A systematic review of current and emergent manipulator control approaches

Abstract

Pressing demands of productivity and accuracy in today’s robotic applications have highlighted an urge to replace classical control strategies with their modern control counterparts. This recent trend is further justified by the fact that the robotic manipulators have complex nonlinear dynamic structure with uncertain parameters. Highlighting the authors’ research achievements in the domain of manipulator design and control, this paper presents a systematic and comprehensive review of the state-of-the-art control techniques that find enormous potential in controlling manipulators to execute cutting-edge applications. In particular, three kinds of strategies, i.e., intelligent proportional-integral-derivative (PID) scheme, robust control and adaptation based approaches, are reviewed. Future trend in the subject area is commented. Open-source simulators to facilitate controller design are also tabulated. With a comprehensive list of references, it is anticipated that the review will act as a first-hand reference for researchers, engineers and industrial-interns to realize the control laws for multi-degree of freedom (DOF) manipulators.

Keywords

robot control / robust and nonlinear control / adaptive control / intelligent control / industrial manipulators / robotic arm

References

[1] Khan H, Iqbal J, Baizid K, . Longitudinal and lateral slip control of autonomous wheeled mobile robot for trajectory tracking. Frontiers of Information Technology & Electronic Engineering, 2015, 16(2): 166–172

[2] Spong M W, Vidyasagar M. Robot Dynamics and Control. 3rd ed. New York: John Wiley & Sons, 2008

[3] Iqbal J, Tsagarakis N G, Fiorilla A E, . A portable rehabilitation device for the hand. In: 2010 Annual International Conference of the IEEE on Engineering in Medicine and Biology Society (EMBC). Buenos Aires: IEEE, 2010, 3694–3697 doi:10.1109/IEMBS.2010.5627448

[4] Iqbal J, Tsagarakis N, Caldwell D. Design optimization of a hand exoskeleton rehabilitation device. In: Proceedings of Workshop on Understanding the Human Hand for Advancing Robotic Manipulation, Robotics Science and Systems (RSS). Seattle, 2009, 44–45

[5] Iqbal J, Tsagarakis N G, Caldwell D G. A human hand compatible optimised exoskeleton system. In: 2010 IEEE International Conference on Robotics and Biomimetics (ROBIO). Tianjin: IEEE, 2010, 685–690

[6] Iqbal J, Tsagarakis N G, Caldwell D G. A multi-DOF robotic exoskeleton interface for hand motion assistance. In: 2011 Annual International Conference of the IEEE on Engineering in Medicine and Biology Society (EMBC). Boston: IEEE, 2011, 1575–1578

[7] Iqbal J, Tsagarakis N, Fiorilla A E, . Design requirements of a hand exoskeleton robotic device. In: 14th IASTED International Conference on Robotics and Applications (RA). Massachusetts, 2009, 44–51

[8] Khan A A, un Nabi S R, Iqbal J. Surface estimation of a pedestrian walk for outdoor use of power wheelchair based robot. Life Science Journal, 2013, 10(3): 1697–1704

[9] Iqbal J, Tsagarakis N, Caldwell D. Design of a wearable direct-driven optimized hand exoskeleton device. In: Proceedings of the Fourth International Conference on Advances in Computer-Human Interactions (ACHI). Gosier: IARIA, 2011, 142–146

[10] Azeem M M, Iqbal J, Toivanen P, . Emotions in robots. In: Chowdhry B S, Shaikh F K, Akbar Hussain D M, , eds. Emerging Trends and Applications in Information Communication Technologies. Berlin: Springer, 2012, 144–153

[11] Naveed K, Iqbal J, ur Rahman H. Brain controlled human robot interface. In: 2012 International Conference on Robotics and Artificial Intelligence (ICRAI). Rawalpindi: IEEE, 2012, 55–60

[12] Iqbal J, Pasha S M, Baizid K, . Computer vision inspired real-time autonomous moving target detection, tracking and locking. Life Science Journal, 2013, 10(4): 3338–3345

[13] Iqbal J, Pasha M, Riaz-un-Nabi, . Real-time target detection and tracking: A comparative in-depth review of strategies. Life Science Journal, 2013, 10(3): 804–813

[14] Iqbal J, Heikkila S, Halme A. Tether tracking and control of ROSA robotic rover. In: 10th International Conference on Control, Automation, Robotics and Vision (ICARCV). Hanoi: IEEE, 2008, 689–693

[15] Iqbal J, Saad M R, Tahir A M, . State estimation technique for a planetary robotic rover. Revista Facultad de Ingeniería, 2014, 73: 58–68

