal of Process Control, Volume 17 (Issue 7): 607-619, August 2007.

K. J. Astrom and P. Eykhoff , System Identification-Survey, Automatica Journal, Volume 7 (Issue 1): pp. 123-162, January 1971

Lennart Ljung and Qinghua Zhang, An integrated System Identification tool- box for linear and non-linear models, IFAC Symposium on System Identification, Vol. 1, No. 3, pp. 1–9, Newcastle, Australia, June 2007

Lennart Ljung, System Identification , Theory for the User, (Prentice Hall, 1999, 2nd Edition, Chapter 17)

Lennart Ljung and Qinghua Zhang, System Identification Toolbox 7 User's Guide MATLAB SIMULINK, (The MathWorks USA, 2008)

Zulkeflee, S.A. & Aziz, N., Nonlinear Autoregressive with Exogenous Inputs Based Model Predictive Control for Batch Citronellyl Laurate Esterification Reactor, INTECHOPEN Journal, Volume 1 (Issue 13): 268-290, June. 2011.

Heikki Koivo , Adaptive Neuro-Fuzzy Inference System ,(ANFIS, 2000, Japan)

Ivan Taufer and Oldrich Drabek, Identification of nonlinear systems based on mathematical – physical analysis and least square method, Acta Montanistica Slovaca Conference, Volume 8 (Issue 4): 188-190, Nov 2003

Abdellah, A., Abdelhafid, A., Mostafa, R., Combining Sliding Mode and Linear Quadratic Regulator to Control the Inverted Pendulum, (2013) International Review of Automatic Control (IREACO), 6 (1), pp. 69-76.

Quanser (2010). “3 Degrees of Freedom Tower Crane User Manual”, Quanser Ltd. (Quanser User Manual)

Inteco (2010). “Tower Crane Control User Manual”, Inteco Ltd. (Inteco User Manual, Version 1.4.)

H.M. Omar, A.H. Nayfeh. Anti-swing control of gantry and tower cranes using fuzzy and time-delayed feedback with friction compensation, Shock and Vibration Journal of Hindawi, Volume 12 (Issue 2): 73-89, March 2005.


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