[16] Iqbal J, Tahir A, Islam R U, . Robotics for nuclear power plants—Challenges and future perspectives. In: 2012 2nd International Conference on Applied Robotics for the Power Industry (CARPI). Zurich: IEEE, 2012, 151–156 doi:10.1109/CARPI.2012.6473373

[17] Baizid K, Chellali R, Yousnadj A, . Modelling of robotized site and simulation of robot’s optimum placement and orientation zone. In: 21st IASTED International Conference on Modelling and Simulation (MS). Canada, 2010, 9–16

[18] Meddahi A, Baizid K, Yousnadj A, . API based graphical simulation of robotized sites. In: IASTED International Conference on Robotics and Applications. Cambridge, 2009, 485–492

[19] Groover M P, Weiss M, Nagel R N, . Industrial Robotics: Technology, Programming and Applications. McGraw-Hill Education, 2008

[20] Fu K S, Gonzalez R C, Lee C S G. Robotics: Control Sensing Vision and Intelligence. McGraw-Hill Education, 2008

[21] Bamdad M. Analytical dynamic solution of a flexible cable-suspended manipulator. Frontiers of Mechanical Engineering, 2013, 8(4): 350–359

[22] Baizid K, Yousnadj A, Meddahi A, . Time scheduling and optimization of industrial robotized tasks based on genetic algorithms. Robotics and Computer Integrated Manufacturing, 2015, 34: 140–150

[23] Asfahl C. Robots and Manufacturing Automation. 2nd ed. John Wiley & Sons, Inc., 1992

[24] Visioli A. Research trends for PID controllers. Acta Polytechnica, 2012, 52(5): 144–150

[25] Blevins T. PID advances in industrial control. In: Preprints IFAC Conference on Advances in PID Control. Brescia, 2012

[26] McMillan G K. Industrial applications of PID control. In: Vilanova R, Visioli A, eds. PID Control in the Third Millennium. London: Springer, 2012, 415–461

[27] Brogårdh T. Present and future robot control development—An industrial perspective. Annual Reviews in Control, 2007, 31(1): 69–79

[28] Brogårdh T. Robot control overview: An industrial perspective. Modeling, Identification and Control, 2009, 30(3): 167–180

[29] Khan M F, Iqbal J, Islam R U. Control strategies for robotic manipulators. In: 2012 International Conference on Robotics and Artificial Intelligence (ICRAI). Rawalpindi: IEEE, 2012, 26–33

[30] Craig J J. Introduction to Robotics. Addison-Wesley Reading, MA, 2006

[31] Liang C, Ceccarelli M. Feasible workspace regions for general two-revolute manipulator. Frontiers of Mechanical Engineering, 2011, 6(4): 397–408

[32] Islam R U, Iqbal J, Manzoor S, . An autonomous image—Guided robotic system simulating industrial applications. In: 2012 7th International Conference on System of Systems Engineering (SoSE). Genoa: IEEE, 2012, 344–349

[33] Manzoor S, Islam R U, Khalid A, . An open-source multi-DOF articulated robotic educational platform for autonomous object manipulation. Robotics and Computer-integrated Manufacturing, 2014, 30(3): 351–362

[34] Álvarez Chavarría J S, Jiménez Builes J A, Ramírez Patiño J F. Design cycle of a robot for learning and the development of creativity in engineering. DYNA, 2011, 78(170): 51–58

[35] Ajwad S A, Ullah M I, Islam R U, . Modeling robotic arms-A review and derivation of screw theory based kinematics. In: International Conference on Engineering & Emerging Technologies. Lahore, 2014, 66–69

[36] Yime-Rodríguez E, Peña-Cortés C A, Rojas-Contreras W M. The dynamic model of a four control moment gyroscope system. DYNA, 2014, 81(185): 41–47

[37] Márton L, Lantos B. Control of robotic systems with unknown friction and payload. IEEE Transactions on Control Systems Technology, 2011, 19(6): 1534–1539

[38] Iqbal J, Islam R U, Khan H. Modeling and analysis of a 6 DOF robotic arm manipulator. Canadian Journal on Electrical and Electronics Engineering, 2012, 3(6): 300–306

[39] Iqbal J, un Nabi S R, Khan A A, . A novel track-drive mobile robotic framework for conducting projects on robotics and control systems. Journal of Life Science, 2013, 10(3): 130–137

[40] Ajwad S A, Iqbal U, Iqbal J. Hardware realization and control of multi-degree of freedom articulated robotic arm. In: Emerging Trends and Applications in Information Communication Technologies, Communications in Computer and Information Science (CCIS). Berlin: Springer2015 (i<?Pub Caret?>n press)

[41] Fei Y, Wu Q. Tracking control of robot manipulators via output feedback linearization. Frontiers of Mechanical Engineering in China, 2006, 1(3): 329–335

[42] Nagaraj B, Murugananth N. A comparative study of PID controller tuning using GA, EP, PSO and ACO. In: 2010 IEEE International Conference on Communication Control and Computing Technologies (ICCCCT). Ramanathapuram: IEEE, 2010, 305–313

[43] Tan W, Liu J, Chen T, . Comparison of some well-known PID tuning formulas. Computers & Chemical Engineering, 2006, 30(9): 1416–1423

[44] Foley M W, Julien R H, Copeland B R. A comparison of PID controller tuning methods. Canadian Journal of Chemical Engineering, 2005, 83(4): 712–722

[45] Iqbal J, Tsagarakis N G, Caldwell D G. Human hand compatible underactuated exoskeleton robotic system. Electronics Letters, 2014, 50(7): 494–496

[46] Iqbal J, Khan H, Tsagarakis N G, . A novel exoskeleton robotic system for hand rehabilitation—Conceptualization to prototyping. Biocybernetics and Biomedical Engineering, 2014, 34(2): 79–89

[47] Iqbal U, Samad A, Nissa Z, . Embedded control system for AUTAREP—A novel AUTonomous articulated robotic educational platform. Technical Gazette, 2014, 21(6): 1255–1261

[48] Ajwad S, Ullah M, Baizid K, . A comprehensive state-of-the-art on control of industrial articulated robots. Journal of the Balkan Tribological Association, 2014, 20(4): 499–521

[49] Ullah M I, Ajwad S A, Islam R U, . Modeling and computed torque control of a 6 degree of freedom robotic arm. In: 2014 International Conference on Robotics & Emerging Allied Technologies in Engineering (iCREATE). Islamabad: IEEE, 2014, 133–138

[50] Piltan F, Sulaiman N, Jalali A, . Design of model free adaptive fuzzy computed torque controller: Applied to nonlinear second order system. International Journal of Robotics and Automation, 2011, 2(4): 232–244

[51] Sharkawy A B, Othman M M, Khalil A M A. A robust fuzzy tracking control scheme for robotic manipulators with experimental verification. Intelligent Control and Automation, 2011, 2(2): 100–111

[52] Chen Y, Ma G, Lin S, . Adaptive fuzzy computed-torque control for robot manipulator with uncertain dynamics. International Journal of Advanced Robotic Systems, 2012, 9: 237–245

[53] Leines M T, Yang J S. LQR control of an under actuated planar biped robot. In: 2011 6th IEEE Conference on Industrial Electronics and Applications (ICIEA). Beijing: IEEE, 2011, 1684–1689

[54] Simmons G, Demiris Y. Optimal robot arm control using the minimum variance model. Journal of Robotic Systems, 2005, 22(11): 677–690

[55] Islam R U, Iqbal J, Khan Q. Design and comparison of two control strategies for multi-DOF articulated robotic arm manipulator. Control Engineering and Applied Informatics, 2014, 16(2): 28–39

[56] Wai R J, Muthusamy R. Fuzzy-neural-network inherited sliding-mode control for robot manipulator including actuator dynamics. IEEE Transactions on Neural Networks and Learning Systems, 2013, 24(2): 274–287

[57] Nabaee A R, Piltan F, Ebrahimi M M, . Design intelligent robust partly linear term SMC for robot manipulator systems. International Journal of Intelligent Systems and Applications, 2014, 6: 58–71

[58] Hacioglu Y, Arslan Y Z, Yagiz N. MIMO fuzzy sliding mode controlled dual arm robot in load transportation. Journal of the Franklin Institute, 2011, 348(8): 1886–1902

[59] Corradini M L, Fossi V, Giantomassi A, . Discrete time sliding mode control of robotic manipulators: Development and experimental validation. Control Engineering Practice, 2012, 20(8): 816–822

[60] Laghrouche S, Mehmood A, Bagdouri M E. Study of the nonlinear control techniques for single acting VGT pneumatic actuator. International Journal of Vehicle Design, 2012, 60(3/4): 264–285

[61] Camacho E F, Alba C B. Model Predictive Control. Springer, 2013

[62] Wang L. Model Predictive Control System Design and Implementation Using MATLAB®. London: Springer, 2009

[63] Henmi T, Deng M, Inoue A. Adaptive control of a two-link planar manipulator using nonlinear model predictive control. In: 2010 International Conference on Mechatronics and Automation (ICMA). Xi’an: IEEE, 2010, 1868–1873

[64] Mazdarani H, Farrokhi M. Adaptive neuro-predictive control of robot manipulators in work space. In: 2012 17th International Conference on Methods and Models in Automation and Robotics (MMAR). Miedzyzdrojie: IEEE, 2012, 349–354

[65] Rojas–Moreno A, Valdivia–Mallqui R. Embedded position control system of a manipulator using a robust nonlinear predictive control. In: 2013 16th International Conference on Advanced Robotics (ICAR). Montevideo: IEEE, 2013, 1–6

[66] Copot C, Lazar C, Burlacu A. Predictive control of nonlinear visual servoing systems using image moments. IET Control Theory & Applications, 2012, 6(10): 1486–1496

[67] Wang L, Chai S, Rogers E, . Multivariable repetitive-predictive controllers using frequency decomposition. IEEE Transactions on Control Systems Technology, 2012, 20(6): 1597–1604

[68] Gu D W. Robust Control Design with MATLAB®. London: Springer, 2005

[69] Montano O E, Orlov Y. Discontinuous H. ∞-control of mechanical manipulators with frictional joints. In: 2012 9th International Conference on Electrical Engineering, Computing Science and Automatic Control (CCE). Mexico City: IEEE, 2012, 1–6

[70] Chen C. Robust self-organizing neural-fuzzy control with uncertainty observer for MIMO nonlinear systems. IEEE Transactions on Fuzzy Systems, 2011, 19(4): 694–706

[71] Siqueira A A G, Terra M H. Mixed model-based/neural network H∞ impedance control of constrained manipulators. In: IEEE International Conference on Control and Automation (ICCA). Christchurch: IEEE, 2009, 1901–1906

[72] Yang Z, Fukushima Y, Qin P. Decentralized adaptive robust control of robot manipulators using disturbance observers. IEEE Transactions on Control Systems Technology, 2012, 20(5): 1357–1365

[73] Kim Y, Seok J, Noh I, . An adaptive disturbance observer for a two-link robot manipulator. In: International Conference on Control, Automation and Systems (ICCAS). Seoul: IEEE, 2008, 141–145

[74] He Z, Xie W. Improved disturbance observer based control structure. In: Chinese Control and Decision Conference (CCDC). Guilin: IEEE, 2009, 1015–1020

[75] Parsa M, Farrokhi M. Robust nonlinear model predictive trajectory free control of biped robots based on nonlinear disturbance observer. In: 2010 18th Iranian Conference on Electrical Engineering (ICEE). Isfahan: IEEE, 2010, 617–622

[76] Mohammadi A, Tavakoli M, Marquez H. Disturbance observer-based control of non-linear haptic teleoperation systems. IET Control Theory & Applications, 2011, 5(18): 2063–2074

[77] Mohammadi A, Marquez H J, Tavakoli M. Disturbance observer-based trajectory following control of nonlinear robotic manipulators. In: Proceedings of the 23rd Canadian Congress of Applied Mechanics. 2011

[78] Mohammadi A, Tavakoli M, Marquez H, . Nonlinear disturbance observer design for robotic manipulators. Control Engineering Practice, 2013, 21(3): 253–267

[79] Laghrouche S, Ahmed F S, Mehmood A. Pressure and friction observer-based backstepping control for a VGT pneumatic actuator. IEEE Transactions on Control Systems Technology, 2014, 22(2): 456–467

[80] Arimoto S. Passivity-based control [robot dynamics]. In: IEEE International Conference on Robotics and Automation (ICRA) (Volume 1). San Francisco: IEEE, 2000, 227–232

[81] Shibata T, Murakami T. A null space force control based on passivity in redundant manipulator. In: ICM2007 4th IEEE International Conference on Mechatronics. Kumamoto: IEEE, 2007, 1–6

[82] Ott C, Albu-Schaffer A, Kugi A, . On the passivity-based impedance control of flexible joint robots. IEEE Transactions on Robotics, 2008, 24(2): 416–429

[83] Kawai H, Murao T, Sato R, . Passivity-based control for 2DOF robot manipulators with antagonistic bi-articular muscles. In: 2011 IEEE International Conference on Control Applications (CCA). Denver: IEEE, 2011, 1451–1456

[84] Foudil A, Hadia S. Passivity based control of a 3-DOF robot manipulator. In: International Conference on Communication, Computer & Power (ICCCP). Muscat, 2007, 56–59

[85] Bouakrif F, Boukhetala D, Boudjema F. Passivity-based controller-observer for robot manipulators. In: 3rd International Conference on Information and Communication Technologies: From Theory to Applications. Damascus: IEEE, 2008, 1–5

[86] Landau I D, Lozano R, M’Saad M, . Adaptive Control: Algorithms, Analysis and Applications. London: Springer, 2011

[87] Sun T, Pei H, Pan Y, . Neural network-based sliding mode adaptive control for robot manipulators. Neurocomputing, 2011, 74(14-15): 2377–2384

[88] Aseltine J, Mancini A, Sarture C. A survey of adaptive control systems. IRE Transactions on Automatic Control. 1958, 6(1): 102–108

[89] Åström K J, Wittenmark B. On self tuning regulators. Automatica, 1973, 9(2): 185–199

[90] Slotine J J E, Li W. On the adaptive control of robot manipulators. International Journal of Robotics Research, 1987, 6(3): 49–59

[91] Lozano R, Brogliato B. Adaptive control of robot manipulators with flexible joints. IEEE Transactions on Automatic Control, 1992, 37(2): 174–181

[92] Huang S, Tan K K, Lee T H. Adaptive friction compensation using neural network approximations. IEEE Transactions on Systems, Man, and Cybernetics, Part C: Applications and Reviews, 2000, 30(4): 551–557

[93] Purwar S, Kar I N, Jha A N. Adaptive control of robot manipulators using fuzzy logic systems under actuator constraints. In: 2004 IEEE International Conference on Fuzzy Systems (Volume 3). IEEE, 2004, 1449–1454

[94] Schindele D, Aschemann H. Adaptive friction compensation based on the LuGre model for a pneumatic rodless cylinder. In: Industrial Electronics, 2009. IECON’09 35th Annual Conference of IEEE. Porto: IEEE, 2009, 1432–1437

[95] Garpinger O, Hägglund T, Cederqvist L. Software for PID design: Benefits and pitfalls. In: 2nd IFAC Conference on Advances in PID Control. Brescia, 2012, 2(1): 140–145

[96] Jara C A, Candelas F A, Gil P, . Ejs+EjsRL: An interactive tool for industrial robots simulation, computer vision and remote operation. Robotics and Autonomous Systems, 2011, 59(6): 389–401

[97] Corke P I. A robotics toolbox for MATLAB. IEEE Robotics & Automation Magazine, 1996, 3(1): 24–32

[98] Corke P. Robotics, Vision and Control: Fundamental Algorithms in MATLAB. Berlin: Springer, 2011

[99] Falconi R, Melchiorri C. Roboticad: An educational tool for robotics. In: Proceedings of the 17th IFAC World Congress. Korea, 2008, 9111–9116

[100] Žlajpah L. Integrated environment for modelling, simulation and control design for robotic manipulators. Journal of Intelligent & Robotic Systems, 2001, 32(2): 219–234

[101] Maza J I, Ollero A. HEMERO: A MATLAB-Simulink toolbox for robotics. In: 1st Workshop on Robotics Education and Training. Germany, 2001, 43–50

[102] Alsina P J. ROBOTLAB: A software for robot graphic simulation. Simpósio Brasileiro de Automação Inteligente, 1997, 465–470

[103] Nethery J F, Spong M W. Robotica: A mathematica package for robot analysis. IEEE Robotics & Automation Magazine, 1994, 1(1): 13–20

[104] Dean-Leon E, Nair S, Knoll A. User friendly Matlab-toolbox for symbolic robot dynamic modeling used for control design. In: 2012 IEEE International Conference on Robotics and Biomimetics (ROBIO). Guangzhou: IEEE, 2012, 2181–2188

[105] Rohmer E, Singh S P, Freese M. V-REP: A versatile and scalable robot simulation framework. In: 2013 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS). Tokyo: IEEE, 2013, 1321–1326

[106] Breijs A, Klaassens B, Babuska R. Matlab design environment for robotic manipulators. In: 16th IFAC World Congress. Prague, 2005, 1331–1336

[107] Shah S V, Nandihal P V, Saha S K. Recursive dynamics simulator (ReDySim): A multibody dynamics solver. Theoretical and Applied Mechanics Letters, 2012, 2: 063011

[108] Ferreira N F, Machado J T. RobLib: An educational program for robotics. In: Symposium on Robot Control (SYROCO). Vienna, 2000, 563–568

[109] Arm6x Manual. Concurrent Dynamics International, 2014

[110] Fueanggan S, Chokchaitam S. Dynamics and kinematics simulation for robots. In: International Association of Computer Science and Information Technology—Spring Conference. Singapore: IEEE, 2009, 136–140

Acknowledgements

Special thanks to Raza Ul Islam, Research Associate, CAST, COMSATS Institute of Information Technology, Islamabad, Pakistan for his kind help in implementation of various control strategies.

RIGHTS & PERMISSIONS

2014 Higher Education Press and Springer-Verlag Berlin Heidelberg